diff options
132 files changed, 1160 insertions, 973 deletions
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/BaseMutableRow.java b/sql/catalyst/src/main/java/org/apache/spark/sql/BaseMutableRow.java index acec2bf452..acec2bf452 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/BaseMutableRow.java +++ b/sql/catalyst/src/main/java/org/apache/spark/sql/BaseMutableRow.java diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/BaseRow.java b/sql/catalyst/src/main/java/org/apache/spark/sql/BaseRow.java index e91daf17f8..611e02d8fb 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/BaseRow.java +++ b/sql/catalyst/src/main/java/org/apache/spark/sql/BaseRow.java @@ -25,10 +25,11 @@ import java.util.List; import scala.collection.Seq; import scala.collection.mutable.ArraySeq; +import org.apache.spark.sql.catalyst.InternalRow; import org.apache.spark.sql.catalyst.expressions.GenericRow; import org.apache.spark.sql.types.StructType; -public abstract class BaseRow implements Row { +public abstract class BaseRow extends InternalRow { @Override final public int length() { @@ -176,7 +177,7 @@ public abstract class BaseRow implements Row { } @Override - public Row copy() { + public InternalRow copy() { final int n = size(); Object[] arr = new Object[n]; for (int i = 0; i < n; i++) { diff --git a/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMap.java b/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMap.java index 299ff3728a..b23e0efc83 100644 --- a/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMap.java +++ b/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMap.java @@ -20,7 +20,7 @@ package org.apache.spark.sql.catalyst.expressions; import java.util.Arrays; import java.util.Iterator; -import org.apache.spark.sql.Row; +import org.apache.spark.sql.catalyst.InternalRow; import org.apache.spark.sql.types.StructField; import org.apache.spark.sql.types.StructType; import org.apache.spark.unsafe.PlatformDependent; @@ -107,7 +107,7 @@ public final class UnsafeFixedWidthAggregationMap { * @param enablePerfMetrics if true, performance metrics will be recorded (has minor perf impact) */ public UnsafeFixedWidthAggregationMap( - Row emptyAggregationBuffer, + InternalRow emptyAggregationBuffer, StructType aggregationBufferSchema, StructType groupingKeySchema, TaskMemoryManager memoryManager, @@ -125,7 +125,7 @@ public final class UnsafeFixedWidthAggregationMap { /** * Convert a Java object row into an UnsafeRow, allocating it into a new long array. */ - private static long[] convertToUnsafeRow(Row javaRow, StructType schema) { + private static long[] convertToUnsafeRow(InternalRow javaRow, StructType schema) { final UnsafeRowConverter converter = new UnsafeRowConverter(schema); final long[] unsafeRow = new long[converter.getSizeRequirement(javaRow)]; final long writtenLength = @@ -138,7 +138,7 @@ public final class UnsafeFixedWidthAggregationMap { * Return the aggregation buffer for the current group. For efficiency, all calls to this method * return the same object. */ - public UnsafeRow getAggregationBuffer(Row groupingKey) { + public UnsafeRow getAggregationBuffer(InternalRow groupingKey) { final int groupingKeySize = groupingKeyToUnsafeRowConverter.getSizeRequirement(groupingKey); // Make sure that the buffer is large enough to hold the key. If it's not, grow it: if (groupingKeySize > groupingKeyConversionScratchSpace.length) { diff --git a/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeRow.java b/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeRow.java index 143acc9f5e..aec88c9241 100644 --- a/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeRow.java +++ b/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeRow.java @@ -26,7 +26,7 @@ import java.util.Set; import scala.collection.Seq; import scala.collection.mutable.ArraySeq; -import org.apache.spark.sql.Row; +import org.apache.spark.sql.catalyst.InternalRow; import org.apache.spark.sql.BaseMutableRow; import org.apache.spark.sql.types.DataType; import org.apache.spark.sql.types.StructType; @@ -334,7 +334,7 @@ public final class UnsafeRow extends BaseMutableRow { @Override - public Row copy() { + public InternalRow copy() { throw new UnsupportedOperationException(); } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala index 7e4b11a495..6175456c58 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/CatalystTypeConverters.scala @@ -27,6 +27,7 @@ import scala.collection.mutable.HashMap import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.util.DateUtils +import org.apache.spark.sql.Row import org.apache.spark.sql.types._ import org.apache.spark.unsafe.types.UTF8String @@ -105,7 +106,7 @@ object CatalystTypeConverters { /** * Given a Catalyst row, convert the value at column `column` to its Scala equivalent. */ - final def toScala(row: Row, column: Int): ScalaOutputType = { + final def toScala(row: InternalRow, column: Int): ScalaOutputType = { if (row.isNullAt(column)) null.asInstanceOf[ScalaOutputType] else toScalaImpl(row, column) } @@ -125,20 +126,20 @@ object CatalystTypeConverters { * Given a Catalyst row, convert the value at column `column` to its Scala equivalent. * This method will only be called on non-null columns. */ - protected def toScalaImpl(row: Row, column: Int): ScalaOutputType + protected def toScalaImpl(row: InternalRow, column: Int): ScalaOutputType } private object IdentityConverter extends CatalystTypeConverter[Any, Any, Any] { override def toCatalystImpl(scalaValue: Any): Any = scalaValue override def toScala(catalystValue: Any): Any = catalystValue - override def toScalaImpl(row: Row, column: Int): Any = row(column) + override def toScalaImpl(row: InternalRow, column: Int): Any = row(column) } private case class UDTConverter( udt: UserDefinedType[_]) extends CatalystTypeConverter[Any, Any, Any] { override def toCatalystImpl(scalaValue: Any): Any = udt.serialize(scalaValue) override def toScala(catalystValue: Any): Any = udt.deserialize(catalystValue) - override def toScalaImpl(row: Row, column: Int): Any = toScala(row(column)) + override def toScalaImpl(row: InternalRow, column: Int): Any = toScala(row(column)) } /** Converter for arrays, sequences, and Java iterables. */ @@ -170,7 +171,7 @@ object CatalystTypeConverters { } } - override def toScalaImpl(row: Row, column: Int): Seq[Any] = + override def toScalaImpl(row: InternalRow, column: Int): Seq[Any] = toScala(row(column).asInstanceOf[Seq[Any]]) } @@ -209,16 +210,16 @@ object CatalystTypeConverters { } } - override def toScalaImpl(row: Row, column: Int): Map[Any, Any] = + override def toScalaImpl(row: InternalRow, column: Int): Map[Any, Any] = toScala(row(column).asInstanceOf[Map[Any, Any]]) } private case class StructConverter( - structType: StructType) extends CatalystTypeConverter[Any, Row, Row] { + structType: StructType) extends CatalystTypeConverter[Any, Row, InternalRow] { private[this] val converters = structType.fields.map { f => getConverterForType(f.dataType) } - override def toCatalystImpl(scalaValue: Any): Row = scalaValue match { + override def toCatalystImpl(scalaValue: Any): InternalRow = scalaValue match { case row: Row => val ar = new Array[Any](row.size) var idx = 0 @@ -239,7 +240,7 @@ object CatalystTypeConverters { new GenericRowWithSchema(ar, structType) } - override def toScala(row: Row): Row = { + override def toScala(row: InternalRow): Row = { if (row == null) { null } else { @@ -253,7 +254,8 @@ object CatalystTypeConverters { } } - override def toScalaImpl(row: Row, column: Int): Row = toScala(row(column).asInstanceOf[Row]) + override def toScalaImpl(row: InternalRow, column: Int): Row = + toScala(row(column).asInstanceOf[InternalRow]) } private object StringConverter extends CatalystTypeConverter[Any, String, Any] { @@ -266,14 +268,14 @@ object CatalystTypeConverters { case str: String => str case utf8: UTF8String => utf8.toString() } - override def toScalaImpl(row: Row, column: Int): String = row(column).toString + override def toScalaImpl(row: InternalRow, column: Int): String = row(column).toString } private object DateConverter extends CatalystTypeConverter[Date, Date, Any] { override def toCatalystImpl(scalaValue: Date): Int = DateUtils.fromJavaDate(scalaValue) override def toScala(catalystValue: Any): Date = if (catalystValue == null) null else DateUtils.toJavaDate(catalystValue.asInstanceOf[Int]) - override def toScalaImpl(row: Row, column: Int): Date = toScala(row.getInt(column)) + override def toScalaImpl(row: InternalRow, column: Int): Date = toScala(row.getInt(column)) } private object TimestampConverter extends CatalystTypeConverter[Timestamp, Timestamp, Any] { @@ -282,7 +284,8 @@ object CatalystTypeConverters { override def toScala(catalystValue: Any): Timestamp = if (catalystValue == null) null else DateUtils.toJavaTimestamp(catalystValue.asInstanceOf[Long]) - override def toScalaImpl(row: Row, column: Int): Timestamp = toScala(row.getLong(column)) + override def toScalaImpl(row: InternalRow, column: Int): Timestamp = + toScala(row.getLong(column)) } private object BigDecimalConverter extends CatalystTypeConverter[Any, JavaBigDecimal, Decimal] { @@ -292,10 +295,11 @@ object CatalystTypeConverters { case d: Decimal => d } override def toScala(catalystValue: Decimal): JavaBigDecimal = catalystValue.toJavaBigDecimal - override def toScalaImpl(row: Row, column: Int): JavaBigDecimal = row.get(column) match { - case d: JavaBigDecimal => d - case d: Decimal => d.toJavaBigDecimal - } + override def toScalaImpl(row: InternalRow, column: Int): JavaBigDecimal = + row.get(column) match { + case d: JavaBigDecimal => d + case d: Decimal => d.toJavaBigDecimal + } } private abstract class PrimitiveConverter[T] extends CatalystTypeConverter[T, Any, Any] { @@ -304,31 +308,31 @@ object CatalystTypeConverters { } private object BooleanConverter extends PrimitiveConverter[Boolean] { - override def toScalaImpl(row: Row, column: Int): Boolean = row.getBoolean(column) + override def toScalaImpl(row: InternalRow, column: Int): Boolean = row.getBoolean(column) } private object ByteConverter extends PrimitiveConverter[Byte] { - override def toScalaImpl(row: Row, column: Int): Byte = row.getByte(column) + override def toScalaImpl(row: InternalRow, column: Int): Byte = row.getByte(column) } private object ShortConverter extends PrimitiveConverter[Short] { - override def toScalaImpl(row: Row, column: Int): Short = row.getShort(column) + override def toScalaImpl(row: InternalRow, column: Int): Short = row.getShort(column) } private object IntConverter extends PrimitiveConverter[Int] { - override def toScalaImpl(row: Row, column: Int): Int = row.getInt(column) + override def toScalaImpl(row: InternalRow, column: Int): Int = row.getInt(column) } private object LongConverter extends PrimitiveConverter[Long] { - override def toScalaImpl(row: Row, column: Int): Long = row.getLong(column) + override def toScalaImpl(row: InternalRow, column: Int): Long = row.getLong(column) } private object FloatConverter extends PrimitiveConverter[Float] { - override def toScalaImpl(row: Row, column: Int): Float = row.getFloat(column) + override def toScalaImpl(row: InternalRow, column: Int): Float = row.getFloat(column) } private object DoubleConverter extends PrimitiveConverter[Double] { - override def toScalaImpl(row: Row, column: Int): Double = row.getDouble(column) + override def toScalaImpl(row: InternalRow, column: Int): Double = row.getDouble(column) } /** @@ -382,7 +386,7 @@ object CatalystTypeConverters { case d: BigDecimal => BigDecimalConverter.toCatalyst(d) case d: JavaBigDecimal => BigDecimalConverter.toCatalyst(d) case seq: Seq[Any] => seq.map(convertToCatalyst) - case r: Row => Row(r.toSeq.map(convertToCatalyst): _*) + case r: Row => InternalRow(r.toSeq.map(convertToCatalyst): _*) case arr: Array[Any] => arr.toSeq.map(convertToCatalyst).toArray case m: Map[Any, Any] => m.map { case (k, v) => (convertToCatalyst(k), convertToCatalyst(v)) }.toMap diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/InternalRow.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/InternalRow.scala new file mode 100644 index 0000000000..e3c2cc2433 --- /dev/null +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/InternalRow.scala @@ -0,0 +1,57 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.catalyst + +import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.expressions.GenericRow + +/** + * An abstract class for row used internal in Spark SQL, which only contain the columns as + * internal types. + */ +abstract class InternalRow extends Row { + // A default implementation to change the return type + override def copy(): InternalRow = {this} +} + +object InternalRow { + def unapplySeq(row: InternalRow): Some[Seq[Any]] = Some(row.toSeq) + + /** + * This method can be used to construct a [[Row]] with the given values. + */ + def apply(values: Any*): InternalRow = new GenericRow(values.toArray) + + /** + * This method can be used to construct a [[Row]] from a [[Seq]] of values. + */ + def fromSeq(values: Seq[Any]): InternalRow = new GenericRow(values.toArray) + + def fromTuple(tuple: Product): InternalRow = fromSeq(tuple.productIterator.toSeq) + + /** + * Merge multiple rows into a single row, one after another. + */ + def merge(rows: InternalRow*): InternalRow = { + // TODO: Improve the performance of this if used in performance critical part. + new GenericRow(rows.flatMap(_.toSeq).toArray) + } + + /** Returns an empty row. */ + val empty = apply() +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala index bbb150c1e8..5de188d418 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.catalyst.analysis +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.{errors, trees} import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.expressions._ @@ -67,7 +68,7 @@ case class UnresolvedAttribute(nameParts: Seq[String]) override def withName(newName: String): UnresolvedAttribute = UnresolvedAttribute.quoted(newName) // Unresolved attributes are transient at compile time and don't get evaluated during execution. - override def eval(input: Row = null): Any = + override def eval(input: catalyst.InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") override def toString: String = s"'$name" @@ -85,7 +86,7 @@ case class UnresolvedFunction(name: String, children: Seq[Expression]) extends E override lazy val resolved = false // Unresolved functions are transient at compile time and don't get evaluated during execution. - override def eval(input: Row = null): Any = + override def eval(input: catalyst.InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") override def toString: String = s"'$name(${children.mkString(",")})" @@ -107,7 +108,7 @@ trait Star extends NamedExpression with trees.LeafNode[Expression] { override lazy val resolved = false // Star gets expanded at runtime so we never evaluate a Star. - override def eval(input: Row = null): Any = + override def eval(input: catalyst.InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") def expand(input: Seq[Attribute], resolver: Resolver): Seq[NamedExpression] @@ -166,7 +167,7 @@ case class MultiAlias(child: Expression, names: Seq[String]) override lazy val resolved = false - override def eval(input: Row = null): Any = + override def eval(input: catalyst.InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") override def toString: String = s"$child AS $names" @@ -200,7 +201,7 @@ case class UnresolvedExtractValue(child: Expression, extraction: Expression) override def nullable: Boolean = throw new UnresolvedException(this, "nullable") override lazy val resolved = false - override def eval(input: Row = null): Any = + override def eval(input: catalyst.InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") override def toString: String = s"$child[$extraction]" diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala index fcadf9595e..c4dd11a451 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala @@ -21,7 +21,7 @@ import org.apache.spark.Logging import org.apache.spark.sql.catalyst.errors.attachTree import org.apache.spark.sql.catalyst.expressions.codegen.{GeneratedExpressionCode, CodeGenContext} import org.apache.spark.sql.types._ -import org.apache.spark.sql.catalyst.trees +import org.apache.spark.sql.catalyst.{InternalRow, trees} /** * A bound reference points to a specific slot in the input tuple, allowing the actual value @@ -33,7 +33,7 @@ case class BoundReference(ordinal: Int, dataType: DataType, nullable: Boolean) override def toString: String = s"input[$ordinal]" - override def eval(input: Row): Any = input(ordinal) + override def eval(input: InternalRow): Any = input(ordinal) override def name: String = s"i[$ordinal]" diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala index 4c7123fcb7..afbf30af33 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala @@ -21,6 +21,7 @@ import java.sql.{Date, Timestamp} import java.text.{DateFormat, SimpleDateFormat} import org.apache.spark.Logging +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.expressions.codegen.{CodeGenContext, GeneratedExpressionCode} import org.apache.spark.sql.catalyst.util.DateUtils import org.apache.spark.sql.types._ @@ -393,7 +394,7 @@ case class Cast(child: Expression, dataType: DataType) extends UnaryExpression w } // TODO: Could be faster? val newRow = new GenericMutableRow(from.fields.size) - buildCast[Row](_, row => { + buildCast[catalyst.InternalRow](_, row => { var i = 0 while (i < row.length) { val v = row(i) @@ -425,7 +426,7 @@ case class Cast(child: Expression, dataType: DataType) extends UnaryExpression w private[this] lazy val cast: Any => Any = cast(child.dataType, dataType) - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evaluated = child.eval(input) if (evaluated == null) null else cast(evaluated) } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala index 0b9f621fed..61de34bfa4 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.catalyst.analysis.{TypeCheckResult, UnresolvedAttribute} -import org.apache.spark.sql.catalyst.expressions.codegen.{GeneratedExpressionCode, CodeGenContext} +import org.apache.spark.sql.catalyst.expressions.codegen.{CodeGenContext, GeneratedExpressionCode} import org.apache.spark.sql.catalyst.trees import org.apache.spark.sql.catalyst.trees.TreeNode import org.apache.spark.sql.types._ @@ -59,7 +59,7 @@ abstract class Expression extends TreeNode[Expression] { def references: AttributeSet = AttributeSet(children.flatMap(_.references.iterator)) /** Returns the result of evaluating this expression on a given input Row */ - def eval(input: Row = null): Any + def eval(input: InternalRow = null): Any /** * Returns an [[GeneratedExpressionCode]], which contains Java source code that diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExtractValue.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExtractValue.scala index a1e0819e8a..16f3ccc3d6 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExtractValue.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExtractValue.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions import scala.collection.Map -import org.apache.spark.sql.AnalysisException +import org.apache.spark.sql.{catalyst, AnalysisException} import org.apache.spark.sql.catalyst.analysis._ import org.apache.spark.sql.types._ @@ -105,8 +105,8 @@ case class GetStructField(child: Expression, field: StructField, ordinal: Int) override def foldable: Boolean = child.foldable override def toString: String = s"$child.${field.name}" - override def eval(input: Row): Any = { - val baseValue = child.eval(input).asInstanceOf[Row] + override def eval(input: catalyst.InternalRow): Any = { + val baseValue = child.eval(input).asInstanceOf[catalyst.InternalRow] if (baseValue == null) null else baseValue(ordinal) } } @@ -125,8 +125,8 @@ case class GetArrayStructFields( override def foldable: Boolean = child.foldable override def toString: String = s"$child.${field.name}" - override def eval(input: Row): Any = { - val baseValue = child.eval(input).asInstanceOf[Seq[Row]] + override def eval(input: catalyst.InternalRow): Any = { + val baseValue = child.eval(input).asInstanceOf[Seq[catalyst.InternalRow]] if (baseValue == null) null else { baseValue.map { row => if (row == null) null else row(ordinal) @@ -146,7 +146,7 @@ abstract class ExtractValueWithOrdinal extends ExtractValue { override def toString: String = s"$child[$ordinal]" override def children: Seq[Expression] = child :: ordinal :: Nil - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val value = child.eval(input) if (value == null) { null diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Projection.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Projection.scala index 8cae548279..d6806f78ab 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Projection.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Projection.scala @@ -17,6 +17,8 @@ package org.apache.spark.sql.catalyst.expressions +import org.apache.spark.sql.catalyst + /** * A [[Projection]] that is calculated by calling the `eval` of each of the specified expressions. @@ -30,7 +32,7 @@ class InterpretedProjection(expressions: Seq[Expression]) extends Projection { // null check is required for when Kryo invokes the no-arg constructor. protected val exprArray = if (expressions != null) expressions.toArray else null - def apply(input: Row): Row = { + def apply(input: catalyst.InternalRow): catalyst.InternalRow = { val outputArray = new Array[Any](exprArray.length) var i = 0 while (i < exprArray.length) { @@ -55,14 +57,14 @@ case class InterpretedMutableProjection(expressions: Seq[Expression]) extends Mu private[this] val exprArray = expressions.toArray private[this] var mutableRow: MutableRow = new GenericMutableRow(exprArray.size) - def currentValue: Row = mutableRow + def currentValue: catalyst.InternalRow = mutableRow override def target(row: MutableRow): MutableProjection = { mutableRow = row this } - override def apply(input: Row): Row = { + override def apply(input: catalyst.InternalRow): catalyst.InternalRow = { var i = 0 while (i < exprArray.length) { mutableRow(i) = exprArray(i).eval(input) @@ -76,31 +78,31 @@ case class InterpretedMutableProjection(expressions: Seq[Expression]) extends Mu * A mutable wrapper that makes two rows appear as a single concatenated row. Designed to * be instantiated once per thread and reused. */ -class JoinedRow extends Row { - private[this] var row1: Row = _ - private[this] var row2: Row = _ +class JoinedRow extends catalyst.InternalRow { + private[this] var row1: catalyst.InternalRow = _ + private[this] var row2: catalyst.InternalRow = _ - def this(left: Row, right: Row) = { + def this(left: catalyst.InternalRow, right: catalyst.InternalRow) = { this() row1 = left row2 = right } /** Updates this JoinedRow to used point at two new base rows. Returns itself. */ - def apply(r1: Row, r2: Row): Row = { + def apply(r1: catalyst.InternalRow, r2: catalyst.InternalRow): catalyst.InternalRow = { row1 = r1 row2 = r2 this } /** Updates this JoinedRow by updating its left base row. Returns itself. */ - def withLeft(newLeft: Row): Row = { + def withLeft(newLeft: catalyst.InternalRow): catalyst.InternalRow = { row1 = newLeft this } /** Updates this JoinedRow by updating its right base row. Returns itself. */ - def withRight(newRight: Row): Row = { + def withRight(newRight: catalyst.InternalRow): catalyst.InternalRow = { row2 = newRight this } @@ -142,7 +144,7 @@ class JoinedRow extends Row { override def getAs[T](i: Int): T = if (i < row1.length) row1.getAs[T](i) else row2.getAs[T](i - row1.length) - override def copy(): Row = { + override def copy(): catalyst.InternalRow = { val totalSize = row1.length + row2.length val copiedValues = new Array[Any](totalSize) var i = 0 @@ -176,31 +178,31 @@ class JoinedRow extends Row { * Row will be referenced, increasing the opportunity for the JIT to play tricks. This sounds * crazy but in benchmarks it had noticeable effects. */ -class JoinedRow2 extends Row { - private[this] var row1: Row = _ - private[this] var row2: Row = _ +class JoinedRow2 extends catalyst.InternalRow { + private[this] var row1: catalyst.InternalRow = _ + private[this] var row2: catalyst.InternalRow = _ - def this(left: Row, right: Row) = { + def this(left: catalyst.InternalRow, right: catalyst.InternalRow) = { this() row1 = left row2 = right } /** Updates this JoinedRow to used point at two new base rows. Returns itself. */ - def apply(r1: Row, r2: Row): Row = { + def apply(r1: catalyst.InternalRow, r2: catalyst.InternalRow): catalyst.InternalRow = { row1 = r1 row2 = r2 this } /** Updates this JoinedRow by updating its left base row. Returns itself. */ - def withLeft(newLeft: Row): Row = { + def withLeft(newLeft: catalyst.InternalRow): catalyst.InternalRow = { row1 = newLeft this } /** Updates this JoinedRow by updating its right base row. Returns itself. */ - def withRight(newRight: Row): Row = { + def withRight(newRight: catalyst.InternalRow): catalyst.InternalRow = { row2 = newRight this } @@ -242,7 +244,7 @@ class JoinedRow2 extends Row { override def getAs[T](i: Int): T = if (i < row1.length) row1.getAs[T](i) else row2.getAs[T](i - row1.length) - override def copy(): Row = { + override def copy(): catalyst.InternalRow = { val totalSize = row1.length + row2.length val copiedValues = new Array[Any](totalSize) var i = 0 @@ -270,31 +272,31 @@ class JoinedRow2 extends Row { /** * JIT HACK: Replace with macros */ -class JoinedRow3 extends Row { - private[this] var row1: Row = _ - private[this] var row2: Row = _ +class JoinedRow3 extends catalyst.InternalRow { + private[this] var row1: catalyst.InternalRow = _ + private[this] var row2: catalyst.InternalRow = _ - def this(left: Row, right: Row) = { + def this(left: catalyst.InternalRow, right: catalyst.InternalRow) = { this() row1 = left row2 = right } /** Updates this JoinedRow to used point at two new base rows. Returns itself. */ - def apply(r1: Row, r2: Row): Row = { + def apply(r1: catalyst.InternalRow, r2: catalyst.InternalRow): catalyst.InternalRow = { row1 = r1 row2 = r2 this } /** Updates this JoinedRow by updating its left base row. Returns itself. */ - def withLeft(newLeft: Row): Row = { + def withLeft(newLeft: catalyst.InternalRow): catalyst.InternalRow = { row1 = newLeft this } /** Updates this JoinedRow by updating its right base row. Returns itself. */ - def withRight(newRight: Row): Row = { + def withRight(newRight: catalyst.InternalRow): catalyst.InternalRow = { row2 = newRight this } @@ -336,7 +338,7 @@ class JoinedRow3 extends Row { override def getAs[T](i: Int): T = if (i < row1.length) row1.getAs[T](i) else row2.getAs[T](i - row1.length) - override def copy(): Row = { + override def copy(): catalyst.InternalRow = { val totalSize = row1.length + row2.length val copiedValues = new Array[Any](totalSize) var i = 0 @@ -364,31 +366,31 @@ class JoinedRow3 extends Row { /** * JIT HACK: Replace with macros */ -class JoinedRow4 extends Row { - private[this] var row1: Row = _ - private[this] var row2: Row = _ +class JoinedRow4 extends catalyst.InternalRow { + private[this] var row1: catalyst.InternalRow = _ + private[this] var row2: catalyst.InternalRow = _ - def this(left: Row, right: Row) = { + def this(left: catalyst.InternalRow, right: catalyst.InternalRow) = { this() row1 = left row2 = right } /** Updates this JoinedRow to used point at two new base rows. Returns itself. */ - def apply(r1: Row, r2: Row): Row = { + def apply(r1: catalyst.InternalRow, r2: catalyst.InternalRow): catalyst.InternalRow = { row1 = r1 row2 = r2 this } /** Updates this JoinedRow by updating its left base row. Returns itself. */ - def withLeft(newLeft: Row): Row = { + def withLeft(newLeft: catalyst.InternalRow): catalyst.InternalRow = { row1 = newLeft this } /** Updates this JoinedRow by updating its right base row. Returns itself. */ - def withRight(newRight: Row): Row = { + def withRight(newRight: catalyst.InternalRow): catalyst.InternalRow = { row2 = newRight this } @@ -430,7 +432,7 @@ class JoinedRow4 extends Row { override def getAs[T](i: Int): T = if (i < row1.length) row1.getAs[T](i) else row2.getAs[T](i - row1.length) - override def copy(): Row = { + override def copy(): catalyst.InternalRow = { val totalSize = row1.length + row2.length val copiedValues = new Array[Any](totalSize) var i = 0 @@ -458,31 +460,31 @@ class JoinedRow4 extends Row { /** * JIT HACK: Replace with macros */ -class JoinedRow5 extends Row { - private[this] var row1: Row = _ - private[this] var row2: Row = _ +class JoinedRow5 extends catalyst.InternalRow { + private[this] var row1: catalyst.InternalRow = _ + private[this] var row2: catalyst.InternalRow = _ - def this(left: Row, right: Row) = { + def this(left: catalyst.InternalRow, right: catalyst.InternalRow) = { this() row1 = left row2 = right } /** Updates this JoinedRow to used point at two new base rows. Returns itself. */ - def apply(r1: Row, r2: Row): Row = { + def apply(r1: catalyst.InternalRow, r2: catalyst.InternalRow): catalyst.InternalRow = { row1 = r1 row2 = r2 this } /** Updates this JoinedRow by updating its left base row. Returns itself. */ - def withLeft(newLeft: Row): Row = { + def withLeft(newLeft: catalyst.InternalRow): catalyst.InternalRow = { row1 = newLeft this } /** Updates this JoinedRow by updating its right base row. Returns itself. */ - def withRight(newRight: Row): Row = { + def withRight(newRight: catalyst.InternalRow): catalyst.InternalRow = { row2 = newRight this } @@ -524,7 +526,7 @@ class JoinedRow5 extends Row { override def getAs[T](i: Int): T = if (i < row1.length) row1.getAs[T](i) else row2.getAs[T](i - row1.length) - override def copy(): Row = { + override def copy(): catalyst.InternalRow = { val totalSize = row1.length + row2.length val copiedValues = new Array[Any](totalSize) var i = 0 @@ -552,31 +554,31 @@ class JoinedRow5 extends Row { /** * JIT HACK: Replace with macros */ -class JoinedRow6 extends Row { - private[this] var row1: Row = _ - private[this] var row2: Row = _ +class JoinedRow6 extends catalyst.InternalRow { + private[this] var row1: catalyst.InternalRow = _ + private[this] var row2: catalyst.InternalRow = _ - def this(left: Row, right: Row) = { + def this(left: catalyst.InternalRow, right: catalyst.InternalRow) = { this() row1 = left row2 = right } /** Updates this JoinedRow to used point at two new base rows. Returns itself. */ - def apply(r1: Row, r2: Row): Row = { + def apply(r1: catalyst.InternalRow, r2: catalyst.InternalRow): catalyst.InternalRow = { row1 = r1 row2 = r2 this } /** Updates this JoinedRow by updating its left base row. Returns itself. */ - def withLeft(newLeft: Row): Row = { + def withLeft(newLeft: catalyst.InternalRow): catalyst.InternalRow = { row1 = newLeft this } /** Updates this JoinedRow by updating its right base row. Returns itself. */ - def withRight(newRight: Row): Row = { + def withRight(newRight: catalyst.InternalRow): catalyst.InternalRow = { row2 = newRight this } @@ -618,7 +620,7 @@ class JoinedRow6 extends Row { override def getAs[T](i: Int): T = if (i < row1.length) row1.getAs[T](i) else row2.getAs[T](i - row1.length) - override def copy(): Row = { + override def copy(): catalyst.InternalRow = { val totalSize = row1.length + row2.length val copiedValues = new Array[Any](totalSize) var i = 0 diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala index 5b45347872..40f235fc19 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.catalyst.expressions +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.CatalystTypeConverters import org.apache.spark.sql.types.DataType @@ -45,7 +46,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi val func = function.asInstanceOf[($anys) => Any] $childs $converters - (input: Row) => { + (input: InternalRow) => { func( $evals) } @@ -57,7 +58,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi private[this] val f = children.size match { case 0 => val func = function.asInstanceOf[() => Any] - (input: Row) => { + (input: catalyst.InternalRow) => { func() } @@ -65,7 +66,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi val func = function.asInstanceOf[(Any) => Any] val child0 = children(0) lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input))) } @@ -76,7 +77,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi val child1 = children(1) lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType) lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input))) @@ -90,7 +91,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter0 = CatalystTypeConverters.createToScalaConverter(child0.dataType) lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType) lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -107,7 +108,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter1 = CatalystTypeConverters.createToScalaConverter(child1.dataType) lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType) lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -127,7 +128,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter2 = CatalystTypeConverters.createToScalaConverter(child2.dataType) lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType) lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -150,7 +151,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter3 = CatalystTypeConverters.createToScalaConverter(child3.dataType) lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType) lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -176,7 +177,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter4 = CatalystTypeConverters.createToScalaConverter(child4.dataType) lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType) lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -205,7 +206,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter5 = CatalystTypeConverters.createToScalaConverter(child5.dataType) lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType) lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -237,7 +238,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter6 = CatalystTypeConverters.createToScalaConverter(child6.dataType) lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType) lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -272,7 +273,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter7 = CatalystTypeConverters.createToScalaConverter(child7.dataType) lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType) lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -310,7 +311,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter8 = CatalystTypeConverters.createToScalaConverter(child8.dataType) lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType) lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -351,7 +352,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter9 = CatalystTypeConverters.createToScalaConverter(child9.dataType) lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType) lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -395,7 +396,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter10 = CatalystTypeConverters.createToScalaConverter(child10.dataType) lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType) lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -442,7 +443,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter11 = CatalystTypeConverters.createToScalaConverter(child11.dataType) lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType) lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -492,7 +493,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter12 = CatalystTypeConverters.createToScalaConverter(child12.dataType) lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType) lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -545,7 +546,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter13 = CatalystTypeConverters.createToScalaConverter(child13.dataType) lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType) lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -601,7 +602,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter14 = CatalystTypeConverters.createToScalaConverter(child14.dataType) lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType) lazy val converter16 = CatalystTypeConverters.createToScalaConverter(child16.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -660,7 +661,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter15 = CatalystTypeConverters.createToScalaConverter(child15.dataType) lazy val converter16 = CatalystTypeConverters.createToScalaConverter(child16.dataType) lazy val converter17 = CatalystTypeConverters.createToScalaConverter(child17.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -722,7 +723,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter16 = CatalystTypeConverters.createToScalaConverter(child16.dataType) lazy val converter17 = CatalystTypeConverters.createToScalaConverter(child17.dataType) lazy val converter18 = CatalystTypeConverters.createToScalaConverter(child18.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -787,7 +788,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter17 = CatalystTypeConverters.createToScalaConverter(child17.dataType) lazy val converter18 = CatalystTypeConverters.createToScalaConverter(child18.dataType) lazy val converter19 = CatalystTypeConverters.createToScalaConverter(child19.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -855,7 +856,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter18 = CatalystTypeConverters.createToScalaConverter(child18.dataType) lazy val converter19 = CatalystTypeConverters.createToScalaConverter(child19.dataType) lazy val converter20 = CatalystTypeConverters.createToScalaConverter(child20.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -926,7 +927,7 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi lazy val converter19 = CatalystTypeConverters.createToScalaConverter(child19.dataType) lazy val converter20 = CatalystTypeConverters.createToScalaConverter(child20.dataType) lazy val converter21 = CatalystTypeConverters.createToScalaConverter(child21.dataType) - (input: Row) => { + (input: catalyst.InternalRow) => { func( converter0(child0.eval(input)), converter1(child1.eval(input)), @@ -955,6 +956,6 @@ case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expressi // scalastyle:on private[this] val converter = CatalystTypeConverters.createToCatalystConverter(dataType) - override def eval(input: Row): Any = converter(f(input)) + override def eval(input: catalyst.InternalRow): Any = converter(f(input)) } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SortOrder.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SortOrder.scala index 99340a14c9..8a34355999 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SortOrder.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SortOrder.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.catalyst.errors.TreeNodeException -import org.apache.spark.sql.catalyst.trees +import org.apache.spark.sql.catalyst.{InternalRow, trees} import org.apache.spark.sql.types.DataType abstract sealed class SortDirection @@ -36,7 +36,7 @@ case class SortOrder(child: Expression, direction: SortDirection) extends Expres override def nullable: Boolean = child.nullable // SortOrder itself is never evaluated. - override def eval(input: Row = null): Any = + override def eval(input: InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") override def toString: String = s"$child ${if (direction == Ascending) "ASC" else "DESC"}" diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala index 98eda61a80..05aab34559 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala @@ -222,7 +222,7 @@ final class SpecificMutableRow(val values: Array[MutableValue]) extends MutableR override def isNullAt(i: Int): Boolean = values(i).isNull - override def copy(): Row = { + override def copy(): InternalRow = { val newValues = new Array[Any](values.length) var i = 0 while (i < values.length) { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverter.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverter.scala index 5350123bf4..d771e454b5 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverter.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverter.scala @@ -48,7 +48,7 @@ class UnsafeRowConverter(fieldTypes: Array[DataType]) { /** * Compute the amount of space, in bytes, required to encode the given row. */ - def getSizeRequirement(row: Row): Int = { + def getSizeRequirement(row: InternalRow): Int = { var fieldNumber = 0 var variableLengthFieldSize: Int = 0 while (fieldNumber < writers.length) { @@ -68,7 +68,7 @@ class UnsafeRowConverter(fieldTypes: Array[DataType]) { * @param baseOffset the base offset of the destination address * @return the number of bytes written. This should be equal to `getSizeRequirement(row)`. */ - def writeRow(row: Row, baseObject: Object, baseOffset: Long): Long = { + def writeRow(row: InternalRow, baseObject: Object, baseOffset: Long): Long = { unsafeRow.pointTo(baseObject, baseOffset, writers.length, null) var fieldNumber = 0 var appendCursor: Int = fixedLengthSize @@ -99,12 +99,12 @@ private abstract class UnsafeColumnWriter { * used for calculating where variable-length data should be written * @return the number of variable-length bytes written */ - def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int + def write(source: InternalRow, target: UnsafeRow, column: Int, appendCursor: Int): Int /** * Return the number of bytes that are needed to write this variable-length value. */ - def getSize(source: Row, column: Int): Int + def getSize(source: InternalRow, column: Int): Int } private object UnsafeColumnWriter { @@ -140,72 +140,108 @@ private object StringUnsafeColumnWriter extends StringUnsafeColumnWriter private abstract class PrimitiveUnsafeColumnWriter extends UnsafeColumnWriter { // Primitives don't write to the variable-length region: - def getSize(sourceRow: Row, column: Int): Int = 0 + def getSize(sourceRow: InternalRow, column: Int): Int = 0 } private class NullUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { - override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + override def write( + source: InternalRow, + target: UnsafeRow, + column: Int, + appendCursor: Int): Int = { target.setNullAt(column) 0 } } private class BooleanUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { - override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + override def write( + source: InternalRow, + target: UnsafeRow, + column: Int, + appendCursor: Int): Int = { target.setBoolean(column, source.getBoolean(column)) 0 } } private class ByteUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { - override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + override def write( + source: InternalRow, + target: UnsafeRow, + column: Int, + appendCursor: Int): Int = { target.setByte(column, source.getByte(column)) 0 } } private class ShortUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { - override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + override def write( + source: InternalRow, + target: UnsafeRow, + column: Int, + appendCursor: Int): Int = { target.setShort(column, source.getShort(column)) 0 } } private class IntUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { - override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + override def write( + source: InternalRow, + target: UnsafeRow, + column: Int, + appendCursor: Int): Int = { target.setInt(column, source.getInt(column)) 0 } } private class LongUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { - override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + override def write( + source: InternalRow, + target: UnsafeRow, + column: Int, + appendCursor: Int): Int = { target.setLong(column, source.getLong(column)) 0 } } private class FloatUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { - override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + override def write( + source: InternalRow, + target: UnsafeRow, + column: Int, + appendCursor: Int): Int = { target.setFloat(column, source.getFloat(column)) 0 } } private class DoubleUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { - override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + override def write( + source: InternalRow, + target: UnsafeRow, + column: Int, + appendCursor: Int): Int = { target.setDouble(column, source.getDouble(column)) 0 } } private class StringUnsafeColumnWriter private() extends UnsafeColumnWriter { - def getSize(source: Row, column: Int): Int = { + def getSize(source: InternalRow, column: Int): Int = { val numBytes = source.get(column).asInstanceOf[UTF8String].getBytes.length 8 + ByteArrayMethods.roundNumberOfBytesToNearestWord(numBytes) } - override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + override def write( + source: InternalRow, + target: UnsafeRow, + column: Int, + appendCursor: Int): Int = { val value = source.get(column).asInstanceOf[UTF8String] val baseObject = target.getBaseObject val baseOffset = target.getBaseOffset diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala index 0266084a6d..f9e8150a68 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala @@ -19,9 +19,10 @@ package org.apache.spark.sql.catalyst.expressions import com.clearspring.analytics.stream.cardinality.HyperLogLog -import org.apache.spark.sql.types._ -import org.apache.spark.sql.catalyst.trees +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.errors.TreeNodeException +import org.apache.spark.sql.catalyst.trees +import org.apache.spark.sql.types._ import org.apache.spark.util.collection.OpenHashSet abstract class AggregateExpression extends Expression { @@ -37,7 +38,7 @@ abstract class AggregateExpression extends Expression { * [[AggregateExpression.eval]] should never be invoked because [[AggregateExpression]]'s are * replaced with a physical aggregate operator at runtime. */ - override def eval(input: Row = null): Any = + override def eval(input: catalyst.InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") } @@ -80,7 +81,7 @@ abstract class AggregateFunction override def nullable: Boolean = base.nullable override def dataType: DataType = base.dataType - def update(input: Row): Unit + def update(input: catalyst.InternalRow): Unit // Do we really need this? override def newInstance(): AggregateFunction = { @@ -108,7 +109,7 @@ case class MinFunction(expr: Expression, base: AggregateExpression) extends Aggr val currentMin: MutableLiteral = MutableLiteral(null, expr.dataType) val cmp = GreaterThan(currentMin, expr) - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { if (currentMin.value == null) { currentMin.value = expr.eval(input) } else if (cmp.eval(input) == true) { @@ -116,7 +117,7 @@ case class MinFunction(expr: Expression, base: AggregateExpression) extends Aggr } } - override def eval(input: Row): Any = currentMin.value + override def eval(input: catalyst.InternalRow): Any = currentMin.value } case class Max(child: Expression) extends PartialAggregate with trees.UnaryNode[Expression] { @@ -139,7 +140,7 @@ case class MaxFunction(expr: Expression, base: AggregateExpression) extends Aggr val currentMax: MutableLiteral = MutableLiteral(null, expr.dataType) val cmp = LessThan(currentMax, expr) - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { if (currentMax.value == null) { currentMax.value = expr.eval(input) } else if (cmp.eval(input) == true) { @@ -147,7 +148,7 @@ case class MaxFunction(expr: Expression, base: AggregateExpression) extends Aggr } } - override def eval(input: Row): Any = currentMax.value + override def eval(input: catalyst.InternalRow): Any = currentMax.value } case class Count(child: Expression) extends PartialAggregate with trees.UnaryNode[Expression] { @@ -205,14 +206,14 @@ case class CollectHashSetFunction( @transient val distinctValue = new InterpretedProjection(expr) - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val evaluatedExpr = distinctValue(input) if (!evaluatedExpr.anyNull) { seen.add(evaluatedExpr) } } - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { seen } } @@ -238,7 +239,7 @@ case class CombineSetsAndCountFunction( val seen = new OpenHashSet[Any]() - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val inputSetEval = inputSet.eval(input).asInstanceOf[OpenHashSet[Any]] val inputIterator = inputSetEval.iterator while (inputIterator.hasNext) { @@ -246,7 +247,7 @@ case class CombineSetsAndCountFunction( } } - override def eval(input: Row): Any = seen.size.toLong + override def eval(input: catalyst.InternalRow): Any = seen.size.toLong } /** The data type of ApproxCountDistinctPartition since its output is a HyperLogLog object. */ @@ -453,7 +454,7 @@ case class CombineSetsAndSumFunction( val seen = new OpenHashSet[Any]() - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val inputSetEval = inputSet.eval(input).asInstanceOf[OpenHashSet[Any]] val inputIterator = inputSetEval.iterator while (inputIterator.hasNext) { @@ -461,8 +462,8 @@ case class CombineSetsAndSumFunction( } } - override def eval(input: Row): Any = { - val casted = seen.asInstanceOf[OpenHashSet[Row]] + override def eval(input: catalyst.InternalRow): Any = { + val casted = seen.asInstanceOf[OpenHashSet[catalyst.InternalRow]] if (casted.size == 0) { null } else { @@ -524,7 +525,7 @@ case class AverageFunction(expr: Expression, base: AggregateExpression) private def addFunction(value: Any) = Add(sum, Cast(Literal.create(value, expr.dataType), calcType)) - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { if (count == 0L) { null } else { @@ -541,7 +542,7 @@ case class AverageFunction(expr: Expression, base: AggregateExpression) } } - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val evaluatedExpr = expr.eval(input) if (evaluatedExpr != null) { count += 1 @@ -555,14 +556,14 @@ case class CountFunction(expr: Expression, base: AggregateExpression) extends Ag var count: Long = _ - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val evaluatedExpr = expr.eval(input) if (evaluatedExpr != null) { count += 1L } } - override def eval(input: Row): Any = count + override def eval(input: catalyst.InternalRow): Any = count } case class ApproxCountDistinctPartitionFunction( @@ -574,14 +575,14 @@ case class ApproxCountDistinctPartitionFunction( private val hyperLogLog = new HyperLogLog(relativeSD) - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val evaluatedExpr = expr.eval(input) if (evaluatedExpr != null) { hyperLogLog.offer(evaluatedExpr) } } - override def eval(input: Row): Any = hyperLogLog + override def eval(input: catalyst.InternalRow): Any = hyperLogLog } case class ApproxCountDistinctMergeFunction( @@ -593,12 +594,12 @@ case class ApproxCountDistinctMergeFunction( private val hyperLogLog = new HyperLogLog(relativeSD) - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val evaluatedExpr = expr.eval(input) hyperLogLog.addAll(evaluatedExpr.asInstanceOf[HyperLogLog]) } - override def eval(input: Row): Any = hyperLogLog.cardinality() + override def eval(input: catalyst.InternalRow): Any = hyperLogLog.cardinality() } case class SumFunction(expr: Expression, base: AggregateExpression) extends AggregateFunction { @@ -619,11 +620,11 @@ case class SumFunction(expr: Expression, base: AggregateExpression) extends Aggr private val addFunction = Coalesce(Seq(Add(Coalesce(Seq(sum, zero)), Cast(expr, calcType)), sum, zero)) - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { sum.update(addFunction, input) } - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { expr.dataType match { case DecimalType.Fixed(_, _) => Cast(sum, dataType).eval(null) @@ -652,7 +653,7 @@ case class CombineSumFunction(expr: Expression, base: AggregateExpression) private val addFunction = Coalesce(Seq(Add(Coalesce(Seq(sum, zero)), Cast(expr, calcType)), sum, zero)) - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val result = expr.eval(input) // partial sum result can be null only when no input rows present if(result != null) { @@ -660,7 +661,7 @@ case class CombineSumFunction(expr: Expression, base: AggregateExpression) } } - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { expr.dataType match { case DecimalType.Fixed(_, _) => Cast(sum, dataType).eval(null) @@ -676,14 +677,14 @@ case class SumDistinctFunction(expr: Expression, base: AggregateExpression) private val seen = new scala.collection.mutable.HashSet[Any]() - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val evaluatedExpr = expr.eval(input) if (evaluatedExpr != null) { seen += evaluatedExpr } } - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { if (seen.size == 0) { null } else { @@ -707,14 +708,14 @@ case class CountDistinctFunction( @transient val distinctValue = new InterpretedProjection(expr) - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { val evaluatedExpr = distinctValue(input) if (!evaluatedExpr.anyNull) { seen.add(evaluatedExpr) } } - override def eval(input: Row): Any = seen.size.toLong + override def eval(input: catalyst.InternalRow): Any = seen.size.toLong } case class FirstFunction(expr: Expression, base: AggregateExpression) extends AggregateFunction { @@ -722,13 +723,13 @@ case class FirstFunction(expr: Expression, base: AggregateExpression) extends Ag var result: Any = null - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { if (result == null) { result = expr.eval(input) } } - override def eval(input: Row): Any = result + override def eval(input: catalyst.InternalRow): Any = result } case class LastFunction(expr: Expression, base: AggregateExpression) extends AggregateFunction { @@ -736,11 +737,11 @@ case class LastFunction(expr: Expression, base: AggregateExpression) extends Agg var result: Any = null - override def update(input: Row): Unit = { + override def update(input: catalyst.InternalRow): Unit = { result = input } - override def eval(input: Row): Any = { - if (result != null) expr.eval(result.asInstanceOf[Row]) else null + override def eval(input: catalyst.InternalRow): Any = { + if (result != null) expr.eval(result.asInstanceOf[catalyst.InternalRow]) else null } } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala index 124274c942..0ba2ff75aa 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala @@ -17,8 +17,9 @@ package org.apache.spark.sql.catalyst.expressions +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.analysis.TypeCheckResult -import org.apache.spark.sql.catalyst.expressions.codegen.{GeneratedExpressionCode, CodeGenContext} +import org.apache.spark.sql.catalyst.expressions.codegen.{CodeGenContext, GeneratedExpressionCode} import org.apache.spark.sql.catalyst.util.TypeUtils import org.apache.spark.sql.types._ @@ -29,7 +30,7 @@ abstract class UnaryArithmetic extends UnaryExpression { override def nullable: Boolean = child.nullable override def dataType: DataType = child.dataType - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evalE = child.eval(input) if (evalE == null) { null @@ -124,7 +125,7 @@ abstract class BinaryArithmetic extends BinaryExpression { protected def checkTypesInternal(t: DataType): TypeCheckResult - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evalE1 = left.eval(input) if(evalE1 == null) { null @@ -219,7 +220,7 @@ case class Divide(left: Expression, right: Expression) extends BinaryArithmetic case it: IntegralType => it.integral.asInstanceOf[Integral[Any]].quot } - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evalE2 = right.eval(input) if (evalE2 == null || evalE2 == 0) { null @@ -279,7 +280,7 @@ case class Remainder(left: Expression, right: Expression) extends BinaryArithmet case i: FractionalType => i.asIntegral.asInstanceOf[Integral[Any]] } - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evalE2 = right.eval(input) if (evalE2 == null || evalE2 == 0) { null @@ -330,7 +331,7 @@ case class MaxOf(left: Expression, right: Expression) extends BinaryArithmetic { private lazy val ordering = TypeUtils.getOrdering(dataType) - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evalE1 = left.eval(input) val evalE2 = right.eval(input) if (evalE1 == null) { @@ -384,7 +385,7 @@ case class MinOf(left: Expression, right: Expression) extends BinaryArithmetic { private lazy val ordering = TypeUtils.getOrdering(dataType) - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evalE1 = left.eval(input) val evalE2 = right.eval(input) if (evalE1 == null) { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala index 536e477330..244a06638f 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala @@ -24,6 +24,7 @@ import com.google.common.cache.{CacheBuilder, CacheLoader} import org.codehaus.janino.ClassBodyEvaluator import org.apache.spark.Logging +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.types._ import org.apache.spark.unsafe.types.UTF8String @@ -34,7 +35,7 @@ class IntegerHashSet extends org.apache.spark.util.collection.OpenHashSet[Int] class LongHashSet extends org.apache.spark.util.collection.OpenHashSet[Long] /** - * Java source for evaluating an [[Expression]] given a [[Row]] of input. + * Java source for evaluating an [[Expression]] given a [[catalyst.InternalRow]] of input. * * @param code The sequence of statements required to evaluate the expression. * @param isNull A term that holds a boolean value representing whether the expression evaluated @@ -183,13 +184,13 @@ class CodeGenContext { } /** - * List of data types that have special accessors and setters in [[Row]]. + * List of data types that have special accessors and setters in [[catalyst.InternalRow]]. */ val nativeTypes = Seq(IntegerType, BooleanType, LongType, DoubleType, FloatType, ShortType, ByteType) /** - * Returns true if the data type has a special accessor and setter in [[Row]]. + * Returns true if the data type has a special accessor and setter in [[catalyst.InternalRow]]. */ def isNativeType(dt: DataType): Boolean = nativeTypes.contains(dt) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateMutableProjection.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateMutableProjection.scala index ed3df547d1..35cb954c54 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateMutableProjection.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateMutableProjection.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.catalyst.expressions.codegen +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.expressions._ // MutableProjection is not accessible in Java @@ -24,7 +25,7 @@ abstract class BaseMutableProjection extends MutableProjection {} /** * Generates byte code that produces a [[MutableRow]] object that can update itself based on a new - * input [[Row]] for a fixed set of [[Expression Expressions]]. + * input [[catalyst.InternalRow]] for a fixed set of [[Expression Expressions]]. */ object GenerateMutableProjection extends CodeGenerator[Seq[Expression], () => MutableProjection] { @@ -47,7 +48,7 @@ object GenerateMutableProjection extends CodeGenerator[Seq[Expression], () => Mu """ }.mkString("\n") val code = s""" - import org.apache.spark.sql.Row; + import org.apache.spark.sql.catalyst.InternalRow; public SpecificProjection generate($exprType[] expr) { return new SpecificProjection(expr); @@ -69,12 +70,12 @@ object GenerateMutableProjection extends CodeGenerator[Seq[Expression], () => Mu } /* Provide immutable access to the last projected row. */ - public Row currentValue() { - return mutableRow; + public InternalRow currentValue() { + return (InternalRow) mutableRow; } public Object apply(Object _i) { - Row i = (Row) _i; + InternalRow i = (InternalRow) _i; $projectionCode return mutableRow; diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateOrdering.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateOrdering.scala index 56ecc5fc06..db5d570aeb 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateOrdering.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateOrdering.scala @@ -19,15 +19,15 @@ package org.apache.spark.sql.catalyst.expressions.codegen import org.apache.spark.Logging import org.apache.spark.annotation.Private -import org.apache.spark.sql.Row +import org.apache.spark.sql.{catalyst, Row} import org.apache.spark.sql.catalyst.expressions._ /** * Inherits some default implementation for Java from `Ordering[Row]` */ @Private -class BaseOrdering extends Ordering[Row] { - def compare(a: Row, b: Row): Int = { +class BaseOrdering extends Ordering[catalyst.InternalRow] { + def compare(a: catalyst.InternalRow, b: catalyst.InternalRow): Int = { throw new UnsupportedOperationException } } @@ -36,7 +36,8 @@ class BaseOrdering extends Ordering[Row] { * Generates bytecode for an [[Ordering]] of [[Row Rows]] for a given set of * [[Expression Expressions]]. */ -object GenerateOrdering extends CodeGenerator[Seq[SortOrder], Ordering[Row]] with Logging { +object GenerateOrdering + extends CodeGenerator[Seq[SortOrder], Ordering[catalyst.InternalRow]] with Logging { import scala.reflect.runtime.universe._ protected def canonicalize(in: Seq[SortOrder]): Seq[SortOrder] = @@ -45,7 +46,7 @@ object GenerateOrdering extends CodeGenerator[Seq[SortOrder], Ordering[Row]] wit protected def bind(in: Seq[SortOrder], inputSchema: Seq[Attribute]): Seq[SortOrder] = in.map(BindReferences.bindReference(_, inputSchema)) - protected def create(ordering: Seq[SortOrder]): Ordering[Row] = { + protected def create(ordering: Seq[SortOrder]): Ordering[catalyst.InternalRow] = { val a = newTermName("a") val b = newTermName("b") val ctx = newCodeGenContext() @@ -75,7 +76,7 @@ object GenerateOrdering extends CodeGenerator[Seq[SortOrder], Ordering[Row]] wit }.mkString("\n") val code = s""" - import org.apache.spark.sql.Row; + import org.apache.spark.sql.catalyst.InternalRow; public SpecificOrdering generate($exprType[] expr) { return new SpecificOrdering(expr); @@ -90,8 +91,8 @@ object GenerateOrdering extends CodeGenerator[Seq[SortOrder], Ordering[Row]] wit } @Override - public int compare(Row a, Row b) { - Row i = null; // Holds current row being evaluated. + public int compare(InternalRow a, InternalRow b) { + InternalRow i = null; // Holds current row being evaluated. $comparisons return 0; } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GeneratePredicate.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GeneratePredicate.scala index 4a547b5ce9..9e191dc2e9 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GeneratePredicate.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GeneratePredicate.scala @@ -17,30 +17,31 @@ package org.apache.spark.sql.catalyst.expressions.codegen +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.expressions._ /** * Interface for generated predicate */ abstract class Predicate { - def eval(r: Row): Boolean + def eval(r: catalyst.InternalRow): Boolean } /** - * Generates bytecode that evaluates a boolean [[Expression]] on a given input [[Row]]. + * Generates bytecode that evaluates a boolean [[Expression]] on a given input [[InternalRow]]. */ -object GeneratePredicate extends CodeGenerator[Expression, (Row) => Boolean] { +object GeneratePredicate extends CodeGenerator[Expression, (catalyst.InternalRow) => Boolean] { protected def canonicalize(in: Expression): Expression = ExpressionCanonicalizer.execute(in) protected def bind(in: Expression, inputSchema: Seq[Attribute]): Expression = BindReferences.bindReference(in, inputSchema) - protected def create(predicate: Expression): ((Row) => Boolean) = { + protected def create(predicate: Expression): ((catalyst.InternalRow) => Boolean) = { val ctx = newCodeGenContext() val eval = predicate.gen(ctx) val code = s""" - import org.apache.spark.sql.Row; + import org.apache.spark.sql.catalyst.InternalRow; public SpecificPredicate generate($exprType[] expr) { return new SpecificPredicate(expr); @@ -53,7 +54,7 @@ object GeneratePredicate extends CodeGenerator[Expression, (Row) => Boolean] { } @Override - public boolean eval(Row i) { + public boolean eval(InternalRow i) { ${eval.code} return !${eval.isNull} && ${eval.primitive}; } @@ -65,6 +66,6 @@ object GeneratePredicate extends CodeGenerator[Expression, (Row) => Boolean] { // fetch the only one method `generate(Expression[])` val m = c.getDeclaredMethods()(0) val p = m.invoke(c.newInstance(), ctx.references.toArray).asInstanceOf[Predicate] - (r: Row) => p.eval(r) + (r: catalyst.InternalRow) => p.eval(r) } } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateProjection.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateProjection.scala index 9b906c3ff5..8b5dc194be 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateProjection.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateProjection.scala @@ -27,9 +27,10 @@ import org.apache.spark.sql.types._ abstract class BaseProject extends Projection {} /** - * Generates bytecode that produces a new [[Row]] object based on a fixed set of input - * [[Expression Expressions]] and a given input [[Row]]. The returned [[Row]] object is custom - * generated based on the output types of the [[Expression]] to avoid boxing of primitive values. + * Generates bytecode that produces a new [[InternalRow]] object based on a fixed set of input + * [[Expression Expressions]] and a given input [[InternalRow]]. The returned [[InternalRow]] + * object is custom generated based on the output types of the [[Expression]] to avoid boxing of + * primitive values. */ object GenerateProjection extends CodeGenerator[Seq[Expression], Projection] { import scala.reflect.runtime.universe._ @@ -146,7 +147,7 @@ object GenerateProjection extends CodeGenerator[Seq[Expression], Projection] { }.mkString("\n") val code = s""" - import org.apache.spark.sql.Row; + import org.apache.spark.sql.catalyst.InternalRow; public SpecificProjection generate($exprType[] expr) { return new SpecificProjection(expr); @@ -161,7 +162,7 @@ object GenerateProjection extends CodeGenerator[Seq[Expression], Projection] { @Override public Object apply(Object r) { - return new SpecificRow(expressions, (Row) r); + return new SpecificRow(expressions, (InternalRow) r); } } @@ -169,7 +170,7 @@ object GenerateProjection extends CodeGenerator[Seq[Expression], Projection] { $columns - public SpecificRow($exprType[] expressions, Row i) { + public SpecificRow($exprType[] expressions, InternalRow i) { $initColumns } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala index 6398b8f9e4..a6913cc03c 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.catalyst.expressions +import org.apache.spark.sql.catalyst import org.apache.spark.sql.types._ @@ -41,7 +42,7 @@ case class CreateArray(children: Seq[Expression]) extends Expression { override def nullable: Boolean = false - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { children.map(_.eval(input)) } @@ -69,7 +70,7 @@ case class CreateStruct(children: Seq[NamedExpression]) extends Expression { override def nullable: Boolean = false - override def eval(input: Row): Any = { - Row(children.map(_.eval(input)): _*) + override def eval(input: catalyst.InternalRow): Any = { + InternalRow(children.map(_.eval(input)): _*) } } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/conditionals.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/conditionals.scala index 72b9f23456..a119c31300 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/conditionals.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/conditionals.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.catalyst.expressions +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.analysis.TypeCheckResult import org.apache.spark.sql.catalyst.expressions.codegen._ import org.apache.spark.sql.types.{BooleanType, DataType} @@ -42,7 +43,7 @@ case class If(predicate: Expression, trueValue: Expression, falseValue: Expressi override def dataType: DataType = trueValue.dataType - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { if (true == predicate.eval(input)) { trueValue.eval(input) } else { @@ -137,7 +138,7 @@ case class CaseWhen(branches: Seq[Expression]) extends CaseWhenLike { } /** Written in imperative fashion for performance considerations. */ - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val len = branchesArr.length var i = 0 // If all branches fail and an elseVal is not provided, the whole statement @@ -229,7 +230,7 @@ case class CaseKeyWhen(key: Expression, branches: Seq[Expression]) extends CaseW } /** Written in imperative fashion for performance considerations. */ - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evaluatedKey = key.eval(input) val len = branchesArr.length var i = 0 diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala index 8ab6d977dd..de8b66bc3b 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala @@ -17,7 +17,8 @@ package org.apache.spark.sql.catalyst.expressions -import org.apache.spark.sql.catalyst.expressions.codegen.{GeneratedExpressionCode, CodeGenContext} +import org.apache.spark.sql.catalyst +import org.apache.spark.sql.catalyst.expressions.codegen.{CodeGenContext, GeneratedExpressionCode} import org.apache.spark.sql.types._ /** Return the unscaled Long value of a Decimal, assuming it fits in a Long */ @@ -28,7 +29,7 @@ case class UnscaledValue(child: Expression) extends UnaryExpression { override def nullable: Boolean = child.nullable override def toString: String = s"UnscaledValue($child)" - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val childResult = child.eval(input) if (childResult == null) { null @@ -50,7 +51,7 @@ case class MakeDecimal(child: Expression, precision: Int, scale: Int) extends Un override def nullable: Boolean = child.nullable override def toString: String = s"MakeDecimal($child,$precision,$scale)" - override def eval(input: Row): Decimal = { + override def eval(input: catalyst.InternalRow): Decimal = { val childResult = child.eval(input) if (childResult == null) { null diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala index b6191eafba..a80c255a29 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala @@ -19,6 +19,7 @@ package org.apache.spark.sql.catalyst.expressions import scala.collection.Map +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.{CatalystTypeConverters, trees} import org.apache.spark.sql.types._ @@ -53,13 +54,13 @@ abstract class Generator extends Expression { def elementTypes: Seq[(DataType, Boolean)] /** Should be implemented by child classes to perform specific Generators. */ - override def eval(input: Row): TraversableOnce[Row] + override def eval(input: catalyst.InternalRow): TraversableOnce[catalyst.InternalRow] /** * Notifies that there are no more rows to process, clean up code, and additional * rows can be made here. */ - def terminate(): TraversableOnce[Row] = Nil + def terminate(): TraversableOnce[catalyst.InternalRow] = Nil } /** @@ -67,22 +68,22 @@ abstract class Generator extends Expression { */ case class UserDefinedGenerator( elementTypes: Seq[(DataType, Boolean)], - function: Row => TraversableOnce[Row], + function: catalyst.InternalRow => TraversableOnce[catalyst.InternalRow], children: Seq[Expression]) extends Generator { @transient private[this] var inputRow: InterpretedProjection = _ - @transient private[this] var convertToScala: (Row) => Row = _ + @transient private[this] var convertToScala: (catalyst.InternalRow) => catalyst.InternalRow = _ private def initializeConverters(): Unit = { inputRow = new InterpretedProjection(children) convertToScala = { val inputSchema = StructType(children.map(e => StructField(e.simpleString, e.dataType, true))) CatalystTypeConverters.createToScalaConverter(inputSchema) - }.asInstanceOf[(Row => Row)] + }.asInstanceOf[(catalyst.InternalRow => catalyst.InternalRow)] } - override def eval(input: Row): TraversableOnce[Row] = { + override def eval(input: catalyst.InternalRow): TraversableOnce[catalyst.InternalRow] = { if (inputRow == null) { initializeConverters() } @@ -108,7 +109,7 @@ case class Explode(child: Expression) case MapType(kt, vt, valueContainsNull) => (kt, false) :: (vt, valueContainsNull) :: Nil } - override def eval(input: Row): TraversableOnce[Row] = { + override def eval(input: catalyst.InternalRow): TraversableOnce[catalyst.InternalRow] = { child.dataType match { case ArrayType(_, _) => val inputArray = child.eval(input).asInstanceOf[Seq[Any]] diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala index a33007bda1..d8fff2b84d 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala @@ -19,6 +19,7 @@ package org.apache.spark.sql.catalyst.expressions import java.sql.{Date, Timestamp} +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.CatalystTypeConverters import org.apache.spark.sql.catalyst.expressions.codegen.{CodeGenContext, GeneratedExpressionCode} import org.apache.spark.sql.catalyst.util.DateUtils @@ -87,7 +88,7 @@ case class Literal protected (value: Any, dataType: DataType) extends LeafExpres case _ => false } - override def eval(input: Row): Any = value + override def eval(input: catalyst.InternalRow): Any = value override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = { // change the isNull and primitive to consts, to inline them @@ -142,9 +143,9 @@ case class Literal protected (value: Any, dataType: DataType) extends LeafExpres case class MutableLiteral(var value: Any, dataType: DataType, nullable: Boolean = true) extends LeafExpression { - def update(expression: Expression, input: Row): Unit = { + def update(expression: Expression, input: catalyst.InternalRow): Unit = { value = expression.eval(input) } - override def eval(input: Row): Any = value + override def eval(input: catalyst.InternalRow): Any = value } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/math.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/math.scala index 97e960b8d6..6f90d607dd 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/math.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/math.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.catalyst.expressions +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.expressions.codegen._ import org.apache.spark.sql.types.{DataType, DoubleType} @@ -34,7 +35,7 @@ abstract class LeafMathExpression(c: Double, name: String) override def nullable: Boolean = false override def toString: String = s"$name()" - override def eval(input: Row): Any = c + override def eval(input: catalyst.InternalRow): Any = c override def genCode(ctx: CodeGenContext, ev: GeneratedExpressionCode): String = { s""" @@ -60,7 +61,7 @@ abstract class UnaryMathExpression(f: Double => Double, name: String) override def nullable: Boolean = true override def toString: String = s"$name($child)" - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evalE = child.eval(input) if (evalE == null) { null @@ -103,7 +104,7 @@ abstract class BinaryMathExpression(f: (Double, Double) => Double, name: String) override def dataType: DataType = DoubleType - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evalE1 = left.eval(input) if (evalE1 == null) { null @@ -215,7 +216,7 @@ case class ToRadians(child: Expression) extends UnaryMathExpression(math.toRadia case class Atan2(left: Expression, right: Expression) extends BinaryMathExpression(math.atan2, "ATAN2") { - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { val evalE1 = left.eval(input) if (evalE1 == null) { null diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala index 2e4b9ba678..20505129e9 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.catalyst.expressions +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.expressions.codegen.{CodeGenContext, GeneratedExpressionCode} @@ -114,7 +115,7 @@ case class Alias(child: Expression, name: String)( // Alias(Generator, xx) need to be transformed into Generate(generator, ...) override lazy val resolved = childrenResolved && !child.isInstanceOf[Generator] - override def eval(input: Row): Any = child.eval(input) + override def eval(input: catalyst.InternalRow): Any = child.eval(input) override def gen(ctx: CodeGenContext): GeneratedExpressionCode = child.gen(ctx) @@ -230,7 +231,7 @@ case class AttributeReference( } // Unresolved attributes are transient at compile time and don't get evaluated during execution. - override def eval(input: Row = null): Any = + override def eval(input: catalyst.InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") override def toString: String = s"$name#${exprId.id}$typeSuffix" @@ -252,7 +253,7 @@ case class PrettyAttribute(name: String) extends Attribute with trees.LeafNode[E override def withName(newName: String): Attribute = throw new UnsupportedOperationException override def qualifiers: Seq[String] = throw new UnsupportedOperationException override def exprId: ExprId = throw new UnsupportedOperationException - override def eval(input: Row): Any = throw new UnsupportedOperationException + override def eval(input: catalyst.InternalRow): Any = throw new UnsupportedOperationException override def nullable: Boolean = throw new UnsupportedOperationException override def dataType: DataType = NullType } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/nullFunctions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/nullFunctions.scala index c2d1a4eada..292d626f01 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/nullFunctions.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/nullFunctions.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.catalyst.expressions +import org.apache.spark.sql.catalyst import org.apache.spark.sql.catalyst.expressions.codegen.{GeneratedExpressionCode, CodeGenContext} import org.apache.spark.sql.catalyst.trees import org.apache.spark.sql.catalyst.analysis.UnresolvedException @@ -43,7 +44,7 @@ case class Coalesce(children: Seq[Expression]) extends Expression { this, s"Coalesce cannot have children of different types. $childTypes") } - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { var i = 0 var result: Any = null val childIterator = children.iterator @@ -77,7 +78,7 @@ case class IsNull(child: Expression) extends Predicate with trees.UnaryNode[Expr override def foldable: Boolean = child.foldable override def nullable: Boolean = false - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { child.eval(input) == null } @@ -96,7 +97,7 @@ case class IsNotNull(child: Expression) extends Predicate with trees.UnaryNode[E override def nullable: Boolean = false override def toString: String = s"IS NOT NULL $child" - override def eval(input: Row): Any = { + override def eval(input: catalyst.InternalRow): Any = { child.eval(input) != null } @@ -118,7 +119,7 @@ case class AtLeastNNonNulls(n: Int, children: Seq[Expression]) extends Predicate private[this] val childrenArray = children.toArray - override def eval(input: Row): Boolean = { + override def eval(input: catalyst.InternalRow): Boolean = { var numNonNulls = 0 var i = 0 while (i < childrenArray.length && numNonNulls < n) { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/package.scala index fbc97b2e75..c2e57b4715 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/package.scala @@ -17,6 +17,8 @@ package org.apache.spark.sql.catalyst +import org.apache.spark.sql.catalyst + /** * A set of classes that can be used to represent trees of relational expressions. A key goal of * the expression library is to hide the details of naming and scoping from developers who want to @@ -49,30 +51,30 @@ package org.apache.spark.sql.catalyst */ package object expressions { - type Row = org.apache.spark.sql.Row + type InternalRow = catalyst.InternalRow - val Row = org.apache.spark.sql.Row + val InternalRow = catalyst.InternalRow /** - * Converts a [[Row]] to another Row given a sequence of expression that define each column of the - * new row. If the schema of the input row is specified, then the given expression will be bound - * to that schema. + * Converts a [[InternalRow]] to another Row given a sequence of expression that define each + * column of the new row. If the schema of the input row is specified, then the given expression + * will be bound to that schema. */ - abstract class Projection extends (Row => Row) + abstract class Projection extends (InternalRow => InternalRow) /** - * Converts a [[Row]] to another Row given a sequence of expression that define each column of the - * new row. If the schema of the input row is specified, then the given expression will be bound - * to that schema. + * Converts a [[InternalRow]] to another Row given a sequence of expression that define each + * column of the new row. If the schema of the input row is specified, then the given expression + * will be bound to that schema. * * In contrast to a normal projection, a MutableProjection reuses the same underlying row object * each time an input row is added. This significantly reduces the cost of calculating the - * projection, but means that it is not safe to hold on to a reference to a [[Row]] after `next()` - * has been called on the [[Iterator]] that produced it. Instead, the user must call `Row.copy()` - * and hold on to the returned [[Row]] before calling `next()`. + * projection, but means that it is not safe to hold on to a reference to a [[InternalRow]] after + * `next()` has been called on the [[Iterator]] that produced it. Instead, the user must call + * `InternalRow.copy()` and hold on to the returned [[InternalRow]] before calling `next()`. */ abstract class MutableProjection extends Projection { - def currentValue: Row + def currentValue: InternalRow /** Uses the given row to store the output of the projection. */ def target(row: MutableRow): MutableProjection diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala index 7574d1cbda..082d72eb43 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala @@ -24,11 +24,11 @@ import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.types._ object InterpretedPredicate { - def create(expression: Expression, inputSchema: Seq[Attribute]): (Row => Boolean) = + def create(expression: Expression, inputSchema: Seq[Attribute]): (InternalRow => Boolean) = create(BindReferences.bindReference(expression, inputSchema)) - def create(expression: Expression): (Row => Boolean) = { - (r: Row) => expression.eval(r).asInstanceOf[Boolean] + def create(expression: Expression): (InternalRow => Boolean) = { + (r: InternalRow) => expression.eval(r).asInstanceOf[Boolean] } } @@ -77,7 +77,7 @@ case class Not(child: Expression) extends UnaryExpression with Predicate with Ex override def expectedChildTypes: Seq[DataType] = Seq(BooleanType) - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { child.eval(input) match { case null => null case b: Boolean => !b @@ -98,7 +98,7 @@ case class In(value: Expression, list: Seq[Expression]) extends Predicate { override def nullable: Boolean = true // TODO: Figure out correct nullability semantics of IN. override def toString: String = s"$value IN ${list.mkString("(", ",", ")")}" - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val evaluatedValue = value.eval(input) list.exists(e => e.eval(input) == evaluatedValue) } @@ -117,7 +117,7 @@ case class InSet(value: Expression, hset: Set[Any]) override def nullable: Boolean = true // TODO: Figure out correct nullability semantics of IN. override def toString: String = s"$value INSET ${hset.mkString("(", ",", ")")}" - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { hset.contains(value.eval(input)) } } @@ -129,7 +129,7 @@ case class And(left: Expression, right: Expression) override def symbol: String = "&&" - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val l = left.eval(input) if (l == false) { false @@ -178,7 +178,7 @@ case class Or(left: Expression, right: Expression) override def symbol: String = "||" - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val l = left.eval(input) if (l == true) { true @@ -235,7 +235,7 @@ abstract class BinaryComparison extends BinaryExpression with Predicate { protected def checkTypesInternal(t: DataType): TypeCheckResult - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val evalE1 = left.eval(input) if (evalE1 == null) { null @@ -288,7 +288,7 @@ case class EqualNullSafe(left: Expression, right: Expression) extends BinaryComp override protected def checkTypesInternal(t: DataType) = TypeCheckResult.TypeCheckSuccess - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val l = left.eval(input) val r = right.eval(input) if (l == null && r == null) { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/random.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/random.scala index 6e4e9cb1be..7e8033307e 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/random.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/random.scala @@ -48,7 +48,7 @@ abstract class RDG(seed: Long) extends LeafExpression with Serializable { /** Generate a random column with i.i.d. uniformly distributed values in [0, 1). */ case class Rand(seed: Long) extends RDG(seed) { - override def eval(input: Row): Double = rng.nextDouble() + override def eval(input: InternalRow): Double = rng.nextDouble() } object Rand { @@ -62,7 +62,7 @@ object Rand { /** Generate a random column with i.i.d. gaussian random distribution. */ case class Randn(seed: Long) extends RDG(seed) { - override def eval(input: Row): Double = rng.nextGaussian() + override def eval(input: InternalRow): Double = rng.nextGaussian() } object Randn { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala index 5d2d82077f..534dac1f92 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala @@ -21,10 +21,10 @@ import org.apache.spark.sql.types.{DataType, StructType, AtomicType} import org.apache.spark.unsafe.types.UTF8String /** - * An extended interface to [[Row]] that allows the values for each column to be updated. Setting - * a value through a primitive function implicitly marks that column as not null. + * An extended interface to [[InternalRow]] that allows the values for each column to be updated. + * Setting a value through a primitive function implicitly marks that column as not null. */ -trait MutableRow extends Row { +trait MutableRow extends InternalRow { def setNullAt(i: Int): Unit def update(ordinal: Int, value: Any) @@ -37,13 +37,12 @@ trait MutableRow extends Row { def setByte(ordinal: Int, value: Byte) def setFloat(ordinal: Int, value: Float) def setString(ordinal: Int, value: String) - // TODO(davies): add setDate() and setDecimal() } /** * A row with no data. Calling any methods will result in an error. Can be used as a placeholder. */ -object EmptyRow extends Row { +object EmptyRow extends InternalRow { override def apply(i: Int): Any = throw new UnsupportedOperationException override def toSeq: Seq[Any] = Seq.empty override def length: Int = 0 @@ -57,7 +56,7 @@ object EmptyRow extends Row { override def getByte(i: Int): Byte = throw new UnsupportedOperationException override def getString(i: Int): String = throw new UnsupportedOperationException override def getAs[T](i: Int): T = throw new UnsupportedOperationException - override def copy(): Row = this + override def copy(): InternalRow = this } /** @@ -65,7 +64,7 @@ object EmptyRow extends Row { * the array is not copied, and thus could technically be mutated after creation, this is not * allowed. */ -class GenericRow(protected[sql] val values: Array[Any]) extends Row { +class GenericRow(protected[sql] val values: Array[Any]) extends InternalRow { /** No-arg constructor for serialization. */ protected def this() = this(null) @@ -154,7 +153,7 @@ class GenericRow(protected[sql] val values: Array[Any]) extends Row { } override def equals(o: Any): Boolean = o match { - case other: Row => + case other: InternalRow => if (values.length != other.length) { return false } @@ -174,7 +173,7 @@ class GenericRow(protected[sql] val values: Array[Any]) extends Row { case _ => false } - override def copy(): Row = this + override def copy(): InternalRow = this } class GenericRowWithSchema(values: Array[Any], override val schema: StructType) @@ -207,15 +206,15 @@ class GenericMutableRow(v: Array[Any]) extends GenericRow(v) with MutableRow { override def update(ordinal: Int, value: Any): Unit = { values(ordinal) = value } - override def copy(): Row = new GenericRow(values.clone()) + override def copy(): InternalRow = new GenericRow(values.clone()) } -class RowOrdering(ordering: Seq[SortOrder]) extends Ordering[Row] { +class RowOrdering(ordering: Seq[SortOrder]) extends Ordering[InternalRow] { def this(ordering: Seq[SortOrder], inputSchema: Seq[Attribute]) = this(ordering.map(BindReferences.bindReference(_, inputSchema))) - def compare(a: Row, b: Row): Int = { + def compare(a: InternalRow, b: InternalRow): Int = { var i = 0 while (i < ordering.size) { val order = ordering(i) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala index 2bcb960e91..30e41677b7 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala @@ -17,7 +17,7 @@ package org.apache.spark.sql.catalyst.expressions -import org.apache.spark.sql.catalyst.expressions.codegen.{GeneratedExpressionCode, CodeGenContext} +import org.apache.spark.sql.catalyst.expressions.codegen.{CodeGenContext, GeneratedExpressionCode} import org.apache.spark.sql.types._ import org.apache.spark.util.collection.OpenHashSet @@ -57,7 +57,7 @@ case class NewSet(elementType: DataType) extends LeafExpression { override def dataType: OpenHashSetUDT = new OpenHashSetUDT(elementType) - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { new OpenHashSet[Any]() } @@ -87,7 +87,7 @@ case class AddItemToSet(item: Expression, set: Expression) extends Expression { override def dataType: OpenHashSetUDT = set.dataType.asInstanceOf[OpenHashSetUDT] - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val itemEval = item.eval(input) val setEval = set.eval(input).asInstanceOf[OpenHashSet[Any]] @@ -137,7 +137,7 @@ case class CombineSets(left: Expression, right: Expression) extends BinaryExpres override def symbol: String = "++=" - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val leftEval = left.eval(input).asInstanceOf[OpenHashSet[Any]] if(leftEval != null) { val rightEval = right.eval(input).asInstanceOf[OpenHashSet[Any]] @@ -183,7 +183,7 @@ case class CountSet(child: Expression) extends UnaryExpression { override def dataType: DataType = LongType - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val childEval = child.eval(input).asInstanceOf[OpenHashSet[Any]] if (childEval != null) { childEval.size.toLong diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala index 4f4c19526e..8ca8d22bc4 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala @@ -49,7 +49,7 @@ trait StringRegexExpression extends ExpectsInputTypes { protected def pattern(str: String) = if (cache == null) compile(str) else cache - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val l = left.eval(input) if (l == null) { null @@ -121,7 +121,7 @@ trait CaseConversionExpression extends ExpectsInputTypes { override def dataType: DataType = StringType override def expectedChildTypes: Seq[DataType] = Seq(StringType) - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val evaluated = child.eval(input) if (evaluated == null) { null @@ -169,7 +169,7 @@ trait StringComparison extends ExpectsInputTypes { override def expectedChildTypes: Seq[DataType] = Seq(StringType, StringType) - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val leftEval = left.eval(input) if(leftEval == null) { null @@ -262,7 +262,7 @@ case class Substring(str: Expression, pos: Expression, len: Expression) (start, end) } - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val string = str.eval(input) val po = pos.eval(input) val ln = len.eval(input) @@ -303,7 +303,7 @@ case class StringLength(child: Expression) extends UnaryExpression with ExpectsI override def dataType: DataType = IntegerType override def expectedChildTypes: Seq[DataType] = Seq(StringType) - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { val string = child.eval(input) if (string == null) null else string.asInstanceOf[UTF8String].length } @@ -314,5 +314,3 @@ case class StringLength(child: Expression) extends UnaryExpression with ExpectsI defineCodeGen(ctx, ev, c => s"($c).length()") } } - - diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala index 82c4d462cc..056f170539 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala @@ -74,7 +74,7 @@ case class WindowSpecDefinition( override def toString: String = simpleString - override def eval(input: Row): Any = throw new UnsupportedOperationException + override def eval(input: InternalRow): Any = throw new UnsupportedOperationException override def nullable: Boolean = true override def foldable: Boolean = false override def dataType: DataType = throw new UnsupportedOperationException @@ -259,7 +259,7 @@ trait WindowFunction extends Expression { def reset(): Unit - def prepareInputParameters(input: Row): AnyRef + def prepareInputParameters(input: InternalRow): AnyRef def update(input: AnyRef): Unit @@ -286,7 +286,7 @@ case class UnresolvedWindowFunction( throw new UnresolvedException(this, "init") override def reset(): Unit = throw new UnresolvedException(this, "reset") - override def prepareInputParameters(input: Row): AnyRef = + override def prepareInputParameters(input: InternalRow): AnyRef = throw new UnresolvedException(this, "prepareInputParameters") override def update(input: AnyRef): Unit = throw new UnresolvedException(this, "update") @@ -297,7 +297,7 @@ case class UnresolvedWindowFunction( override def get(index: Int): Any = throw new UnresolvedException(this, "get") // Unresolved functions are transient at compile time and don't get evaluated during execution. - override def eval(input: Row = null): Any = + override def eval(input: InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") override def toString: String = s"'$name(${children.mkString(",")})" @@ -316,7 +316,7 @@ case class UnresolvedWindowExpression( override lazy val resolved = false // Unresolved functions are transient at compile time and don't get evaluated during execution. - override def eval(input: Row = null): Any = + override def eval(input: InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") } @@ -327,7 +327,7 @@ case class WindowExpression( override def children: Seq[Expression] = windowFunction :: windowSpec :: Nil - override def eval(input: Row): Any = + override def eval(input: InternalRow): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") override def dataType: DataType = windowFunction.dataType diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LocalRelation.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LocalRelation.scala index e3e070f0ff..2c946cd12f 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LocalRelation.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LocalRelation.scala @@ -17,10 +17,9 @@ package org.apache.spark.sql.catalyst.plans.logical -import org.apache.spark.sql.Row -import org.apache.spark.sql.catalyst.{CatalystTypeConverters, analysis} import org.apache.spark.sql.catalyst.expressions.Attribute -import org.apache.spark.sql.types.{StructType, StructField} +import org.apache.spark.sql.catalyst.{InternalRow, CatalystTypeConverters, analysis} +import org.apache.spark.sql.types.{StructField, StructType} object LocalRelation { def apply(output: Attribute*): LocalRelation = new LocalRelation(output) @@ -32,11 +31,11 @@ object LocalRelation { def fromProduct(output: Seq[Attribute], data: Seq[Product]): LocalRelation = { val schema = StructType.fromAttributes(output) val converter = CatalystTypeConverters.createToCatalystConverter(schema) - LocalRelation(output, data.map(converter(_).asInstanceOf[Row])) + LocalRelation(output, data.map(converter(_).asInstanceOf[InternalRow])) } } -case class LocalRelation(output: Seq[Attribute], data: Seq[Row] = Nil) +case class LocalRelation(output: Seq[Attribute], data: Seq[InternalRow] = Nil) extends LeafNode with analysis.MultiInstanceRelation { /** diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala index 80ba57a082..42dead7c28 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala @@ -17,8 +17,9 @@ package org.apache.spark.sql.catalyst.plans.physical +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.errors.TreeNodeException -import org.apache.spark.sql.catalyst.expressions.{Expression, Row, SortOrder} +import org.apache.spark.sql.catalyst.expressions.{Expression, SortOrder} import org.apache.spark.sql.types.{DataType, IntegerType} /** @@ -169,7 +170,7 @@ case class HashPartitioning(expressions: Seq[Expression], numPartitions: Int) override def keyExpressions: Seq[Expression] = expressions - override def eval(input: Row = null): Any = + override def eval(input: InternalRow = null): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") } @@ -213,6 +214,6 @@ case class RangePartitioning(ordering: Seq[SortOrder], numPartitions: Int) override def keyExpressions: Seq[Expression] = ordering.map(_.child) - override def eval(input: Row): Any = + override def eval(input: InternalRow): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") } diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala index 9a24b23024..b4d5e013f3 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala @@ -21,7 +21,7 @@ import java.math.BigInteger import java.sql.{Date, Timestamp} import org.apache.spark.SparkFunSuite -import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.types._ case class PrimitiveData( @@ -257,7 +257,7 @@ class ScalaReflectionSuite extends SparkFunSuite { test("convert PrimitiveData to catalyst") { val data = PrimitiveData(1, 1, 1, 1, 1, 1, true) - val convertedData = Row(1, 1.toLong, 1.toDouble, 1.toFloat, 1.toShort, 1.toByte, true) + val convertedData = InternalRow(1, 1.toLong, 1.toDouble, 1.toFloat, 1.toShort, 1.toByte, true) val dataType = schemaFor[PrimitiveData].dataType assert(CatalystTypeConverters.convertToCatalyst(data, dataType) === convertedData) } @@ -267,8 +267,8 @@ class ScalaReflectionSuite extends SparkFunSuite { val data = OptionalData(Some(2), Some(2), Some(2), Some(2), Some(2), Some(2), Some(true), Some(primitiveData)) val dataType = schemaFor[OptionalData].dataType - val convertedData = Row(2, 2.toLong, 2.toDouble, 2.toFloat, 2.toShort, 2.toByte, true, - Row(1, 1, 1, 1, 1, 1, true)) + val convertedData = InternalRow(2, 2.toLong, 2.toDouble, 2.toFloat, 2.toShort, 2.toByte, true, + InternalRow(1, 1, 1, 1, 1, 1, true)) assert(CatalystTypeConverters.convertToCatalyst(data, dataType) === convertedData) } diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CastSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CastSuite.scala index 969c6cc15f..e407f6f166 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CastSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CastSuite.scala @@ -437,14 +437,14 @@ class CastSuite extends SparkFunSuite with ExpressionEvalHelper { test("cast from struct") { val struct = Literal.create( - Row("123", "abc", "", null), + InternalRow("123", "abc", "", null), StructType(Seq( StructField("a", StringType, nullable = true), StructField("b", StringType, nullable = true), StructField("c", StringType, nullable = true), StructField("d", StringType, nullable = true)))) val struct_notNull = Literal.create( - Row("123", "abc", ""), + InternalRow("123", "abc", ""), StructType(Seq( StructField("a", StringType, nullable = false), StructField("b", StringType, nullable = false), @@ -457,7 +457,7 @@ class CastSuite extends SparkFunSuite with ExpressionEvalHelper { StructField("c", IntegerType, nullable = true), StructField("d", IntegerType, nullable = true)))) assert(ret.resolved === true) - checkEvaluation(ret, Row(123, null, null, null)) + checkEvaluation(ret, InternalRow(123, null, null, null)) } { val ret = cast(struct, StructType(Seq( @@ -474,7 +474,7 @@ class CastSuite extends SparkFunSuite with ExpressionEvalHelper { StructField("c", BooleanType, nullable = true), StructField("d", BooleanType, nullable = true)))) assert(ret.resolved === true) - checkEvaluation(ret, Row(true, true, false, null)) + checkEvaluation(ret, InternalRow(true, true, false, null)) } { val ret = cast(struct, StructType(Seq( @@ -491,7 +491,7 @@ class CastSuite extends SparkFunSuite with ExpressionEvalHelper { StructField("b", IntegerType, nullable = true), StructField("c", IntegerType, nullable = true)))) assert(ret.resolved === true) - checkEvaluation(ret, Row(123, null, null)) + checkEvaluation(ret, InternalRow(123, null, null)) } { val ret = cast(struct_notNull, StructType(Seq( @@ -506,7 +506,7 @@ class CastSuite extends SparkFunSuite with ExpressionEvalHelper { StructField("b", BooleanType, nullable = true), StructField("c", BooleanType, nullable = true)))) assert(ret.resolved === true) - checkEvaluation(ret, Row(true, true, false)) + checkEvaluation(ret, InternalRow(true, true, false)) } { val ret = cast(struct_notNull, StructType(Seq( @@ -514,7 +514,7 @@ class CastSuite extends SparkFunSuite with ExpressionEvalHelper { StructField("b", BooleanType, nullable = true), StructField("c", BooleanType, nullable = false)))) assert(ret.resolved === true) - checkEvaluation(ret, Row(true, true, false)) + checkEvaluation(ret, InternalRow(true, true, false)) } { @@ -532,10 +532,10 @@ class CastSuite extends SparkFunSuite with ExpressionEvalHelper { test("complex casting") { val complex = Literal.create( - Row( + InternalRow( Seq("123", "abc", ""), Map("a" -> "123", "b" -> "abc", "c" -> ""), - Row(0)), + InternalRow(0)), StructType(Seq( StructField("a", ArrayType(StringType, containsNull = false), nullable = true), @@ -555,10 +555,10 @@ class CastSuite extends SparkFunSuite with ExpressionEvalHelper { StructField("l", LongType, nullable = true))))))) assert(ret.resolved === true) - checkEvaluation(ret, Row( + checkEvaluation(ret, InternalRow( Seq(123, null, null), Map("a" -> true, "b" -> true, "c" -> false), - Row(0L))) + InternalRow(0L))) } } diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ComplexTypeSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ComplexTypeSuite.scala index bcc594cb7c..2b0f4618b2 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ComplexTypeSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ComplexTypeSuite.scala @@ -27,10 +27,10 @@ import org.apache.spark.unsafe.types.UTF8String class ComplexTypeSuite extends SparkFunSuite with ExpressionEvalHelper { test("CreateStruct") { - val row = Row(1, 2, 3) + val row = InternalRow(1, 2, 3) val c1 = 'a.int.at(0).as("a") val c3 = 'c.int.at(2).as("c") - checkEvaluation(CreateStruct(Seq(c1, c3)), Row(1, 3), row) + checkEvaluation(CreateStruct(Seq(c1, c3)), InternalRow(1, 3), row) } test("complex type") { diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala index 4a241d3603..12d2da8b33 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala @@ -32,26 +32,26 @@ import org.apache.spark.sql.catalyst.plans.logical.{OneRowRelation, Project} trait ExpressionEvalHelper { self: SparkFunSuite => - protected def create_row(values: Any*): Row = { + protected def create_row(values: Any*): InternalRow = { new GenericRow(values.map(CatalystTypeConverters.convertToCatalyst).toArray) } protected def checkEvaluation( - expression: Expression, expected: Any, inputRow: Row = EmptyRow): Unit = { + expression: Expression, expected: Any, inputRow: InternalRow = EmptyRow): Unit = { checkEvaluationWithoutCodegen(expression, expected, inputRow) checkEvaluationWithGeneratedMutableProjection(expression, expected, inputRow) checkEvaluationWithGeneratedProjection(expression, expected, inputRow) checkEvaluationWithOptimization(expression, expected, inputRow) } - protected def evaluate(expression: Expression, inputRow: Row = EmptyRow): Any = { + protected def evaluate(expression: Expression, inputRow: InternalRow = EmptyRow): Any = { expression.eval(inputRow) } protected def checkEvaluationWithoutCodegen( expression: Expression, expected: Any, - inputRow: Row = EmptyRow): Unit = { + inputRow: InternalRow = EmptyRow): Unit = { val actual = try evaluate(expression, inputRow) catch { case e: Exception => fail(s"Exception evaluating $expression", e) } @@ -66,7 +66,7 @@ trait ExpressionEvalHelper { protected def checkEvaluationWithGeneratedMutableProjection( expression: Expression, expected: Any, - inputRow: Row = EmptyRow): Unit = { + inputRow: InternalRow = EmptyRow): Unit = { val plan = try { GenerateMutableProjection.generate(Alias(expression, s"Optimized($expression)")() :: Nil)() @@ -92,7 +92,7 @@ trait ExpressionEvalHelper { protected def checkEvaluationWithGeneratedProjection( expression: Expression, expected: Any, - inputRow: Row = EmptyRow): Unit = { + inputRow: InternalRow = EmptyRow): Unit = { val ctx = GenerateProjection.newCodeGenContext() lazy val evaluated = expression.gen(ctx) @@ -128,7 +128,7 @@ trait ExpressionEvalHelper { protected def checkEvaluationWithOptimization( expression: Expression, expected: Any, - inputRow: Row = EmptyRow): Unit = { + inputRow: InternalRow = EmptyRow): Unit = { val plan = Project(Alias(expression, s"Optimized($expression)")() :: Nil, OneRowRelation) val optimizedPlan = DefaultOptimizer.execute(plan) checkEvaluationWithoutCodegen(optimizedPlan.expressions.head, expected, inputRow) @@ -137,7 +137,7 @@ trait ExpressionEvalHelper { protected def checkDoubleEvaluation( expression: Expression, expected: Spread[Double], - inputRow: Row = EmptyRow): Unit = { + inputRow: InternalRow = EmptyRow): Unit = { val actual = try evaluate(expression, inputRow) catch { case e: Exception => fail(s"Exception evaluating $expression", e) } diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMapSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMapSuite.scala index 72bbc4efeb..7aae2bbd8a 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMapSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMapSuite.scala @@ -37,7 +37,7 @@ class UnsafeFixedWidthAggregationMapSuite private val groupKeySchema = StructType(StructField("product", StringType) :: Nil) private val aggBufferSchema = StructType(StructField("salePrice", IntegerType) :: Nil) - private def emptyAggregationBuffer: Row = new GenericRow(Array[Any](0)) + private def emptyAggregationBuffer: InternalRow = new GenericRow(Array[Any](0)) private var memoryManager: TaskMemoryManager = null diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala index 61722f1ffa..577c7a0de0 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala @@ -86,7 +86,7 @@ class UnsafeRowConverterSuite extends SparkFunSuite with Matchers { DoubleType) val converter = new UnsafeRowConverter(fieldTypes) - val rowWithAllNullColumns: Row = { + val rowWithAllNullColumns: InternalRow = { val r = new SpecificMutableRow(fieldTypes) for (i <- 0 to fieldTypes.length - 1) { r.setNullAt(i) @@ -117,7 +117,7 @@ class UnsafeRowConverterSuite extends SparkFunSuite with Matchers { // If we have an UnsafeRow with columns that are initially non-null and we null out those // columns, then the serialized row representation should be identical to what we would get by // creating an entirely null row via the converter - val rowWithNoNullColumns: Row = { + val rowWithNoNullColumns: InternalRow = { val r = new SpecificMutableRow(fieldTypes) r.setNullAt(0) r.setBoolean(1, false) diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConvertToLocalRelationSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConvertToLocalRelationSuite.scala index 6841bd9890..54e8c6462e 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConvertToLocalRelationSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConvertToLocalRelationSuite.scala @@ -17,10 +17,10 @@ package org.apache.spark.sql.catalyst.optimizer -import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute -import org.apache.spark.sql.catalyst.dsl.plans._ import org.apache.spark.sql.catalyst.dsl.expressions._ +import org.apache.spark.sql.catalyst.dsl.plans._ +import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.PlanTest import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan} import org.apache.spark.sql.catalyst.rules.RuleExecutor @@ -37,13 +37,11 @@ class ConvertToLocalRelationSuite extends PlanTest { test("Project on LocalRelation should be turned into a single LocalRelation") { val testRelation = LocalRelation( LocalRelation('a.int, 'b.int).output, - Row(1, 2) :: - Row(4, 5) :: Nil) + InternalRow(1, 2) :: InternalRow(4, 5) :: Nil) val correctAnswer = LocalRelation( LocalRelation('a1.int, 'b1.int).output, - Row(1, 3) :: - Row(4, 6) :: Nil) + InternalRow(1, 3) :: InternalRow(4, 6) :: Nil) val projectOnLocal = testRelation.select( UnresolvedAttribute("a").as("a1"), diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala index 8ec79c3d4d..bda217935c 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala @@ -28,7 +28,7 @@ case class Dummy(optKey: Option[Expression]) extends Expression { override def nullable: Boolean = true override def dataType: NullType = NullType override lazy val resolved = true - override def eval(input: Row): Any = null.asInstanceOf[Any] + override def eval(input: InternalRow): Any = null.asInstanceOf[Any] } case class ComplexPlan(exprs: Seq[Seq[Expression]]) diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/DateUtilsSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/DateUtilsSuite.scala index a4245545ff..4d8fe4ac5e 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/DateUtilsSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/DateUtilsSuite.scala @@ -21,7 +21,6 @@ import java.sql.Timestamp import org.apache.spark.SparkFunSuite - class DateUtilsSuite extends SparkFunSuite { test("timestamp") { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala index f041fd397b..f1acdfeea5 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala @@ -20,7 +20,6 @@ package org.apache.spark.sql import java.io.CharArrayWriter import java.util.Properties -import scala.collection.JavaConversions._ import scala.language.implicitConversions import scala.reflect.ClassTag import scala.reflect.runtime.universe.TypeTag @@ -33,7 +32,7 @@ import org.apache.spark.annotation.{DeveloperApi, Experimental} import org.apache.spark.api.java.JavaRDD import org.apache.spark.api.python.SerDeUtil import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.analysis.{MultiAlias, ResolvedStar, UnresolvedAttribute, UnresolvedRelation} +import org.apache.spark.sql.catalyst.analysis.{MultiAlias, ResolvedStar, UnresolvedAttribute} import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical.{Filter, _} import org.apache.spark.sql.catalyst.plans.{Inner, JoinType} @@ -1032,7 +1031,8 @@ class DataFrame private[sql]( val names = schema.toAttributes.map(_.name) val rowFunction = - f.andThen(_.map(CatalystTypeConverters.convertToCatalyst(_, schema).asInstanceOf[Row])) + f.andThen(_.map(CatalystTypeConverters.convertToCatalyst(_, schema) + .asInstanceOf[InternalRow])) val generator = UserDefinedGenerator(elementTypes, rowFunction, input.map(_.expr)) Generate(generator, join = true, outer = false, @@ -1058,8 +1058,9 @@ class DataFrame private[sql]( val elementTypes = attributes.map { attr => (attr.dataType, attr.nullable) } val names = attributes.map(_.name) - def rowFunction(row: Row): TraversableOnce[Row] = { - f(row(0).asInstanceOf[A]).map(o => Row(CatalystTypeConverters.convertToCatalyst(o, dataType))) + def rowFunction(row: Row): TraversableOnce[InternalRow] = { + f(row(0).asInstanceOf[A]).map(o => + catalyst.InternalRow(CatalystTypeConverters.convertToCatalyst(o, dataType))) } val generator = UserDefinedGenerator(elementTypes, rowFunction, apply(inputColumn).expr :: Nil) @@ -1221,7 +1222,7 @@ class DataFrame private[sql]( val outputCols = (if (cols.isEmpty) numericColumns.map(_.prettyString) else cols).toList - val ret: Seq[Row] = if (outputCols.nonEmpty) { + val ret: Seq[InternalRow] = if (outputCols.nonEmpty) { val aggExprs = statistics.flatMap { case (_, colToAgg) => outputCols.map(c => Column(Cast(colToAgg(Column(c).expr), StringType)).as(c)) } @@ -1230,11 +1231,12 @@ class DataFrame private[sql]( // Pivot the data so each summary is one row row.grouped(outputCols.size).toSeq.zip(statistics).map { - case (aggregation, (statistic, _)) => Row(statistic :: aggregation.toList: _*) + case (aggregation, (statistic, _)) => + catalyst.InternalRow(statistic :: aggregation.toList: _*) } } else { // If there are no output columns, just output a single column that contains the stats. - statistics.map { case (name, _) => Row(name) } + statistics.map { case (name, _) => catalyst.InternalRow(name) } } // All columns are string type diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala index b44d4c86ac..1828ed1aab 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala @@ -245,7 +245,7 @@ class DataFrameReader private[sql](sqlContext: SQLContext) { JsonRDD.nullTypeToStringType( JsonRDD.inferSchema(jsonRDD, 1.0, columnNameOfCorruptJsonRecord))) val rowRDD = JsonRDD.jsonStringToRow(jsonRDD, appliedSchema, columnNameOfCorruptJsonRecord) - sqlContext.createDataFrame(rowRDD, appliedSchema, needsConversion = false) + sqlContext.internalCreateDataFrame(rowRDD, appliedSchema) } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index 5f758adf3d..22d0e50e4e 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -31,7 +31,7 @@ import org.apache.spark.SparkContext import org.apache.spark.annotation.{DeveloperApi, Experimental} import org.apache.spark.api.java.{JavaRDD, JavaSparkContext} import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst._ +import org.apache.spark.sql.catalyst.{InternalRow, _} import org.apache.spark.sql.catalyst.analysis._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.errors.DialectException @@ -486,15 +486,27 @@ class SQLContext(@transient val sparkContext: SparkContext) // schema differs from the existing schema on any field data type. val catalystRows = if (needsConversion) { val converter = CatalystTypeConverters.createToCatalystConverter(schema) - rowRDD.map(converter(_).asInstanceOf[Row]) + rowRDD.map(converter(_).asInstanceOf[InternalRow]) } else { - rowRDD + rowRDD.map{r: Row => InternalRow.fromSeq(r.toSeq)} } val logicalPlan = LogicalRDD(schema.toAttributes, catalystRows)(self) DataFrame(this, logicalPlan) } /** + * Creates a DataFrame from an RDD[Row]. User can specify whether the input rows should be + * converted to Catalyst rows. + */ + private[sql] + def internalCreateDataFrame(catalystRows: RDD[InternalRow], schema: StructType) = { + // TODO: use MutableProjection when rowRDD is another DataFrame and the applied + // schema differs from the existing schema on any field data type. + val logicalPlan = LogicalRDD(schema.toAttributes, catalystRows)(self) + DataFrame(this, logicalPlan) + } + + /** * :: DeveloperApi :: * Creates a [[DataFrame]] from an [[JavaRDD]] containing [[Row]]s using the given schema. * It is important to make sure that the structure of every [[Row]] of the provided RDD matches @@ -531,7 +543,7 @@ class SQLContext(@transient val sparkContext: SparkContext) extractors.zip(attributeSeq).map { case (e, attr) => CatalystTypeConverters.convertToCatalyst(e.invoke(row), attr.dataType) }.toArray[Any] - ) : Row + ) : InternalRow } } DataFrame(this, LogicalRDD(attributeSeq, rowRdd)(this)) @@ -886,7 +898,7 @@ class SQLContext(@transient val sparkContext: SparkContext) protected[sql] val planner = new SparkPlanner @transient - protected[sql] lazy val emptyResult = sparkContext.parallelize(Seq.empty[Row], 1) + protected[sql] lazy val emptyResult = sparkContext.parallelize(Seq.empty[InternalRow], 1) /** * Prepares a planned SparkPlan for execution by inserting shuffle operations as needed. @@ -953,7 +965,7 @@ class SQLContext(@transient val sparkContext: SparkContext) lazy val executedPlan: SparkPlan = prepareForExecution.execute(sparkPlan) /** Internal version of the RDD. Avoids copies and has no schema */ - lazy val toRdd: RDD[Row] = executedPlan.execute() + lazy val toRdd: RDD[InternalRow] = executedPlan.execute() protected def stringOrError[A](f: => A): String = try f.toString catch { case e: Throwable => e.toString } @@ -1035,7 +1047,7 @@ class SQLContext(@transient val sparkContext: SparkContext) } val rowRdd = convertedRdd.mapPartitions { iter => - iter.map { m => new GenericRow(m): Row} + iter.map { m => new GenericRow(m): InternalRow} } DataFrame(this, LogicalRDD(schema.toAttributes, rowRdd)(self)) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala index aa10af400c..cc7506dec1 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala @@ -18,8 +18,7 @@ package org.apache.spark.sql.columnar import java.nio.{ByteBuffer, ByteOrder} - -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.columnar.ColumnBuilder._ import org.apache.spark.sql.columnar.compression.{AllCompressionSchemes, CompressibleColumnBuilder} import org.apache.spark.sql.types._ @@ -33,7 +32,7 @@ private[sql] trait ColumnBuilder { /** * Appends `row(ordinal)` to the column builder. */ - def appendFrom(row: Row, ordinal: Int) + def appendFrom(row: InternalRow, ordinal: Int) /** * Column statistics information @@ -68,7 +67,7 @@ private[sql] class BasicColumnBuilder[T <: DataType, JvmType]( buffer.order(ByteOrder.nativeOrder()).putInt(columnType.typeId) } - override def appendFrom(row: Row, ordinal: Int): Unit = { + override def appendFrom(row: InternalRow, ordinal: Int): Unit = { buffer = ensureFreeSpace(buffer, columnType.actualSize(row, ordinal)) columnType.append(row, ordinal, buffer) } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala index 11c79c865f..1bce214d1d 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala @@ -17,7 +17,7 @@ package org.apache.spark.sql.columnar -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeMap, AttributeReference} import org.apache.spark.sql.types._ import org.apache.spark.unsafe.types.UTF8String @@ -53,7 +53,7 @@ private[sql] sealed trait ColumnStats extends Serializable { /** * Gathers statistics information from `row(ordinal)`. */ - def gatherStats(row: Row, ordinal: Int): Unit = { + def gatherStats(row: InternalRow, ordinal: Int): Unit = { if (row.isNullAt(ordinal)) { nullCount += 1 // 4 bytes for null position @@ -66,23 +66,23 @@ private[sql] sealed trait ColumnStats extends Serializable { * Column statistics represented as a single row, currently including closed lower bound, closed * upper bound and null count. */ - def collectedStatistics: Row + def collectedStatistics: InternalRow } /** * A no-op ColumnStats only used for testing purposes. */ private[sql] class NoopColumnStats extends ColumnStats { - override def gatherStats(row: Row, ordinal: Int): Unit = super.gatherStats(row, ordinal) + override def gatherStats(row: InternalRow, ordinal: Int): Unit = super.gatherStats(row, ordinal) - override def collectedStatistics: Row = Row(null, null, nullCount, count, 0L) + override def collectedStatistics: InternalRow = InternalRow(null, null, nullCount, count, 0L) } private[sql] class BooleanColumnStats extends ColumnStats { protected var upper = false protected var lower = true - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { val value = row.getBoolean(ordinal) @@ -92,14 +92,15 @@ private[sql] class BooleanColumnStats extends ColumnStats { } } - override def collectedStatistics: Row = Row(lower, upper, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(lower, upper, nullCount, count, sizeInBytes) } private[sql] class ByteColumnStats extends ColumnStats { protected var upper = Byte.MinValue protected var lower = Byte.MaxValue - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { val value = row.getByte(ordinal) @@ -109,14 +110,15 @@ private[sql] class ByteColumnStats extends ColumnStats { } } - override def collectedStatistics: Row = Row(lower, upper, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(lower, upper, nullCount, count, sizeInBytes) } private[sql] class ShortColumnStats extends ColumnStats { protected var upper = Short.MinValue protected var lower = Short.MaxValue - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { val value = row.getShort(ordinal) @@ -126,14 +128,15 @@ private[sql] class ShortColumnStats extends ColumnStats { } } - override def collectedStatistics: Row = Row(lower, upper, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(lower, upper, nullCount, count, sizeInBytes) } private[sql] class LongColumnStats extends ColumnStats { protected var upper = Long.MinValue protected var lower = Long.MaxValue - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { val value = row.getLong(ordinal) @@ -143,14 +146,15 @@ private[sql] class LongColumnStats extends ColumnStats { } } - override def collectedStatistics: Row = Row(lower, upper, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(lower, upper, nullCount, count, sizeInBytes) } private[sql] class DoubleColumnStats extends ColumnStats { protected var upper = Double.MinValue protected var lower = Double.MaxValue - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { val value = row.getDouble(ordinal) @@ -160,14 +164,15 @@ private[sql] class DoubleColumnStats extends ColumnStats { } } - override def collectedStatistics: Row = Row(lower, upper, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(lower, upper, nullCount, count, sizeInBytes) } private[sql] class FloatColumnStats extends ColumnStats { protected var upper = Float.MinValue protected var lower = Float.MaxValue - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { val value = row.getFloat(ordinal) @@ -177,14 +182,15 @@ private[sql] class FloatColumnStats extends ColumnStats { } } - override def collectedStatistics: Row = Row(lower, upper, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(lower, upper, nullCount, count, sizeInBytes) } private[sql] class FixedDecimalColumnStats extends ColumnStats { protected var upper: Decimal = null protected var lower: Decimal = null - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { val value = row(ordinal).asInstanceOf[Decimal] @@ -194,14 +200,15 @@ private[sql] class FixedDecimalColumnStats extends ColumnStats { } } - override def collectedStatistics: Row = Row(lower, upper, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(lower, upper, nullCount, count, sizeInBytes) } private[sql] class IntColumnStats extends ColumnStats { protected var upper = Int.MinValue protected var lower = Int.MaxValue - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { val value = row.getInt(ordinal) @@ -211,14 +218,15 @@ private[sql] class IntColumnStats extends ColumnStats { } } - override def collectedStatistics: Row = Row(lower, upper, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(lower, upper, nullCount, count, sizeInBytes) } private[sql] class StringColumnStats extends ColumnStats { protected var upper: UTF8String = null protected var lower: UTF8String = null - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { val value = row(ordinal).asInstanceOf[UTF8String] @@ -228,7 +236,8 @@ private[sql] class StringColumnStats extends ColumnStats { } } - override def collectedStatistics: Row = Row(lower, upper, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(lower, upper, nullCount, count, sizeInBytes) } private[sql] class DateColumnStats extends IntColumnStats @@ -236,23 +245,25 @@ private[sql] class DateColumnStats extends IntColumnStats private[sql] class TimestampColumnStats extends LongColumnStats private[sql] class BinaryColumnStats extends ColumnStats { - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { sizeInBytes += BINARY.actualSize(row, ordinal) } } - override def collectedStatistics: Row = Row(null, null, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(null, null, nullCount, count, sizeInBytes) } private[sql] class GenericColumnStats extends ColumnStats { - override def gatherStats(row: Row, ordinal: Int): Unit = { + override def gatherStats(row: InternalRow, ordinal: Int): Unit = { super.gatherStats(row, ordinal) if (!row.isNullAt(ordinal)) { sizeInBytes += GENERIC.actualSize(row, ordinal) } } - override def collectedStatistics: Row = Row(null, null, nullCount, count, sizeInBytes) + override def collectedStatistics: InternalRow = + InternalRow(null, null, nullCount, count, sizeInBytes) } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala index 3db26fad2b..761f427b8c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala @@ -19,21 +19,16 @@ package org.apache.spark.sql.columnar import java.nio.ByteBuffer -import org.apache.spark.{Accumulable, Accumulator, Accumulators} -import org.apache.spark.sql.catalyst.expressions - import scala.collection.mutable.ArrayBuffer -import scala.collection.mutable.HashMap import org.apache.spark.rdd.RDD -import org.apache.spark.sql.Row -import org.apache.spark.SparkContext import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation import org.apache.spark.sql.catalyst.dsl.expressions._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Statistics} import org.apache.spark.sql.execution.{LeafNode, SparkPlan} import org.apache.spark.storage.StorageLevel +import org.apache.spark.{Accumulable, Accumulator, Accumulators} private[sql] object InMemoryRelation { def apply( @@ -45,7 +40,7 @@ private[sql] object InMemoryRelation { new InMemoryRelation(child.output, useCompression, batchSize, storageLevel, child, tableName)() } -private[sql] case class CachedBatch(buffers: Array[Array[Byte]], stats: Row) +private[sql] case class CachedBatch(buffers: Array[Array[Byte]], stats: InternalRow) private[sql] case class InMemoryRelation( output: Seq[Attribute], @@ -56,12 +51,12 @@ private[sql] case class InMemoryRelation( tableName: Option[String])( private var _cachedColumnBuffers: RDD[CachedBatch] = null, private var _statistics: Statistics = null, - private var _batchStats: Accumulable[ArrayBuffer[Row], Row] = null) + private var _batchStats: Accumulable[ArrayBuffer[InternalRow], InternalRow] = null) extends LogicalPlan with MultiInstanceRelation { - private val batchStats: Accumulable[ArrayBuffer[Row], Row] = + private val batchStats: Accumulable[ArrayBuffer[InternalRow], InternalRow] = if (_batchStats == null) { - child.sqlContext.sparkContext.accumulableCollection(ArrayBuffer.empty[Row]) + child.sqlContext.sparkContext.accumulableCollection(ArrayBuffer.empty[InternalRow]) } else { _batchStats } @@ -151,7 +146,7 @@ private[sql] case class InMemoryRelation( rowCount += 1 } - val stats = Row.merge(columnBuilders.map(_.columnStats.collectedStatistics) : _*) + val stats = InternalRow.merge(columnBuilders.map(_.columnStats.collectedStatistics) : _*) batchStats += stats CachedBatch(columnBuilders.map(_.build().array()), stats) @@ -267,7 +262,7 @@ private[sql] case class InMemoryColumnarTableScan( private val inMemoryPartitionPruningEnabled = sqlContext.conf.inMemoryPartitionPruning - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { if (enableAccumulators) { readPartitions.setValue(0) readBatches.setValue(0) @@ -296,7 +291,7 @@ private[sql] case class InMemoryColumnarTableScan( val nextRow = new SpecificMutableRow(requestedColumnDataTypes) - def cachedBatchesToRows(cacheBatches: Iterator[CachedBatch]): Iterator[Row] = { + def cachedBatchesToRows(cacheBatches: Iterator[CachedBatch]): Iterator[InternalRow] = { val rows = cacheBatches.flatMap { cachedBatch => // Build column accessors val columnAccessors = requestedColumnIndices.map { batchColumnIndex => @@ -306,15 +301,15 @@ private[sql] case class InMemoryColumnarTableScan( } // Extract rows via column accessors - new Iterator[Row] { + new Iterator[InternalRow] { private[this] val rowLen = nextRow.length - override def next(): Row = { + override def next(): InternalRow = { var i = 0 while (i < rowLen) { columnAccessors(i).extractTo(nextRow, i) i += 1 } - if (attributes.isEmpty) Row.empty else nextRow + if (attributes.isEmpty) InternalRow.empty else nextRow } override def hasNext: Boolean = columnAccessors(0).hasNext diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnBuilder.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnBuilder.scala index f1f494ac26..ba47bc783f 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnBuilder.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/NullableColumnBuilder.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.columnar import java.nio.{ByteBuffer, ByteOrder} -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow /** * A stackable trait used for building byte buffer for a column containing null values. Memory @@ -52,7 +52,7 @@ private[sql] trait NullableColumnBuilder extends ColumnBuilder { super.initialize(initialSize, columnName, useCompression) } - abstract override def appendFrom(row: Row, ordinal: Int): Unit = { + abstract override def appendFrom(row: InternalRow, ordinal: Int): Unit = { columnStats.gatherStats(row, ordinal) if (row.isNullAt(ordinal)) { nulls = ColumnBuilder.ensureFreeSpace(nulls, 4) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala index 8e2a1af6da..39b21ddb47 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala @@ -20,7 +20,7 @@ package org.apache.spark.sql.columnar.compression import java.nio.{ByteBuffer, ByteOrder} import org.apache.spark.Logging -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.columnar.{ColumnBuilder, NativeColumnBuilder} import org.apache.spark.sql.types.AtomicType @@ -66,7 +66,7 @@ private[sql] trait CompressibleColumnBuilder[T <: AtomicType] encoder.compressionRatio < 0.8 } - private def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + private def gatherCompressibilityStats(row: InternalRow, ordinal: Int): Unit = { var i = 0 while (i < compressionEncoders.length) { compressionEncoders(i).gatherCompressibilityStats(row, ordinal) @@ -74,7 +74,7 @@ private[sql] trait CompressibleColumnBuilder[T <: AtomicType] } } - abstract override def appendFrom(row: Row, ordinal: Int): Unit = { + abstract override def appendFrom(row: InternalRow, ordinal: Int): Unit = { super.appendFrom(row, ordinal) if (!row.isNullAt(ordinal)) { gatherCompressibilityStats(row, ordinal) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala index 17c2d9b111..4eaec6d853 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala @@ -18,14 +18,13 @@ package org.apache.spark.sql.columnar.compression import java.nio.{ByteBuffer, ByteOrder} - -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.MutableRow import org.apache.spark.sql.columnar.{ColumnType, NativeColumnType} import org.apache.spark.sql.types.AtomicType private[sql] trait Encoder[T <: AtomicType] { - def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = {} + def gatherCompressibilityStats(row: InternalRow, ordinal: Int): Unit = {} def compressedSize: Int diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala index 534ae90ddb..5abc1259a1 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala @@ -22,8 +22,7 @@ import java.nio.ByteBuffer import scala.collection.mutable import scala.reflect.ClassTag import scala.reflect.runtime.universe.runtimeMirror - -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.{MutableRow, SpecificMutableRow} import org.apache.spark.sql.columnar._ import org.apache.spark.sql.types._ @@ -96,7 +95,7 @@ private[sql] case object RunLengthEncoding extends CompressionScheme { override def compressedSize: Int = _compressedSize - override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + override def gatherCompressibilityStats(row: InternalRow, ordinal: Int): Unit = { val value = columnType.getField(row, ordinal) val actualSize = columnType.actualSize(row, ordinal) _uncompressedSize += actualSize @@ -217,7 +216,7 @@ private[sql] case object DictionaryEncoding extends CompressionScheme { // to store dictionary element count. private var dictionarySize = 4 - override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + override def gatherCompressibilityStats(row: InternalRow, ordinal: Int): Unit = { val value = columnType.getField(row, ordinal) if (!overflow) { @@ -310,7 +309,7 @@ private[sql] case object BooleanBitSet extends CompressionScheme { class Encoder extends compression.Encoder[BooleanType.type] { private var _uncompressedSize = 0 - override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + override def gatherCompressibilityStats(row: InternalRow, ordinal: Int): Unit = { _uncompressedSize += BOOLEAN.defaultSize } @@ -404,7 +403,7 @@ private[sql] case object IntDelta extends CompressionScheme { private var prevValue: Int = _ - override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + override def gatherCompressibilityStats(row: InternalRow, ordinal: Int): Unit = { val value = row.getInt(ordinal) val delta = value - prevValue @@ -484,7 +483,7 @@ private[sql] case object LongDelta extends CompressionScheme { private var prevValue: Long = _ - override def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = { + override def gatherCompressibilityStats(row: InternalRow, ordinal: Int): Unit = { val value = row.getLong(ordinal) val delta = value - prevValue diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Aggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Aggregate.scala index 8d16749697..6e8a5ef18a 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/Aggregate.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Aggregate.scala @@ -20,12 +20,10 @@ package org.apache.spark.sql.execution import java.util.HashMap import org.apache.spark.annotation.DeveloperApi -import org.apache.spark.SparkContext import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.errors._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.physical._ -import org.apache.spark.sql.SQLContext /** * :: DeveloperApi :: @@ -121,11 +119,11 @@ case class Aggregate( } } - protected override def doExecute(): RDD[Row] = attachTree(this, "execute") { + protected override def doExecute(): RDD[InternalRow] = attachTree(this, "execute") { if (groupingExpressions.isEmpty) { child.execute().mapPartitions { iter => val buffer = newAggregateBuffer() - var currentRow: Row = null + var currentRow: InternalRow = null while (iter.hasNext) { currentRow = iter.next() var i = 0 @@ -147,10 +145,10 @@ case class Aggregate( } } else { child.execute().mapPartitions { iter => - val hashTable = new HashMap[Row, Array[AggregateFunction]] + val hashTable = new HashMap[InternalRow, Array[AggregateFunction]] val groupingProjection = new InterpretedMutableProjection(groupingExpressions, child.output) - var currentRow: Row = null + var currentRow: InternalRow = null while (iter.hasNext) { currentRow = iter.next() val currentGroup = groupingProjection(currentRow) @@ -167,7 +165,7 @@ case class Aggregate( } } - new Iterator[Row] { + new Iterator[InternalRow] { private[this] val hashTableIter = hashTable.entrySet().iterator() private[this] val aggregateResults = new GenericMutableRow(computedAggregates.length) private[this] val resultProjection = @@ -177,7 +175,7 @@ case class Aggregate( override final def hasNext: Boolean = hashTableIter.hasNext - override final def next(): Row = { + override final def next(): InternalRow = { val currentEntry = hashTableIter.next() val currentGroup = currentEntry.getKey val currentBuffer = currentEntry.getValue diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala index 6fa7ccc6cc..c9a188309a 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala @@ -17,19 +17,19 @@ package org.apache.spark.sql.execution -import org.apache.spark.{HashPartitioner, Partitioner, RangePartitioner, SparkEnv} import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.{RDD, ShuffledRDD} import org.apache.spark.serializer.Serializer import org.apache.spark.shuffle.sort.SortShuffleManager import org.apache.spark.shuffle.unsafe.UnsafeShuffleManager +import org.apache.spark.sql.SQLContext import org.apache.spark.sql.catalyst.errors.attachTree import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.physical._ import org.apache.spark.sql.catalyst.rules.Rule import org.apache.spark.sql.types.DataType -import org.apache.spark.sql.{SQLContext, Row} import org.apache.spark.util.MutablePair +import org.apache.spark.{HashPartitioner, Partitioner, RangePartitioner, SparkEnv} /** * :: DeveloperApi :: @@ -157,7 +157,7 @@ case class Exchange( serializer } - protected override def doExecute(): RDD[Row] = attachTree(this , "execute") { + protected override def doExecute(): RDD[InternalRow] = attachTree(this , "execute") { newPartitioning match { case HashPartitioning(expressions, numPartitions) => val keySchema = expressions.map(_.dataType).toArray @@ -173,11 +173,11 @@ case class Exchange( } else { child.execute().mapPartitions { iter => val hashExpressions = newMutableProjection(expressions, child.output)() - val mutablePair = new MutablePair[Row, Row]() + val mutablePair = new MutablePair[InternalRow, InternalRow]() iter.map(r => mutablePair.update(hashExpressions(r), r)) } } - val shuffled = new ShuffledRDD[Row, Row, Row](rdd, part) + val shuffled = new ShuffledRDD[InternalRow, InternalRow, InternalRow](rdd, part) shuffled.setSerializer(serializer) shuffled.map(_._2) @@ -190,7 +190,7 @@ case class Exchange( // Internally, RangePartitioner runs a job on the RDD that samples keys to compute // partition bounds. To get accurate samples, we need to copy the mutable keys. val rddForSampling = childRdd.mapPartitions { iter => - val mutablePair = new MutablePair[Row, Null]() + val mutablePair = new MutablePair[InternalRow, Null]() iter.map(row => mutablePair.update(row.copy(), null)) } // TODO: RangePartitioner should take an Ordering. @@ -202,12 +202,12 @@ case class Exchange( childRdd.mapPartitions { iter => iter.map(row => (row.copy(), null))} } else { childRdd.mapPartitions { iter => - val mutablePair = new MutablePair[Row, Null]() + val mutablePair = new MutablePair[InternalRow, Null]() iter.map(row => mutablePair.update(row, null)) } } - val shuffled = new ShuffledRDD[Row, Null, Null](rdd, part) + val shuffled = new ShuffledRDD[InternalRow, Null, Null](rdd, part) shuffled.setSerializer(serializer) shuffled.map(_._1) @@ -217,14 +217,16 @@ case class Exchange( val partitioner = new HashPartitioner(1) val rdd = if (needToCopyObjectsBeforeShuffle(partitioner, serializer)) { - child.execute().mapPartitions { iter => iter.map(r => (null, r.copy())) } + child.execute().mapPartitions { + iter => iter.map(r => (null, r.copy())) + } } else { child.execute().mapPartitions { iter => - val mutablePair = new MutablePair[Null, Row]() + val mutablePair = new MutablePair[Null, InternalRow]() iter.map(r => mutablePair.update(null, r)) } } - val shuffled = new ShuffledRDD[Null, Row, Row](rdd, partitioner) + val shuffled = new ShuffledRDD[Null, InternalRow, InternalRow](rdd, partitioner) shuffled.setSerializer(serializer) shuffled.map(_._2) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala index f931dc95ef..da27a753a7 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.execution import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.CatalystTypeConverters +import org.apache.spark.sql.catalyst.{InternalRow, CatalystTypeConverters} import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation import org.apache.spark.sql.catalyst.expressions.{Attribute, GenericMutableRow} import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Statistics} @@ -31,7 +31,7 @@ import org.apache.spark.sql.{Row, SQLContext} */ @DeveloperApi object RDDConversions { - def productToRowRdd[A <: Product](data: RDD[A], outputTypes: Seq[DataType]): RDD[Row] = { + def productToRowRdd[A <: Product](data: RDD[A], outputTypes: Seq[DataType]): RDD[InternalRow] = { data.mapPartitions { iterator => val numColumns = outputTypes.length val mutableRow = new GenericMutableRow(numColumns) @@ -51,7 +51,7 @@ object RDDConversions { /** * Convert the objects inside Row into the types Catalyst expected. */ - def rowToRowRdd(data: RDD[Row], outputTypes: Seq[DataType]): RDD[Row] = { + def rowToRowRdd(data: RDD[Row], outputTypes: Seq[DataType]): RDD[InternalRow] = { data.mapPartitions { iterator => val numColumns = outputTypes.length val mutableRow = new GenericMutableRow(numColumns) @@ -70,7 +70,9 @@ object RDDConversions { } /** Logical plan node for scanning data from an RDD. */ -private[sql] case class LogicalRDD(output: Seq[Attribute], rdd: RDD[Row])(sqlContext: SQLContext) +private[sql] case class LogicalRDD( + output: Seq[Attribute], + rdd: RDD[InternalRow])(sqlContext: SQLContext) extends LogicalPlan with MultiInstanceRelation { override def children: Seq[LogicalPlan] = Nil @@ -91,13 +93,15 @@ private[sql] case class LogicalRDD(output: Seq[Attribute], rdd: RDD[Row])(sqlCon } /** Physical plan node for scanning data from an RDD. */ -private[sql] case class PhysicalRDD(output: Seq[Attribute], rdd: RDD[Row]) extends LeafNode { - protected override def doExecute(): RDD[Row] = rdd +private[sql] case class PhysicalRDD( + output: Seq[Attribute], + rdd: RDD[InternalRow]) extends LeafNode { + protected override def doExecute(): RDD[InternalRow] = rdd } /** Logical plan node for scanning data from a local collection. */ private[sql] -case class LogicalLocalTable(output: Seq[Attribute], rows: Seq[Row])(sqlContext: SQLContext) +case class LogicalLocalTable(output: Seq[Attribute], rows: Seq[InternalRow])(sqlContext: SQLContext) extends LogicalPlan with MultiInstanceRelation { override def children: Seq[LogicalPlan] = Nil diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Expand.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Expand.scala index 4b601c1192..42a0c1be4f 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/Expand.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Expand.scala @@ -19,10 +19,9 @@ package org.apache.spark.sql.execution import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD -import org.apache.spark.sql.SQLContext import org.apache.spark.sql.catalyst.errors._ import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.plans.physical.{UnknownPartitioning, Partitioning} +import org.apache.spark.sql.catalyst.plans.physical.{Partitioning, UnknownPartitioning} /** * Apply the all of the GroupExpressions to every input row, hence we will get @@ -43,7 +42,7 @@ case class Expand( // as UNKNOWN partitioning override def outputPartitioning: Partitioning = UnknownPartitioning(0) - protected override def doExecute(): RDD[Row] = attachTree(this, "execute") { + protected override def doExecute(): RDD[InternalRow] = attachTree(this, "execute") { child.execute().mapPartitions { iter => // TODO Move out projection objects creation and transfer to // workers via closure. However we can't assume the Projection @@ -51,14 +50,14 @@ case class Expand( // create the projections within each of the partition processing. val groups = projections.map(ee => newProjection(ee, child.output)).toArray - new Iterator[Row] { - private[this] var result: Row = _ + new Iterator[InternalRow] { + private[this] var result: InternalRow = _ private[this] var idx = -1 // -1 means the initial state - private[this] var input: Row = _ + private[this] var input: InternalRow = _ override final def hasNext: Boolean = (-1 < idx && idx < groups.length) || iter.hasNext - override final def next(): Row = { + override final def next(): InternalRow = { if (idx <= 0) { // in the initial (-1) or beginning(0) of a new input row, fetch the next input tuple input = iter.next() diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Generate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Generate.scala index dd02c1f457..c1665f78a9 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/Generate.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Generate.scala @@ -25,12 +25,12 @@ import org.apache.spark.sql.catalyst.expressions._ * For lazy computing, be sure the generator.terminate() called in the very last * TODO reusing the CompletionIterator? */ -private[execution] sealed case class LazyIterator(func: () => TraversableOnce[Row]) - extends Iterator[Row] { +private[execution] sealed case class LazyIterator(func: () => TraversableOnce[InternalRow]) + extends Iterator[InternalRow] { lazy val results = func().toIterator override def hasNext: Boolean = results.hasNext - override def next(): Row = results.next() + override def next(): InternalRow = results.next() } /** @@ -58,11 +58,11 @@ case class Generate( val boundGenerator = BindReferences.bindReference(generator, child.output) - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { // boundGenerator.terminate() should be triggered after all of the rows in the partition if (join) { child.execute().mapPartitions { iter => - val generatorNullRow = Row.fromSeq(Seq.fill[Any](generator.elementTypes.size)(null)) + val generatorNullRow = InternalRow.fromSeq(Seq.fill[Any](generator.elementTypes.size)(null)) val joinedRow = new JoinedRow iter.flatMap { row => diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala index 1c40a9209f..ba2c8f53d7 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala @@ -66,7 +66,7 @@ case class GeneratedAggregate( override def output: Seq[Attribute] = aggregateExpressions.map(_.toAttribute) - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val aggregatesToCompute = aggregateExpressions.flatMap { a => a.collect { case agg: AggregateExpression => agg} } @@ -273,7 +273,7 @@ case class GeneratedAggregate( if (groupingExpressions.isEmpty) { // TODO: Codegening anything other than the updateProjection is probably over kill. val buffer = newAggregationBuffer(EmptyRow).asInstanceOf[MutableRow] - var currentRow: Row = null + var currentRow: InternalRow = null updateProjection.target(buffer) while (iter.hasNext) { @@ -295,19 +295,19 @@ case class GeneratedAggregate( ) while (iter.hasNext) { - val currentRow: Row = iter.next() - val groupKey: Row = groupProjection(currentRow) + val currentRow: InternalRow = iter.next() + val groupKey: InternalRow = groupProjection(currentRow) val aggregationBuffer = aggregationMap.getAggregationBuffer(groupKey) updateProjection.target(aggregationBuffer)(joinedRow(aggregationBuffer, currentRow)) } - new Iterator[Row] { + new Iterator[InternalRow] { private[this] val mapIterator = aggregationMap.iterator() private[this] val resultProjection = resultProjectionBuilder() def hasNext: Boolean = mapIterator.hasNext - def next(): Row = { + def next(): InternalRow = { val entry = mapIterator.next() val result = resultProjection(joinedRow(entry.key, entry.value)) if (hasNext) { @@ -326,9 +326,9 @@ case class GeneratedAggregate( if (unsafeEnabled) { log.info("Not using Unsafe-based aggregator because it is not supported for this schema") } - val buffers = new java.util.HashMap[Row, MutableRow]() + val buffers = new java.util.HashMap[InternalRow, MutableRow]() - var currentRow: Row = null + var currentRow: InternalRow = null while (iter.hasNext) { currentRow = iter.next() val currentGroup = groupProjection(currentRow) @@ -342,13 +342,13 @@ case class GeneratedAggregate( updateProjection.target(currentBuffer)(joinedRow(currentBuffer, currentRow)) } - new Iterator[Row] { + new Iterator[InternalRow] { private[this] val resultIterator = buffers.entrySet.iterator() private[this] val resultProjection = resultProjectionBuilder() def hasNext: Boolean = resultIterator.hasNext - def next(): Row = { + def next(): InternalRow = { val currentGroup = resultIterator.next() resultProjection(joinedRow(currentGroup.getKey, currentGroup.getValue)) } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala index 03bee80ad7..cd341180b6 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala @@ -19,18 +19,20 @@ package org.apache.spark.sql.execution import org.apache.spark.rdd.RDD import org.apache.spark.sql.Row -import org.apache.spark.sql.catalyst.CatalystTypeConverters +import org.apache.spark.sql.catalyst.{InternalRow, CatalystTypeConverters} import org.apache.spark.sql.catalyst.expressions.Attribute /** * Physical plan node for scanning data from a local collection. */ -private[sql] case class LocalTableScan(output: Seq[Attribute], rows: Seq[Row]) extends LeafNode { +private[sql] case class LocalTableScan( + output: Seq[Attribute], + rows: Seq[InternalRow]) extends LeafNode { private lazy val rdd = sqlContext.sparkContext.parallelize(rows) - protected override def doExecute(): RDD[Row] = rdd + protected override def doExecute(): RDD[InternalRow] = rdd override def executeCollect(): Array[Row] = { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala index 435ac01117..7739a9f949 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala @@ -23,6 +23,7 @@ import org.apache.spark.rdd.{RDD, RDDOperationScope} import org.apache.spark.sql.SQLContext import org.apache.spark.sql.catalyst.{CatalystTypeConverters, trees} import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.expressions.codegen._ import org.apache.spark.sql.catalyst.plans.QueryPlan import org.apache.spark.sql.catalyst.plans.physical._ @@ -79,11 +80,11 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ def requiredChildOrdering: Seq[Seq[SortOrder]] = Seq.fill(children.size)(Nil) /** - * Returns the result of this query as an RDD[Row] by delegating to doExecute + * Returns the result of this query as an RDD[InternalRow] by delegating to doExecute * after adding query plan information to created RDDs for visualization. * Concrete implementations of SparkPlan should override doExecute instead. */ - final def execute(): RDD[Row] = { + final def execute(): RDD[InternalRow] = { RDDOperationScope.withScope(sparkContext, nodeName, false, true) { doExecute() } @@ -91,9 +92,9 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ /** * Overridden by concrete implementations of SparkPlan. - * Produces the result of the query as an RDD[Row] + * Produces the result of the query as an RDD[InternalRow] */ - protected def doExecute(): RDD[Row] + protected def doExecute(): RDD[InternalRow] /** * Runs this query returning the result as an array. @@ -117,7 +118,7 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ val childRDD = execute().map(_.copy()) - val buf = new ArrayBuffer[Row] + val buf = new ArrayBuffer[InternalRow] val totalParts = childRDD.partitions.length var partsScanned = 0 while (buf.size < n && partsScanned < totalParts) { @@ -140,7 +141,8 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ val p = partsScanned until math.min(partsScanned + numPartsToTry, totalParts) val sc = sqlContext.sparkContext val res = - sc.runJob(childRDD, (it: Iterator[Row]) => it.take(left).toArray, p, allowLocal = false) + sc.runJob(childRDD, (it: Iterator[InternalRow]) => it.take(left).toArray, p, + allowLocal = false) res.foreach(buf ++= _.take(n - buf.size)) partsScanned += numPartsToTry @@ -175,7 +177,7 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ protected def newPredicate( - expression: Expression, inputSchema: Seq[Attribute]): (Row) => Boolean = { + expression: Expression, inputSchema: Seq[Attribute]): (InternalRow) => Boolean = { if (codegenEnabled) { GeneratePredicate.generate(expression, inputSchema) } else { @@ -183,7 +185,9 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ } } - protected def newOrdering(order: Seq[SortOrder], inputSchema: Seq[Attribute]): Ordering[Row] = { + protected def newOrdering( + order: Seq[SortOrder], + inputSchema: Seq[Attribute]): Ordering[InternalRow] = { if (codegenEnabled) { GenerateOrdering.generate(order, inputSchema) } else { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index 7a1331a391..422992d019 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -203,7 +203,7 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { } protected lazy val singleRowRdd = - sparkContext.parallelize(Seq(new GenericRow(Array[Any]()): Row), 1) + sparkContext.parallelize(Seq(new GenericRow(Array[Any]()): InternalRow), 1) object TakeOrdered extends Strategy { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala index c4327ce262..fd6f1d7ae1 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala @@ -20,9 +20,8 @@ package org.apache.spark.sql.execution import java.util import org.apache.spark.rdd.RDD -import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.plans.physical.{AllTuples, Distribution, ClusteredDistribution, Partitioning} +import org.apache.spark.sql.catalyst.plans.physical.{AllTuples, ClusteredDistribution, Distribution, Partitioning} import org.apache.spark.util.collection.CompactBuffer /** @@ -112,16 +111,16 @@ case class Window( } } - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { child.execute().mapPartitions { iter => - new Iterator[Row] { + new Iterator[InternalRow] { // Although input rows are grouped based on windowSpec.partitionSpec, we need to // know when we have a new partition. // This is to manually construct an ordering that can be used to compare rows. // TODO: We may want to have a newOrdering that takes BoundReferences. // So, we can take advantave of code gen. - private val partitionOrdering: Ordering[Row] = + private val partitionOrdering: Ordering[InternalRow] = RowOrdering.forSchema(windowSpec.partitionSpec.map(_.dataType)) // This is used to project expressions for the partition specification. @@ -137,13 +136,13 @@ case class Window( // The number of buffered rows in the inputRowBuffer (the size of the current partition). var partitionSize: Int = 0 // The buffer used to buffer rows in a partition. - var inputRowBuffer: CompactBuffer[Row] = _ + var inputRowBuffer: CompactBuffer[InternalRow] = _ // The partition key of the current partition. - var currentPartitionKey: Row = _ + var currentPartitionKey: InternalRow = _ // The partition key of next partition. - var nextPartitionKey: Row = _ + var nextPartitionKey: InternalRow = _ // The first row of next partition. - var firstRowInNextPartition: Row = _ + var firstRowInNextPartition: InternalRow = _ // Indicates if this partition is the last one in the iter. var lastPartition: Boolean = false @@ -316,7 +315,7 @@ case class Window( !lastPartition || (rowPosition < partitionSize) } - override final def next(): Row = { + override final def next(): InternalRow = { if (hasNext) { if (rowPosition == partitionSize) { // All rows of this buffer have been consumed. @@ -353,7 +352,7 @@ case class Window( // Fetch the next partition. private def fetchNextPartition(): Unit = { // Create a new buffer for input rows. - inputRowBuffer = new CompactBuffer[Row]() + inputRowBuffer = new CompactBuffer[InternalRow]() // We already have the first row for this partition // (recorded in firstRowInNextPartition). Add it back. inputRowBuffer += firstRowInNextPartition diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala index fb42072f9d..7aedd630e3 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala @@ -17,16 +17,17 @@ package org.apache.spark.sql.execution -import org.apache.spark.{SparkEnv, HashPartitioner, SparkConf} import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.{RDD, ShuffledRDD} import org.apache.spark.shuffle.sort.SortShuffleManager import org.apache.spark.sql.catalyst.CatalystTypeConverters import org.apache.spark.sql.catalyst.errors._ import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.plans.physical._ -import org.apache.spark.util.{CompletionIterator, MutablePair} import org.apache.spark.util.collection.ExternalSorter +import org.apache.spark.util.{CompletionIterator, MutablePair} +import org.apache.spark.{HashPartitioner, SparkEnv} /** * :: DeveloperApi :: @@ -37,7 +38,7 @@ case class Project(projectList: Seq[NamedExpression], child: SparkPlan) extends @transient lazy val buildProjection = newMutableProjection(projectList, child.output) - protected override def doExecute(): RDD[Row] = child.execute().mapPartitions { iter => + protected override def doExecute(): RDD[InternalRow] = child.execute().mapPartitions { iter => val resuableProjection = buildProjection() iter.map(resuableProjection) } @@ -52,9 +53,10 @@ case class Project(projectList: Seq[NamedExpression], child: SparkPlan) extends case class Filter(condition: Expression, child: SparkPlan) extends UnaryNode { override def output: Seq[Attribute] = child.output - @transient lazy val conditionEvaluator: (Row) => Boolean = newPredicate(condition, child.output) + @transient lazy val conditionEvaluator: (InternalRow) => Boolean = + newPredicate(condition, child.output) - protected override def doExecute(): RDD[Row] = child.execute().mapPartitions { iter => + protected override def doExecute(): RDD[InternalRow] = child.execute().mapPartitions { iter => iter.filter(conditionEvaluator) } @@ -83,7 +85,7 @@ case class Sample( override def output: Seq[Attribute] = child.output // TODO: How to pick seed? - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { if (withReplacement) { child.execute().map(_.copy()).sample(withReplacement, upperBound - lowerBound, seed) } else { @@ -99,7 +101,8 @@ case class Sample( case class Union(children: Seq[SparkPlan]) extends SparkPlan { // TODO: attributes output by union should be distinct for nullability purposes override def output: Seq[Attribute] = children.head.output - protected override def doExecute(): RDD[Row] = sparkContext.union(children.map(_.execute())) + protected override def doExecute(): RDD[InternalRow] = + sparkContext.union(children.map(_.execute())) } /** @@ -124,19 +127,19 @@ case class Limit(limit: Int, child: SparkPlan) override def executeCollect(): Array[Row] = child.executeTake(limit) - protected override def doExecute(): RDD[Row] = { - val rdd: RDD[_ <: Product2[Boolean, Row]] = if (sortBasedShuffleOn) { + protected override def doExecute(): RDD[InternalRow] = { + val rdd: RDD[_ <: Product2[Boolean, InternalRow]] = if (sortBasedShuffleOn) { child.execute().mapPartitions { iter => iter.take(limit).map(row => (false, row.copy())) } } else { child.execute().mapPartitions { iter => - val mutablePair = new MutablePair[Boolean, Row]() + val mutablePair = new MutablePair[Boolean, InternalRow]() iter.take(limit).map(row => mutablePair.update(false, row)) } } val part = new HashPartitioner(1) - val shuffled = new ShuffledRDD[Boolean, Row, Row](rdd, part) + val shuffled = new ShuffledRDD[Boolean, InternalRow, InternalRow](rdd, part) shuffled.setSerializer(new SparkSqlSerializer(child.sqlContext.sparkContext.getConf)) shuffled.mapPartitions(_.take(limit).map(_._2)) } @@ -157,7 +160,8 @@ case class TakeOrdered(limit: Int, sortOrder: Seq[SortOrder], child: SparkPlan) private val ord: RowOrdering = new RowOrdering(sortOrder, child.output) - private def collectData(): Array[Row] = child.execute().map(_.copy()).takeOrdered(limit)(ord) + private def collectData(): Array[InternalRow] = + child.execute().map(_.copy()).takeOrdered(limit)(ord) override def executeCollect(): Array[Row] = { val converter = CatalystTypeConverters.createToScalaConverter(schema) @@ -166,7 +170,7 @@ case class TakeOrdered(limit: Int, sortOrder: Seq[SortOrder], child: SparkPlan) // TODO: Terminal split should be implemented differently from non-terminal split. // TODO: Pick num splits based on |limit|. - protected override def doExecute(): RDD[Row] = sparkContext.makeRDD(collectData(), 1) + protected override def doExecute(): RDD[InternalRow] = sparkContext.makeRDD(collectData(), 1) override def outputOrdering: Seq[SortOrder] = sortOrder } @@ -186,7 +190,7 @@ case class Sort( override def requiredChildDistribution: Seq[Distribution] = if (global) OrderedDistribution(sortOrder) :: Nil else UnspecifiedDistribution :: Nil - protected override def doExecute(): RDD[Row] = attachTree(this, "sort") { + protected override def doExecute(): RDD[InternalRow] = attachTree(this, "sort") { child.execute().mapPartitions( { iterator => val ordering = newOrdering(sortOrder, child.output) iterator.map(_.copy()).toArray.sorted(ordering).iterator @@ -214,14 +218,14 @@ case class ExternalSort( override def requiredChildDistribution: Seq[Distribution] = if (global) OrderedDistribution(sortOrder) :: Nil else UnspecifiedDistribution :: Nil - protected override def doExecute(): RDD[Row] = attachTree(this, "sort") { + protected override def doExecute(): RDD[InternalRow] = attachTree(this, "sort") { child.execute().mapPartitions( { iterator => val ordering = newOrdering(sortOrder, child.output) - val sorter = new ExternalSorter[Row, Null, Row](ordering = Some(ordering)) + val sorter = new ExternalSorter[InternalRow, Null, InternalRow](ordering = Some(ordering)) sorter.insertAll(iterator.map(r => (r.copy, null))) val baseIterator = sorter.iterator.map(_._1) // TODO(marmbrus): The complex type signature below thwarts inference for no reason. - CompletionIterator[Row, Iterator[Row]](baseIterator, sorter.stop()) + CompletionIterator[InternalRow, Iterator[InternalRow]](baseIterator, sorter.stop()) }, preservesPartitioning = true) } @@ -239,7 +243,7 @@ case class Repartition(numPartitions: Int, shuffle: Boolean, child: SparkPlan) extends UnaryNode { override def output: Seq[Attribute] = child.output - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { child.execute().map(_.copy()).coalesce(numPartitions, shuffle) } } @@ -254,7 +258,7 @@ case class Repartition(numPartitions: Int, shuffle: Boolean, child: SparkPlan) case class Except(left: SparkPlan, right: SparkPlan) extends BinaryNode { override def output: Seq[Attribute] = left.output - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { left.execute().map(_.copy()).subtract(right.execute().map(_.copy())) } } @@ -268,7 +272,7 @@ case class Except(left: SparkPlan, right: SparkPlan) extends BinaryNode { case class Intersect(left: SparkPlan, right: SparkPlan) extends BinaryNode { override def output: Seq[Attribute] = children.head.output - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { left.execute().map(_.copy()).intersection(right.execute().map(_.copy())) } } @@ -283,5 +287,5 @@ case class Intersect(left: SparkPlan, right: SparkPlan) extends BinaryNode { case class OutputFaker(output: Seq[Attribute], child: SparkPlan) extends SparkPlan { def children: Seq[SparkPlan] = child :: Nil - protected override def doExecute(): RDD[Row] = child.execute() + protected override def doExecute(): RDD[InternalRow] = child.execute() } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala index 49b361e96b..653792ea2e 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala @@ -20,13 +20,13 @@ package org.apache.spark.sql.execution import org.apache.spark.Logging import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.CatalystTypeConverters +import org.apache.spark.sql.catalyst.{InternalRow, CatalystTypeConverters} import org.apache.spark.sql.catalyst.errors.TreeNodeException -import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference, Row} +import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference} import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.types._ -import org.apache.spark.sql.{DataFrame, SQLConf, SQLContext} +import org.apache.spark.sql.{DataFrame, Row, SQLConf, SQLContext} /** * A logical command that is executed for its side-effects. `RunnableCommand`s are @@ -64,9 +64,9 @@ private[sql] case class ExecutedCommand(cmd: RunnableCommand) extends SparkPlan override def executeTake(limit: Int): Array[Row] = sideEffectResult.take(limit).toArray - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val converted = sideEffectResult.map(r => - CatalystTypeConverters.convertToCatalyst(r, schema).asInstanceOf[Row]) + CatalystTypeConverters.convertToCatalyst(r, schema).asInstanceOf[InternalRow]) sqlContext.sparkContext.parallelize(converted, 1) } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/debug/package.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/debug/package.scala index 83c1f65d5c..3ee4033bae 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/debug/package.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/debug/package.scala @@ -18,6 +18,7 @@ package org.apache.spark.sql.execution import org.apache.spark.rdd.RDD +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.Attribute import org.apache.spark.unsafe.types.UTF8String @@ -25,7 +26,7 @@ import scala.collection.mutable.HashSet import org.apache.spark.{AccumulatorParam, Accumulator} import org.apache.spark.annotation.DeveloperApi -import org.apache.spark.sql.{SQLConf, SQLContext, DataFrame, Row} +import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.trees.TreeNodeRef import org.apache.spark.sql.types._ @@ -126,11 +127,11 @@ package object debug { } } - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { child.execute().mapPartitions { iter => - new Iterator[Row] { + new Iterator[InternalRow] { def hasNext: Boolean = iter.hasNext - def next(): Row = { + def next(): InternalRow = { val currentRow = iter.next() tupleCount += 1 var i = 0 @@ -155,7 +156,7 @@ package object debug { def typeCheck(data: Any, schema: DataType): Unit = (data, schema) match { case (null, _) => - case (row: Row, StructType(fields)) => + case (row: InternalRow, StructType(fields)) => row.toSeq.zip(fields.map(_.dataType)).foreach { case(d, t) => typeCheck(d, t) } case (s: Seq[_], ArrayType(elemType, _)) => s.foreach(typeCheck(_, elemType)) @@ -196,7 +197,7 @@ package object debug { def children: List[SparkPlan] = child :: Nil - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { child.execute().map { row => try typeCheck(row, child.schema) catch { case e: Exception => diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/expressions/MonotonicallyIncreasingID.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/expressions/MonotonicallyIncreasingID.scala index e228a60c90..68914cf85c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/expressions/MonotonicallyIncreasingID.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/expressions/MonotonicallyIncreasingID.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.execution.expressions import org.apache.spark.TaskContext -import org.apache.spark.sql.catalyst.expressions.{Row, LeafExpression} +import org.apache.spark.sql.catalyst.expressions.{InternalRow, LeafExpression} import org.apache.spark.sql.types.{LongType, DataType} /** @@ -43,7 +43,7 @@ private[sql] case class MonotonicallyIncreasingID() extends LeafExpression { override def dataType: DataType = LongType - override def eval(input: Row): Long = { + override def eval(input: InternalRow): Long = { val currentCount = count count += 1 (TaskContext.get().partitionId().toLong << 33) + currentCount diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/expressions/SparkPartitionID.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/expressions/SparkPartitionID.scala index 1272793f88..12c2eed0d6 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/expressions/SparkPartitionID.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/expressions/SparkPartitionID.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.execution.expressions import org.apache.spark.TaskContext -import org.apache.spark.sql.catalyst.expressions.{LeafExpression, Row} +import org.apache.spark.sql.catalyst.expressions.{LeafExpression, InternalRow} import org.apache.spark.sql.types.{IntegerType, DataType} @@ -31,5 +31,5 @@ private[sql] case object SparkPartitionID extends LeafExpression { override def dataType: DataType = IntegerType - override def eval(input: Row): Int = TaskContext.get().partitionId() + override def eval(input: InternalRow): Int = TaskContext.get().partitionId() } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala index b8b12be875..2d2e1b92b8 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala @@ -17,16 +17,15 @@ package org.apache.spark.sql.execution.joins -import org.apache.spark.rdd.RDD -import org.apache.spark.util.ThreadUtils - import scala.concurrent._ import scala.concurrent.duration._ import org.apache.spark.annotation.DeveloperApi -import org.apache.spark.sql.catalyst.expressions.{Row, Expression} +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.catalyst.expressions.{Expression, InternalRow} import org.apache.spark.sql.catalyst.plans.physical.{Distribution, Partitioning, UnspecifiedDistribution} import org.apache.spark.sql.execution.{BinaryNode, SparkPlan} +import org.apache.spark.util.ThreadUtils /** * :: DeveloperApi :: @@ -61,12 +60,12 @@ case class BroadcastHashJoin( @transient private val broadcastFuture = future { // Note that we use .execute().collect() because we don't want to convert data to Scala types - val input: Array[Row] = buildPlan.execute().map(_.copy()).collect() + val input: Array[InternalRow] = buildPlan.execute().map(_.copy()).collect() val hashed = HashedRelation(input.iterator, buildSideKeyGenerator, input.length) sparkContext.broadcast(hashed) }(BroadcastHashJoin.broadcastHashJoinExecutionContext) - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val broadcastRelation = Await.result(broadcastFuture, timeout) streamedPlan.execute().mapPartitions { streamedIter => diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastLeftSemiJoinHash.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastLeftSemiJoinHash.scala index a32e5fc4f7..044964f3a3 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastLeftSemiJoinHash.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastLeftSemiJoinHash.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.execution.joins import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.expressions.{Attribute, Expression, Row} +import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.execution.{BinaryNode, SparkPlan} /** @@ -38,10 +38,10 @@ case class BroadcastLeftSemiJoinHash( override def output: Seq[Attribute] = left.output - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val buildIter = buildPlan.execute().map(_.copy()).collect().toIterator - val hashSet = new java.util.HashSet[Row]() - var currentRow: Row = null + val hashSet = new java.util.HashSet[InternalRow]() + var currentRow: InternalRow = null // Create a Hash set of buildKeys while (buildIter.hasNext) { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastNestedLoopJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastNestedLoopJoin.scala index caad3dfbe1..0b2cf8e12a 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastNestedLoopJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastNestedLoopJoin.scala @@ -61,13 +61,14 @@ case class BroadcastNestedLoopJoin( @transient private lazy val boundCondition = newPredicate(condition.getOrElse(Literal(true)), left.output ++ right.output) - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val broadcastedRelation = - sparkContext.broadcast(broadcast.execute().map(_.copy()).collect().toIndexedSeq) + sparkContext.broadcast(broadcast.execute().map(_.copy()) + .collect().toIndexedSeq) /** All rows that either match both-way, or rows from streamed joined with nulls. */ val matchesOrStreamedRowsWithNulls = streamed.execute().mapPartitions { streamedIter => - val matchedRows = new CompactBuffer[Row] + val matchedRows = new CompactBuffer[InternalRow] // TODO: Use Spark's BitSet. val includedBroadcastTuples = new scala.collection.mutable.BitSet(broadcastedRelation.value.size) @@ -118,8 +119,8 @@ case class BroadcastNestedLoopJoin( val leftNulls = new GenericMutableRow(left.output.size) val rightNulls = new GenericMutableRow(right.output.size) /** Rows from broadcasted joined with nulls. */ - val broadcastRowsWithNulls: Seq[Row] = { - val buf: CompactBuffer[Row] = new CompactBuffer() + val broadcastRowsWithNulls: Seq[InternalRow] = { + val buf: CompactBuffer[InternalRow] = new CompactBuffer() var i = 0 val rel = broadcastedRelation.value while (i < rel.length) { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/CartesianProduct.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/CartesianProduct.scala index 191c00cb55..261b472415 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/CartesianProduct.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/CartesianProduct.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.execution.joins import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.{Attribute, JoinedRow} import org.apache.spark.sql.execution.{BinaryNode, SparkPlan} @@ -30,7 +30,7 @@ import org.apache.spark.sql.execution.{BinaryNode, SparkPlan} case class CartesianProduct(left: SparkPlan, right: SparkPlan) extends BinaryNode { override def output: Seq[Attribute] = left.output ++ right.output - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val leftResults = left.execute().map(_.copy()) val rightResults = right.execute().map(_.copy()) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashJoin.scala index 851de16855..3a4196a90d 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashJoin.scala @@ -49,11 +49,13 @@ trait HashJoin { @transient protected lazy val streamSideKeyGenerator: () => MutableProjection = newMutableProjection(streamedKeys, streamedPlan.output) - protected def hashJoin(streamIter: Iterator[Row], hashedRelation: HashedRelation): Iterator[Row] = + protected def hashJoin( + streamIter: Iterator[InternalRow], + hashedRelation: HashedRelation): Iterator[InternalRow] = { - new Iterator[Row] { - private[this] var currentStreamedRow: Row = _ - private[this] var currentHashMatches: CompactBuffer[Row] = _ + new Iterator[InternalRow] { + private[this] var currentStreamedRow: InternalRow = _ + private[this] var currentHashMatches: CompactBuffer[InternalRow] = _ private[this] var currentMatchPosition: Int = -1 // Mutable per row objects. @@ -65,7 +67,7 @@ trait HashJoin { (currentMatchPosition != -1 && currentMatchPosition < currentHashMatches.size) || (streamIter.hasNext && fetchNext()) - override final def next(): Row = { + override final def next(): InternalRow = { val ret = buildSide match { case BuildRight => joinRow(currentStreamedRow, currentHashMatches(currentMatchPosition)) case BuildLeft => joinRow(currentHashMatches(currentMatchPosition), currentStreamedRow) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashOuterJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashOuterJoin.scala index c21a453115..19aef9978e 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashOuterJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashOuterJoin.scala @@ -68,26 +68,29 @@ case class HashOuterJoin( } } - @transient private[this] lazy val DUMMY_LIST = Seq[Row](null) - @transient private[this] lazy val EMPTY_LIST = Seq.empty[Row] + @transient private[this] lazy val DUMMY_LIST = Seq[InternalRow](null) + @transient private[this] lazy val EMPTY_LIST = Seq.empty[InternalRow] @transient private[this] lazy val leftNullRow = new GenericRow(left.output.length) @transient private[this] lazy val rightNullRow = new GenericRow(right.output.length) @transient private[this] lazy val boundCondition = - condition.map(newPredicate(_, left.output ++ right.output)).getOrElse((row: Row) => true) + condition.map( + newPredicate(_, left.output ++ right.output)).getOrElse((row: InternalRow) => true) // TODO we need to rewrite all of the iterators with our own implementation instead of the Scala // iterator for performance purpose. private[this] def leftOuterIterator( - key: Row, joinedRow: JoinedRow, rightIter: Iterable[Row]): Iterator[Row] = { - val ret: Iterable[Row] = { + key: InternalRow, + joinedRow: JoinedRow, + rightIter: Iterable[InternalRow]): Iterator[InternalRow] = { + val ret: Iterable[InternalRow] = { if (!key.anyNull) { val temp = rightIter.collect { case r if boundCondition(joinedRow.withRight(r)) => joinedRow.copy() } if (temp.size == 0) { - joinedRow.withRight(rightNullRow).copy :: Nil + joinedRow.withRight(rightNullRow).copy.asInstanceOf[InternalRow] :: Nil } else { temp } @@ -99,12 +102,15 @@ case class HashOuterJoin( } private[this] def rightOuterIterator( - key: Row, leftIter: Iterable[Row], joinedRow: JoinedRow): Iterator[Row] = { + key: InternalRow, + leftIter: Iterable[InternalRow], + joinedRow: JoinedRow): Iterator[InternalRow] = { - val ret: Iterable[Row] = { + val ret: Iterable[InternalRow] = { if (!key.anyNull) { val temp = leftIter.collect { - case l if boundCondition(joinedRow.withLeft(l)) => joinedRow.copy + case l if boundCondition(joinedRow.withLeft(l)) => + joinedRow.copy } if (temp.size == 0) { joinedRow.withLeft(leftNullRow).copy :: Nil @@ -119,14 +125,14 @@ case class HashOuterJoin( } private[this] def fullOuterIterator( - key: Row, leftIter: Iterable[Row], rightIter: Iterable[Row], - joinedRow: JoinedRow): Iterator[Row] = { + key: InternalRow, leftIter: Iterable[InternalRow], rightIter: Iterable[InternalRow], + joinedRow: JoinedRow): Iterator[InternalRow] = { if (!key.anyNull) { // Store the positions of records in right, if one of its associated row satisfy // the join condition. val rightMatchedSet = scala.collection.mutable.Set[Int]() - leftIter.iterator.flatMap[Row] { l => + leftIter.iterator.flatMap[InternalRow] { l => joinedRow.withLeft(l) var matched = false rightIter.zipWithIndex.collect { @@ -157,24 +163,25 @@ case class HashOuterJoin( joinedRow(leftNullRow, r).copy() } } else { - leftIter.iterator.map[Row] { l => + leftIter.iterator.map[InternalRow] { l => joinedRow(l, rightNullRow).copy() - } ++ rightIter.iterator.map[Row] { r => + } ++ rightIter.iterator.map[InternalRow] { r => joinedRow(leftNullRow, r).copy() } } } private[this] def buildHashTable( - iter: Iterator[Row], keyGenerator: Projection): JavaHashMap[Row, CompactBuffer[Row]] = { - val hashTable = new JavaHashMap[Row, CompactBuffer[Row]]() + iter: Iterator[InternalRow], + keyGenerator: Projection): JavaHashMap[InternalRow, CompactBuffer[InternalRow]] = { + val hashTable = new JavaHashMap[InternalRow, CompactBuffer[InternalRow]]() while (iter.hasNext) { val currentRow = iter.next() val rowKey = keyGenerator(currentRow) var existingMatchList = hashTable.get(rowKey) if (existingMatchList == null) { - existingMatchList = new CompactBuffer[Row]() + existingMatchList = new CompactBuffer[InternalRow]() hashTable.put(rowKey, existingMatchList) } @@ -184,7 +191,7 @@ case class HashOuterJoin( hashTable } - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val joinedRow = new JoinedRow() left.execute().zipPartitions(right.execute()) { (leftIter, rightIter) => // TODO this probably can be replaced by external sort (sort merged join?) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashedRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashedRelation.scala index ab84c123e0..e18c817975 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashedRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashedRelation.scala @@ -20,7 +20,7 @@ package org.apache.spark.sql.execution.joins import java.io.{ObjectInput, ObjectOutput, Externalizable} import java.util.{HashMap => JavaHashMap} -import org.apache.spark.sql.catalyst.expressions.{Projection, Row} +import org.apache.spark.sql.catalyst.expressions.{Projection, InternalRow} import org.apache.spark.sql.execution.SparkSqlSerializer import org.apache.spark.util.collection.CompactBuffer @@ -30,7 +30,7 @@ import org.apache.spark.util.collection.CompactBuffer * object. */ private[joins] sealed trait HashedRelation { - def get(key: Row): CompactBuffer[Row] + def get(key: InternalRow): CompactBuffer[InternalRow] // This is a helper method to implement Externalizable, and is used by // GeneralHashedRelation and UniqueKeyHashedRelation @@ -54,12 +54,12 @@ private[joins] sealed trait HashedRelation { * A general [[HashedRelation]] backed by a hash map that maps the key into a sequence of values. */ private[joins] final class GeneralHashedRelation( - private var hashTable: JavaHashMap[Row, CompactBuffer[Row]]) + private var hashTable: JavaHashMap[InternalRow, CompactBuffer[InternalRow]]) extends HashedRelation with Externalizable { def this() = this(null) // Needed for serialization - override def get(key: Row): CompactBuffer[Row] = hashTable.get(key) + override def get(key: InternalRow): CompactBuffer[InternalRow] = hashTable.get(key) override def writeExternal(out: ObjectOutput): Unit = { writeBytes(out, SparkSqlSerializer.serialize(hashTable)) @@ -75,17 +75,18 @@ private[joins] final class GeneralHashedRelation( * A specialized [[HashedRelation]] that maps key into a single value. This implementation * assumes the key is unique. */ -private[joins] final class UniqueKeyHashedRelation(private var hashTable: JavaHashMap[Row, Row]) +private[joins] +final class UniqueKeyHashedRelation(private var hashTable: JavaHashMap[InternalRow, InternalRow]) extends HashedRelation with Externalizable { def this() = this(null) // Needed for serialization - override def get(key: Row): CompactBuffer[Row] = { + override def get(key: InternalRow): CompactBuffer[InternalRow] = { val v = hashTable.get(key) if (v eq null) null else CompactBuffer(v) } - def getValue(key: Row): Row = hashTable.get(key) + def getValue(key: InternalRow): InternalRow = hashTable.get(key) override def writeExternal(out: ObjectOutput): Unit = { writeBytes(out, SparkSqlSerializer.serialize(hashTable)) @@ -103,13 +104,13 @@ private[joins] final class UniqueKeyHashedRelation(private var hashTable: JavaHa private[joins] object HashedRelation { def apply( - input: Iterator[Row], + input: Iterator[InternalRow], keyGenerator: Projection, sizeEstimate: Int = 64): HashedRelation = { // TODO: Use Spark's HashMap implementation. - val hashTable = new JavaHashMap[Row, CompactBuffer[Row]](sizeEstimate) - var currentRow: Row = null + val hashTable = new JavaHashMap[InternalRow, CompactBuffer[InternalRow]](sizeEstimate) + var currentRow: InternalRow = null // Whether the join key is unique. If the key is unique, we can convert the underlying // hash map into one specialized for this. @@ -122,7 +123,7 @@ private[joins] object HashedRelation { if (!rowKey.anyNull) { val existingMatchList = hashTable.get(rowKey) val matchList = if (existingMatchList == null) { - val newMatchList = new CompactBuffer[Row]() + val newMatchList = new CompactBuffer[InternalRow]() hashTable.put(rowKey, newMatchList) newMatchList } else { @@ -134,7 +135,7 @@ private[joins] object HashedRelation { } if (keyIsUnique) { - val uniqHashTable = new JavaHashMap[Row, Row](hashTable.size) + val uniqHashTable = new JavaHashMap[InternalRow, InternalRow](hashTable.size) val iter = hashTable.entrySet().iterator() while (iter.hasNext) { val entry = iter.next() diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinBNL.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinBNL.scala index 036423e6fa..2a6d4d1ab0 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinBNL.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinBNL.scala @@ -47,7 +47,7 @@ case class LeftSemiJoinBNL( @transient private lazy val boundCondition = newPredicate(condition.getOrElse(Literal(true)), left.output ++ right.output) - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val broadcastedRelation = sparkContext.broadcast(broadcast.execute().map(_.copy()).collect().toIndexedSeq) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinHash.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinHash.scala index 8ad27eae80..20d74270af 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinHash.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinHash.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.execution.joins import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.expressions.{Attribute, Expression, Row} +import org.apache.spark.sql.catalyst.expressions.{Attribute, Expression, InternalRow} import org.apache.spark.sql.catalyst.plans.physical.ClusteredDistribution import org.apache.spark.sql.execution.{BinaryNode, SparkPlan} @@ -42,10 +42,10 @@ case class LeftSemiJoinHash( override def output: Seq[Attribute] = left.output - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { buildPlan.execute().zipPartitions(streamedPlan.execute()) { (buildIter, streamIter) => - val hashSet = new java.util.HashSet[Row]() - var currentRow: Row = null + val hashSet = new java.util.HashSet[InternalRow]() + var currentRow: InternalRow = null // Create a Hash set of buildKeys while (buildIter.hasNext) { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/ShuffledHashJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/ShuffledHashJoin.scala index 219525d9d8..5439e10a60 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/ShuffledHashJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/ShuffledHashJoin.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.execution.joins import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.Expression import org.apache.spark.sql.catalyst.plans.physical.{ClusteredDistribution, Partitioning} import org.apache.spark.sql.execution.{BinaryNode, SparkPlan} @@ -43,7 +43,7 @@ case class ShuffledHashJoin( override def requiredChildDistribution: Seq[ClusteredDistribution] = ClusteredDistribution(leftKeys) :: ClusteredDistribution(rightKeys) :: Nil - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { buildPlan.execute().zipPartitions(streamedPlan.execute()) { (buildIter, streamIter) => val hashed = HashedRelation(buildIter, buildSideKeyGenerator) hashJoin(streamIter, hashed) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala index 1a39fb4b96..2abe65a718 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala @@ -21,9 +21,7 @@ import java.util.NoSuchElementException import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD -import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.plans._ import org.apache.spark.sql.catalyst.plans.physical._ import org.apache.spark.sql.execution.{BinaryNode, SparkPlan} import org.apache.spark.util.collection.CompactBuffer @@ -60,29 +58,29 @@ case class SortMergeJoin( private def requiredOrders(keys: Seq[Expression]): Seq[SortOrder] = keys.map(SortOrder(_, Ascending)) - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val leftResults = left.execute().map(_.copy()) val rightResults = right.execute().map(_.copy()) leftResults.zipPartitions(rightResults) { (leftIter, rightIter) => - new Iterator[Row] { + new Iterator[InternalRow] { // Mutable per row objects. private[this] val joinRow = new JoinedRow5 - private[this] var leftElement: Row = _ - private[this] var rightElement: Row = _ - private[this] var leftKey: Row = _ - private[this] var rightKey: Row = _ - private[this] var rightMatches: CompactBuffer[Row] = _ + private[this] var leftElement: InternalRow = _ + private[this] var rightElement: InternalRow = _ + private[this] var leftKey: InternalRow = _ + private[this] var rightKey: InternalRow = _ + private[this] var rightMatches: CompactBuffer[InternalRow] = _ private[this] var rightPosition: Int = -1 private[this] var stop: Boolean = false - private[this] var matchKey: Row = _ + private[this] var matchKey: InternalRow = _ // initialize iterator initialize() override final def hasNext: Boolean = nextMatchingPair() - override final def next(): Row = { + override final def next(): InternalRow = { if (hasNext) { // we are using the buffered right rows and run down left iterator val joinedRow = joinRow(leftElement, rightMatches(rightPosition)) @@ -145,7 +143,7 @@ case class SortMergeJoin( fetchLeft() } } - rightMatches = new CompactBuffer[Row]() + rightMatches = new CompactBuffer[InternalRow]() if (stop) { stop = false // iterate the right side to buffer all rows that matches diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala index 2b45a83d14..1ce150ceaf 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala @@ -29,7 +29,8 @@ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.api.python.{PythonBroadcast, PythonRDD} import org.apache.spark.broadcast.Broadcast import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.expressions.{Row, _} +import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.catalyst.rules.Rule @@ -56,7 +57,7 @@ private[spark] case class PythonUDF( def nullable: Boolean = true - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { throw new UnsupportedOperationException("PythonUDFs can not be directly evaluated.") } } @@ -241,7 +242,7 @@ case class BatchPythonEvaluation(udf: PythonUDF, output: Seq[Attribute], child: def children: Seq[SparkPlan] = child :: Nil - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { val childResults = child.execute().map(_.copy()) val parent = childResults.mapPartitions { iter => @@ -276,7 +277,7 @@ case class BatchPythonEvaluation(udf: PythonUDF, output: Seq[Attribute], child: val row = new GenericMutableRow(1) iter.map { result => row(0) = EvaluatePython.fromJava(result, udf.dataType) - row: Row + row: InternalRow } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala index c41c21c0ee..8df1da037c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala @@ -20,9 +20,10 @@ package org.apache.spark.sql.execution.stat import scala.collection.mutable.{Map => MutableMap} import org.apache.spark.Logging -import org.apache.spark.sql.{Column, DataFrame, Row} +import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical.LocalRelation import org.apache.spark.sql.types.{ArrayType, StructField, StructType} +import org.apache.spark.sql.{Column, DataFrame} private[sql] object FrequentItems extends Logging { @@ -110,7 +111,7 @@ private[sql] object FrequentItems extends Logging { } ) val justItems = freqItems.map(m => m.baseMap.keys.toSeq) - val resultRow = Row(justItems : _*) + val resultRow = InternalRow(justItems : _*) // append frequent Items to the column name for easy debugging val outputCols = colInfo.map { v => StructField(v._1 + "_freqItems", ArrayType(v._2, false)) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRDD.scala index e75e6681c5..667fc70cff 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRDD.scala @@ -24,7 +24,7 @@ import org.apache.commons.lang3.StringUtils import org.apache.spark.{Logging, Partition, SparkContext, TaskContext} import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.expressions.{Row, SpecificMutableRow} +import org.apache.spark.sql.catalyst.expressions.{InternalRow, SpecificMutableRow} import org.apache.spark.sql.catalyst.util.DateUtils import org.apache.spark.sql.types._ import org.apache.spark.sql.sources._ @@ -211,7 +211,7 @@ private[sql] object JDBCRDD extends Logging { fqTable: String, requiredColumns: Array[String], filters: Array[Filter], - parts: Array[Partition]): RDD[Row] = { + parts: Array[Partition]): RDD[InternalRow] = { val dialect = JdbcDialects.get(url) val quotedColumns = requiredColumns.map(colName => dialect.quoteIdentifier(colName)) new JDBCRDD( @@ -240,7 +240,7 @@ private[sql] class JDBCRDD( filters: Array[Filter], partitions: Array[Partition], properties: Properties) - extends RDD[Row](sc, Nil) { + extends RDD[InternalRow](sc, Nil) { /** * Retrieve the list of partitions corresponding to this RDD. @@ -348,12 +348,12 @@ private[sql] class JDBCRDD( /** * Runs the SQL query against the JDBC driver. */ - override def compute(thePart: Partition, context: TaskContext): Iterator[Row] = new Iterator[Row] - { + override def compute(thePart: Partition, context: TaskContext): Iterator[InternalRow] = + new Iterator[InternalRow] { var closed = false var finished = false var gotNext = false - var nextValue: Row = null + var nextValue: InternalRow = null context.addTaskCompletionListener{ context => close() } val part = thePart.asInstanceOf[JDBCPartition] @@ -375,7 +375,7 @@ private[sql] class JDBCRDD( val conversions = getConversions(schema) val mutableRow = new SpecificMutableRow(schema.fields.map(x => x.dataType)) - def getNext(): Row = { + def getNext(): InternalRow = { if (rs.next()) { var i = 0 while (i < conversions.length) { @@ -443,7 +443,7 @@ private[sql] class JDBCRDD( mutableRow } else { finished = true - null.asInstanceOf[Row] + null.asInstanceOf[InternalRow] } } @@ -486,7 +486,7 @@ private[sql] class JDBCRDD( !finished } - override def next(): Row = { + override def next(): InternalRow = { if (!hasNext) { throw new NoSuchElementException("End of stream") } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRelation.scala index 30f9190d45..4d3aac464c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRelation.scala @@ -23,10 +23,9 @@ import scala.collection.mutable.ArrayBuffer import org.apache.spark.Partition import org.apache.spark.rdd.RDD -import org.apache.spark.sql.{SaveMode, DataFrame, SQLContext} -import org.apache.spark.sql.catalyst.expressions.Row import org.apache.spark.sql.sources._ import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.{DataFrame, Row, SQLContext, SaveMode} /** * Instructions on how to partition the table among workers. @@ -138,7 +137,7 @@ private[sql] case class JDBCRelation( table, requiredColumns, filters, - parts) + parts).map(_.asInstanceOf[Row]) } override def insert(data: DataFrame, overwrite: Boolean): Unit = { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala index c772cd1f53..69bf13e1e5 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala @@ -22,10 +22,10 @@ import java.io.IOException import org.apache.hadoop.fs.Path import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.expressions.{Expression, Attribute, Row} +import org.apache.spark.sql.catalyst.expressions.{Attribute, Expression} import org.apache.spark.sql.sources._ -import org.apache.spark.sql.types.{StructField, StructType} -import org.apache.spark.sql.{DataFrame, SQLContext, SaveMode} +import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.{DataFrame, Row, SQLContext, SaveMode} private[sql] class DefaultSource @@ -154,12 +154,12 @@ private[sql] class JSONRelation( JacksonParser( baseRDD(), schema, - sqlContext.conf.columnNameOfCorruptRecord) + sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row]) } else { JsonRDD.jsonStringToRow( baseRDD(), schema, - sqlContext.conf.columnNameOfCorruptRecord) + sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row]) } } @@ -168,12 +168,12 @@ private[sql] class JSONRelation( JacksonParser( baseRDD(), StructType.fromAttributes(requiredColumns), - sqlContext.conf.columnNameOfCorruptRecord) + sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row]) } else { JsonRDD.jsonStringToRow( baseRDD(), StructType.fromAttributes(requiredColumns), - sqlContext.conf.columnNameOfCorruptRecord) + sqlContext.conf.columnNameOfCorruptRecord).map(_.asInstanceOf[Row]) } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JacksonGenerator.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JacksonGenerator.scala index 325f54b680..1e6b1198d2 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JacksonGenerator.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JacksonGenerator.scala @@ -21,7 +21,7 @@ import scala.collection.Map import com.fasterxml.jackson.core._ -import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.Row import org.apache.spark.sql.types._ private[sql] object JacksonGenerator { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JacksonParser.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JacksonParser.scala index f16075ce58..817e8a20b3 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JacksonParser.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JacksonParser.scala @@ -35,7 +35,7 @@ private[sql] object JacksonParser { def apply( json: RDD[String], schema: StructType, - columnNameOfCorruptRecords: String): RDD[Row] = { + columnNameOfCorruptRecords: String): RDD[InternalRow] = { parseJson(json, schema, columnNameOfCorruptRecords) } @@ -130,7 +130,10 @@ private[sql] object JacksonParser { * * Fields in the json that are not defined in the requested schema will be dropped. */ - private def convertObject(factory: JsonFactory, parser: JsonParser, schema: StructType): Row = { + private def convertObject( + factory: JsonFactory, + parser: JsonParser, + schema: StructType): InternalRow = { val row = new GenericMutableRow(schema.length) while (nextUntil(parser, JsonToken.END_OBJECT)) { schema.getFieldIndex(parser.getCurrentName) match { @@ -176,9 +179,9 @@ private[sql] object JacksonParser { private def parseJson( json: RDD[String], schema: StructType, - columnNameOfCorruptRecords: String): RDD[Row] = { + columnNameOfCorruptRecords: String): RDD[InternalRow] = { - def failedRecord(record: String): Seq[Row] = { + def failedRecord(record: String): Seq[InternalRow] = { // create a row even if no corrupt record column is present val row = new GenericMutableRow(schema.length) for (corruptIndex <- schema.getFieldIndex(columnNameOfCorruptRecords)) { @@ -202,7 +205,7 @@ private[sql] object JacksonParser { // convertField wrap an object into a single value array when necessary. convertField(factory, parser, ArrayType(schema)) match { case null => failedRecord(record) - case list: Seq[Row @unchecked] => list + case list: Seq[InternalRow @unchecked] => list case _ => sys.error( s"Failed to parse record $record. Please make sure that each line of the file " + diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala index e4acf1ddaf..44594c5080 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala @@ -38,7 +38,7 @@ private[sql] object JsonRDD extends Logging { private[sql] def jsonStringToRow( json: RDD[String], schema: StructType, - columnNameOfCorruptRecords: String): RDD[Row] = { + columnNameOfCorruptRecords: String): RDD[InternalRow] = { parseJson(json, columnNameOfCorruptRecords).map(parsed => asRow(parsed, schema)) } @@ -434,7 +434,7 @@ private[sql] object JsonRDD extends Logging { } } - private def asRow(json: Map[String, Any], schema: StructType): Row = { + private def asRow(json: Map[String, Any], schema: StructType): InternalRow = { // TODO: Reuse the row instead of creating a new one for every record. val row = new GenericMutableRow(schema.fields.length) schema.fields.zipWithIndex.foreach { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala index ab9f878d1e..4da5e96b82 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala @@ -79,7 +79,7 @@ private[sql] object CatalystConverter { // TODO: consider using Array[T] for arrays to avoid boxing of primitive types type ArrayScalaType[T] = Seq[T] - type StructScalaType[T] = Row + type StructScalaType[T] = InternalRow type MapScalaType[K, V] = Map[K, V] protected[parquet] def createConverter( @@ -240,7 +240,7 @@ private[parquet] abstract class CatalystConverter extends GroupConverter { * * @return */ - def getCurrentRecord: Row = throw new UnsupportedOperationException + def getCurrentRecord: InternalRow = throw new UnsupportedOperationException /** * Read a decimal value from a Parquet Binary into "dest". Only supports decimals that fit in @@ -275,7 +275,7 @@ private[parquet] abstract class CatalystConverter extends GroupConverter { /** * A `parquet.io.api.GroupConverter` that is able to convert a Parquet record - * to a [[org.apache.spark.sql.catalyst.expressions.Row]] object. + * to a [[org.apache.spark.sql.catalyst.expressions.InternalRow]] object. * * @param schema The corresponding Catalyst schema in the form of a list of attributes. */ @@ -284,7 +284,7 @@ private[parquet] class CatalystGroupConverter( protected[parquet] val index: Int, protected[parquet] val parent: CatalystConverter, protected[parquet] var current: ArrayBuffer[Any], - protected[parquet] var buffer: ArrayBuffer[Row]) + protected[parquet] var buffer: ArrayBuffer[InternalRow]) extends CatalystConverter { def this(schema: Array[FieldType], index: Int, parent: CatalystConverter) = @@ -293,7 +293,7 @@ private[parquet] class CatalystGroupConverter( index, parent, current = null, - buffer = new ArrayBuffer[Row]( + buffer = new ArrayBuffer[InternalRow]( CatalystArrayConverter.INITIAL_ARRAY_SIZE)) /** @@ -309,7 +309,7 @@ private[parquet] class CatalystGroupConverter( override val size = schema.size - override def getCurrentRecord: Row = { + override def getCurrentRecord: InternalRow = { assert(isRootConverter, "getCurrentRecord should only be called in root group converter!") // TODO: use iterators if possible // Note: this will ever only be called in the root converter when the record has been @@ -347,7 +347,7 @@ private[parquet] class CatalystGroupConverter( /** * A `parquet.io.api.GroupConverter` that is able to convert a Parquet record - * to a [[org.apache.spark.sql.catalyst.expressions.Row]] object. Note that his + * to a [[org.apache.spark.sql.catalyst.expressions.InternalRow]] object. Note that his * converter is optimized for rows of primitive types (non-nested records). */ private[parquet] class CatalystPrimitiveRowConverter( @@ -373,7 +373,7 @@ private[parquet] class CatalystPrimitiveRowConverter( override val parent = null // Should be only called in root group converter! - override def getCurrentRecord: Row = current + override def getCurrentRecord: InternalRow = current override def getConverter(fieldIndex: Int): Converter = converters(fieldIndex) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala index 272608d4e2..39360e1331 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala @@ -46,7 +46,7 @@ import org.apache.spark.mapred.SparkHadoopMapRedUtil import org.apache.spark.mapreduce.SparkHadoopMapReduceUtil import org.apache.spark.rdd.RDD import org.apache.spark.sql.SQLConf -import org.apache.spark.sql.catalyst.expressions.{Attribute, Expression, Row, _} +import org.apache.spark.sql.catalyst.expressions.{Attribute, Expression, InternalRow, _} import org.apache.spark.sql.execution.{LeafNode, SparkPlan, UnaryNode} import org.apache.spark.sql.types.StructType import org.apache.spark.{Logging, SerializableWritable, TaskContext} @@ -54,7 +54,7 @@ import org.apache.spark.{Logging, SerializableWritable, TaskContext} /** * :: DeveloperApi :: * Parquet table scan operator. Imports the file that backs the given - * [[org.apache.spark.sql.parquet.ParquetRelation]] as a ``RDD[Row]``. + * [[org.apache.spark.sql.parquet.ParquetRelation]] as a ``RDD[InternalRow]``. */ private[sql] case class ParquetTableScan( attributes: Seq[Attribute], @@ -77,7 +77,7 @@ private[sql] case class ParquetTableScan( } }.toArray - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { import org.apache.parquet.filter2.compat.FilterCompat.FilterPredicateCompat val sc = sqlContext.sparkContext @@ -125,7 +125,7 @@ private[sql] case class ParquetTableScan( sc, classOf[FilteringParquetRowInputFormat], classOf[Void], - classOf[Row], + classOf[InternalRow], conf) if (requestedPartitionOrdinals.nonEmpty) { @@ -154,9 +154,9 @@ private[sql] case class ParquetTableScan( .map(a => Cast(Literal(partValues(a.name)), a.dataType).eval(EmptyRow)) if (primitiveRow) { - new Iterator[Row] { + new Iterator[InternalRow] { def hasNext: Boolean = iter.hasNext - def next(): Row = { + def next(): InternalRow = { // We are using CatalystPrimitiveRowConverter and it returns a SpecificMutableRow. val row = iter.next()._2.asInstanceOf[SpecificMutableRow] @@ -173,12 +173,12 @@ private[sql] case class ParquetTableScan( } else { // Create a mutable row since we need to fill in values from partition columns. val mutableRow = new GenericMutableRow(outputSize) - new Iterator[Row] { + new Iterator[InternalRow] { def hasNext: Boolean = iter.hasNext - def next(): Row = { + def next(): InternalRow = { // We are using CatalystGroupConverter and it returns a GenericRow. // Since GenericRow is not mutable, we just cast it to a Row. - val row = iter.next()._2.asInstanceOf[Row] + val row = iter.next()._2.asInstanceOf[InternalRow] var i = 0 while (i < row.size) { @@ -258,7 +258,7 @@ private[sql] case class InsertIntoParquetTable( /** * Inserts all rows into the Parquet file. */ - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { // TODO: currently we do not check whether the "schema"s are compatible // That means if one first creates a table and then INSERTs data with // and incompatible schema the execution will fail. It would be nice @@ -321,13 +321,13 @@ private[sql] case class InsertIntoParquetTable( * @param conf A [[org.apache.hadoop.conf.Configuration]]. */ private def saveAsHadoopFile( - rdd: RDD[Row], + rdd: RDD[InternalRow], path: String, conf: Configuration) { val job = new Job(conf) val keyType = classOf[Void] job.setOutputKeyClass(keyType) - job.setOutputValueClass(classOf[Row]) + job.setOutputValueClass(classOf[InternalRow]) NewFileOutputFormat.setOutputPath(job, new Path(path)) val wrappedConf = new SerializableWritable(job.getConfiguration) val formatter = new SimpleDateFormat("yyyyMMddHHmm") @@ -342,7 +342,7 @@ private[sql] case class InsertIntoParquetTable( .findMaxTaskId(NewFileOutputFormat.getOutputPath(job).toString, job.getConfiguration) + 1 } - def writeShard(context: TaskContext, iter: Iterator[Row]): Int = { + def writeShard(context: TaskContext, iter: Iterator[InternalRow]): Int = { /* "reduce task" <split #> <attempt # = spark task #> */ val attemptId = newTaskAttemptID(jobtrackerID, stageId, isMap = false, context.partitionId, context.attemptNumber) @@ -381,7 +381,7 @@ private[sql] case class InsertIntoParquetTable( * to imported ones. */ private[parquet] class AppendingParquetOutputFormat(offset: Int) - extends org.apache.parquet.hadoop.ParquetOutputFormat[Row] { + extends org.apache.parquet.hadoop.ParquetOutputFormat[InternalRow] { // override to accept existing directories as valid output directory override def checkOutputSpecs(job: JobContext): Unit = {} var committer: OutputCommitter = null @@ -434,25 +434,25 @@ private[parquet] class AppendingParquetOutputFormat(offset: Int) * RecordFilter we want to use. */ private[parquet] class FilteringParquetRowInputFormat - extends org.apache.parquet.hadoop.ParquetInputFormat[Row] with Logging { + extends org.apache.parquet.hadoop.ParquetInputFormat[InternalRow] with Logging { private var fileStatuses = Map.empty[Path, FileStatus] override def createRecordReader( inputSplit: InputSplit, - taskAttemptContext: TaskAttemptContext): RecordReader[Void, Row] = { + taskAttemptContext: TaskAttemptContext): RecordReader[Void, InternalRow] = { import org.apache.parquet.filter2.compat.FilterCompat.NoOpFilter - val readSupport: ReadSupport[Row] = new RowReadSupport() + val readSupport: ReadSupport[InternalRow] = new RowReadSupport() val filter = ParquetInputFormat.getFilter(ContextUtil.getConfiguration(taskAttemptContext)) if (!filter.isInstanceOf[NoOpFilter]) { - new ParquetRecordReader[Row]( + new ParquetRecordReader[InternalRow]( readSupport, filter) } else { - new ParquetRecordReader[Row](readSupport) + new ParquetRecordReader[InternalRow](readSupport) } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala index c62c592b3f..a8775a2a8f 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala @@ -28,7 +28,7 @@ import org.apache.parquet.io.api._ import org.apache.parquet.schema.MessageType import org.apache.spark.Logging -import org.apache.spark.sql.catalyst.expressions.{Attribute, Row} +import org.apache.spark.sql.catalyst.expressions.{Attribute, InternalRow} import org.apache.spark.sql.catalyst.util.DateUtils import org.apache.spark.sql.types._ import org.apache.spark.unsafe.types.UTF8String @@ -39,12 +39,12 @@ import org.apache.spark.unsafe.types.UTF8String *@param root The root group converter for the record. */ private[parquet] class RowRecordMaterializer(root: CatalystConverter) - extends RecordMaterializer[Row] { + extends RecordMaterializer[InternalRow] { def this(parquetSchema: MessageType, attributes: Seq[Attribute]) = this(CatalystConverter.createRootConverter(parquetSchema, attributes)) - override def getCurrentRecord: Row = root.getCurrentRecord + override def getCurrentRecord: InternalRow = root.getCurrentRecord override def getRootConverter: GroupConverter = root.asInstanceOf[GroupConverter] } @@ -52,13 +52,13 @@ private[parquet] class RowRecordMaterializer(root: CatalystConverter) /** * A `parquet.hadoop.api.ReadSupport` for Row objects. */ -private[parquet] class RowReadSupport extends ReadSupport[Row] with Logging { +private[parquet] class RowReadSupport extends ReadSupport[InternalRow] with Logging { override def prepareForRead( conf: Configuration, stringMap: java.util.Map[String, String], fileSchema: MessageType, - readContext: ReadContext): RecordMaterializer[Row] = { + readContext: ReadContext): RecordMaterializer[InternalRow] = { log.debug(s"preparing for read with Parquet file schema $fileSchema") // Note: this very much imitates AvroParquet val parquetSchema = readContext.getRequestedSchema @@ -133,7 +133,7 @@ private[parquet] object RowReadSupport { /** * A `parquet.hadoop.api.WriteSupport` for Row objects. */ -private[parquet] class RowWriteSupport extends WriteSupport[Row] with Logging { +private[parquet] class RowWriteSupport extends WriteSupport[InternalRow] with Logging { private[parquet] var writer: RecordConsumer = null private[parquet] var attributes: Array[Attribute] = null @@ -157,7 +157,7 @@ private[parquet] class RowWriteSupport extends WriteSupport[Row] with Logging { log.debug(s"preparing for write with schema $attributes") } - override def write(record: Row): Unit = { + override def write(record: InternalRow): Unit = { val attributesSize = attributes.size if (attributesSize > record.size) { throw new IndexOutOfBoundsException( @@ -322,7 +322,7 @@ private[parquet] class RowWriteSupport extends WriteSupport[Row] with Logging { // Optimized for non-nested rows private[parquet] class MutableRowWriteSupport extends RowWriteSupport { - override def write(record: Row): Unit = { + override def write(record: InternalRow): Unit = { val attributesSize = attributes.size if (attributesSize > record.size) { throw new IndexOutOfBoundsException( @@ -345,7 +345,7 @@ private[parquet] class MutableRowWriteSupport extends RowWriteSupport { private def consumeType( ctype: DataType, - record: Row, + record: InternalRow, index: Int): Unit = { ctype match { case StringType => writer.addBinary( diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala index 7af4eb1ca4..bc27a9b67a 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala @@ -34,15 +34,15 @@ import org.apache.parquet.hadoop._ import org.apache.parquet.hadoop.metadata.CompressionCodecName import org.apache.parquet.hadoop.util.ContextUtil +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.{Partition => SparkPartition, SerializableWritable, Logging, SparkException} import org.apache.spark.broadcast.Broadcast import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.rdd.RDD._ import org.apache.spark.rdd.RDD -import org.apache.spark.sql.AnalysisException +import org.apache.spark.sql._ import org.apache.spark.sql.sources._ import org.apache.spark.sql.types.{DataType, StructType} -import org.apache.spark.sql.{Row, SQLConf, SQLContext} import org.apache.spark.util.Utils private[sql] class DefaultSource extends HadoopFsRelationProvider { @@ -60,7 +60,7 @@ private[sql] class DefaultSource extends HadoopFsRelationProvider { private[sql] class ParquetOutputWriter(path: String, context: TaskAttemptContext) extends OutputWriter { - private val recordWriter: RecordWriter[Void, Row] = { + private val recordWriter: RecordWriter[Void, InternalRow] = { val conf = context.getConfiguration val outputFormat = { // When appending new Parquet files to an existing Parquet file directory, to avoid @@ -93,7 +93,7 @@ private[sql] class ParquetOutputWriter(path: String, context: TaskAttemptContext } } - new ParquetOutputFormat[Row]() { + new ParquetOutputFormat[InternalRow]() { // Here we override `getDefaultWorkFile` for two reasons: // // 1. To allow appending. We need to generate output file name based on the max available @@ -112,7 +112,7 @@ private[sql] class ParquetOutputWriter(path: String, context: TaskAttemptContext outputFormat.getRecordWriter(context) } - override def write(row: Row): Unit = recordWriter.write(null, row) + override def write(row: Row): Unit = recordWriter.write(null, row.asInstanceOf[InternalRow]) override def close(): Unit = recordWriter.close(context) } @@ -286,7 +286,7 @@ private[sql] class ParquetRelation2( initLocalJobFuncOpt = Some(initLocalJobFuncOpt), inputFormatClass = classOf[FilteringParquetRowInputFormat], keyClass = classOf[Void], - valueClass = classOf[Row]) { + valueClass = classOf[InternalRow]) { val cacheMetadata = useMetadataCache @@ -331,7 +331,7 @@ private[sql] class ParquetRelation2( new SqlNewHadoopPartition(id, i, rawSplits(i).asInstanceOf[InputSplit with Writable]) } } - }.values + }.values.map(_.asInstanceOf[Row]) } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/DataSourceStrategy.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/DataSourceStrategy.scala index edda3f2017..4cf67439b9 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/DataSourceStrategy.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/DataSourceStrategy.scala @@ -17,48 +17,48 @@ package org.apache.spark.sql.sources -import org.apache.spark.{Logging, SerializableWritable, TaskContext} import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.rdd.{MapPartitionsRDD, RDD, UnionRDD} +import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.planning.PhysicalOperation import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan -import org.apache.spark.sql.execution.SparkPlan import org.apache.spark.sql.types.{StringType, StructType} import org.apache.spark.sql.{SaveMode, Strategy, execution, sources} import org.apache.spark.util.Utils import org.apache.spark.unsafe.types.UTF8String +import org.apache.spark.{Logging, SerializableWritable, TaskContext} /** * A Strategy for planning scans over data sources defined using the sources API. */ private[sql] object DataSourceStrategy extends Strategy with Logging { def apply(plan: LogicalPlan): Seq[execution.SparkPlan] = plan match { - case PhysicalOperation(projectList, filters, l @ LogicalRelation(t: CatalystScan)) => + case PhysicalOperation(projects, filters, l @ LogicalRelation(t: CatalystScan)) => pruneFilterProjectRaw( l, - projectList, + projects, filters, - (a, f) => t.buildScan(a, f)) :: Nil + (a, f) => toCatalystRDD(l, a, t.buildScan(a, f))) :: Nil - case PhysicalOperation(projectList, filters, l @ LogicalRelation(t: PrunedFilteredScan)) => + case PhysicalOperation(projects, filters, l @ LogicalRelation(t: PrunedFilteredScan)) => pruneFilterProject( l, - projectList, + projects, filters, - (a, f) => t.buildScan(a, f)) :: Nil + (a, f) => toCatalystRDD(l, a, t.buildScan(a.map(_.name).toArray, f))) :: Nil - case PhysicalOperation(projectList, filters, l @ LogicalRelation(t: PrunedScan)) => + case PhysicalOperation(projects, filters, l @ LogicalRelation(t: PrunedScan)) => pruneFilterProject( l, - projectList, + projects, filters, - (a, _) => t.buildScan(a)) :: Nil + (a, _) => toCatalystRDD(l, a, t.buildScan(a.map(_.name).toArray))) :: Nil // Scanning partitioned HadoopFsRelation - case PhysicalOperation(projectList, filters, l @ LogicalRelation(t: HadoopFsRelation)) + case PhysicalOperation(projects, filters, l @ LogicalRelation(t: HadoopFsRelation)) if t.partitionSpec.partitionColumns.nonEmpty => val selectedPartitions = prunePartitions(filters, t.partitionSpec).toArray @@ -80,13 +80,13 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { buildPartitionedTableScan( l, - projectList, + projects, pushedFilters, t.partitionSpec.partitionColumns, selectedPartitions) :: Nil // Scanning non-partitioned HadoopFsRelation - case PhysicalOperation(projectList, filters, l @ LogicalRelation(t: HadoopFsRelation)) => + case PhysicalOperation(projects, filters, l @ LogicalRelation(t: HadoopFsRelation)) => // See buildPartitionedTableScan for the reason that we need to create a shard // broadcast HadoopConf. val sharedHadoopConf = SparkHadoopUtil.get.conf @@ -94,12 +94,13 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { t.sqlContext.sparkContext.broadcast(new SerializableWritable(sharedHadoopConf)) pruneFilterProject( l, - projectList, + projects, filters, - (a, f) => t.buildScan(a, f, t.paths, confBroadcast)) :: Nil + (a, f) => + toCatalystRDD(l, a, t.buildScan(a.map(_.name).toArray, f, t.paths, confBroadcast))) :: Nil case l @ LogicalRelation(t: TableScan) => - createPhysicalRDD(l.relation, l.output, t.buildScan()) :: Nil + execution.PhysicalRDD(l.output, toCatalystRDD(l, t.buildScan())) :: Nil case i @ logical.InsertIntoTable( l @ LogicalRelation(t: InsertableRelation), part, query, overwrite, false) if part.isEmpty => @@ -119,7 +120,6 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { filters: Seq[Expression], partitionColumns: StructType, partitions: Array[Partition]) = { - val output = projections.map(_.toAttribute) val relation = logicalRelation.relation.asInstanceOf[HadoopFsRelation] // Because we are creating one RDD per partition, we need to have a shared HadoopConf. @@ -138,23 +138,23 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { logicalRelation, projections, filters, - (requiredColumns, filters) => { + (columns: Seq[Attribute], filters) => { val partitionColNames = partitionColumns.fieldNames // Don't scan any partition columns to save I/O. Here we are being optimistic and // assuming partition columns data stored in data files are always consistent with those // partition values encoded in partition directory paths. - val nonPartitionColumns = requiredColumns.filterNot(partitionColNames.contains) + val needed = columns.filterNot(a => partitionColNames.contains(a.name)) val dataRows = - relation.buildScan(nonPartitionColumns, filters, Array(dir), confBroadcast) + relation.buildScan(needed.map(_.name).toArray, filters, Array(dir), confBroadcast) // Merges data values with partition values. mergeWithPartitionValues( relation.schema, - requiredColumns, + columns.map(_.name).toArray, partitionColNames, partitionValues, - dataRows) + toCatalystRDD(logicalRelation, needed, dataRows)) }) scan.execute() @@ -167,15 +167,15 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { new UnionRDD(relation.sqlContext.sparkContext, perPartitionRows) } - createPhysicalRDD(logicalRelation.relation, output, unionedRows) + execution.PhysicalRDD(projections.map(_.toAttribute), unionedRows) } private def mergeWithPartitionValues( schema: StructType, requiredColumns: Array[String], partitionColumns: Array[String], - partitionValues: Row, - dataRows: RDD[Row]): RDD[Row] = { + partitionValues: InternalRow, + dataRows: RDD[InternalRow]): RDD[InternalRow] = { val nonPartitionColumns = requiredColumns.filterNot(partitionColumns.contains) // If output columns contain any partition column(s), we need to merge scanned data @@ -186,13 +186,13 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { val i = partitionColumns.indexOf(name) if (i != -1) { // If yes, gets column value from partition values. - (mutableRow: MutableRow, dataRow: expressions.Row, ordinal: Int) => { + (mutableRow: MutableRow, dataRow: InternalRow, ordinal: Int) => { mutableRow(ordinal) = partitionValues(i) } } else { // Otherwise, inherits the value from scanned data. val i = nonPartitionColumns.indexOf(name) - (mutableRow: MutableRow, dataRow: expressions.Row, ordinal: Int) => { + (mutableRow: MutableRow, dataRow: InternalRow, ordinal: Int) => { mutableRow(ordinal) = dataRow(i) } } @@ -201,7 +201,7 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { // Since we know for sure that this closure is serializable, we can avoid the overhead // of cleaning a closure for each RDD by creating our own MapPartitionsRDD. Functionally // this is equivalent to calling `dataRows.mapPartitions(mapPartitionsFunc)` (SPARK-7718). - val mapPartitionsFunc = (_: TaskContext, _: Int, iterator: Iterator[Row]) => { + val mapPartitionsFunc = (_: TaskContext, _: Int, iterator: Iterator[InternalRow]) => { val dataTypes = requiredColumns.map(schema(_).dataType) val mutableRow = new SpecificMutableRow(dataTypes) iterator.map { dataRow => @@ -210,7 +210,7 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { mergers(i)(mutableRow, dataRow, i) i += 1 } - mutableRow.asInstanceOf[expressions.Row] + mutableRow.asInstanceOf[InternalRow] } } @@ -256,26 +256,26 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { // Based on Public API. protected def pruneFilterProject( relation: LogicalRelation, - projectList: Seq[NamedExpression], + projects: Seq[NamedExpression], filterPredicates: Seq[Expression], - scanBuilder: (Array[String], Array[Filter]) => RDD[Row]) = { + scanBuilder: (Seq[Attribute], Array[Filter]) => RDD[InternalRow]) = { pruneFilterProjectRaw( relation, - projectList, + projects, filterPredicates, (requestedColumns, pushedFilters) => { - scanBuilder(requestedColumns.map(_.name).toArray, selectFilters(pushedFilters).toArray) + scanBuilder(requestedColumns, selectFilters(pushedFilters).toArray) }) } // Based on Catalyst expressions. protected def pruneFilterProjectRaw( relation: LogicalRelation, - projectList: Seq[NamedExpression], + projects: Seq[NamedExpression], filterPredicates: Seq[Expression], - scanBuilder: (Seq[Attribute], Seq[Expression]) => RDD[Row]) = { + scanBuilder: (Seq[Attribute], Seq[Expression]) => RDD[InternalRow]) = { - val projectSet = AttributeSet(projectList.flatMap(_.references)) + val projectSet = AttributeSet(projects.flatMap(_.references)) val filterSet = AttributeSet(filterPredicates.flatMap(_.references)) val filterCondition = filterPredicates.reduceLeftOption(expressions.And) @@ -283,38 +283,47 @@ private[sql] object DataSourceStrategy extends Strategy with Logging { case a: AttributeReference => relation.attributeMap(a) // Match original case of attributes. }} - if (projectList.map(_.toAttribute) == projectList && - projectSet.size == projectList.size && + if (projects.map(_.toAttribute) == projects && + projectSet.size == projects.size && filterSet.subsetOf(projectSet)) { // When it is possible to just use column pruning to get the right projection and // when the columns of this projection are enough to evaluate all filter conditions, // just do a scan followed by a filter, with no extra project. val requestedColumns = - projectList.asInstanceOf[Seq[Attribute]] // Safe due to if above. + projects.asInstanceOf[Seq[Attribute]] // Safe due to if above. .map(relation.attributeMap) // Match original case of attributes. - val scan = createPhysicalRDD(relation.relation, projectList.map(_.toAttribute), - scanBuilder(requestedColumns, pushedFilters)) + val scan = execution.PhysicalRDD(projects.map(_.toAttribute), + scanBuilder(requestedColumns, pushedFilters)) filterCondition.map(execution.Filter(_, scan)).getOrElse(scan) } else { val requestedColumns = (projectSet ++ filterSet).map(relation.attributeMap).toSeq - val scan = createPhysicalRDD(relation.relation, requestedColumns, + val scan = execution.PhysicalRDD(requestedColumns, scanBuilder(requestedColumns, pushedFilters)) - execution.Project(projectList, filterCondition.map(execution.Filter(_, scan)).getOrElse(scan)) + execution.Project(projects, filterCondition.map(execution.Filter(_, scan)).getOrElse(scan)) } } - private[this] def createPhysicalRDD( - relation: BaseRelation, + /** + * Convert RDD of Row into RDD of InternalRow with objects in catalyst types + */ + private[this] def toCatalystRDD( + relation: LogicalRelation, output: Seq[Attribute], - rdd: RDD[Row]): SparkPlan = { - val converted = if (relation.needConversion) { - execution.RDDConversions.rowToRowRdd(rdd, output.map(_.dataType)) + rdd: RDD[Row]): RDD[InternalRow] = { + if (relation.relation.needConversion) { + execution.RDDConversions.rowToRowRdd(rdd.asInstanceOf[RDD[Row]], output.map(_.dataType)) } else { - rdd + rdd.map(_.asInstanceOf[InternalRow]) } - execution.PhysicalRDD(output, converted) + } + + /** + * Convert RDD of Row into RDD of InternalRow with objects in catalyst types + */ + private[this] def toCatalystRDD(relation: LogicalRelation, rdd: RDD[Row]): RDD[InternalRow] = { + toCatalystRDD(relation, relation.output, rdd) } /** diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/PartitioningUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/PartitioningUtils.scala index 7a2b5b949d..c6f535dde7 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/PartitioningUtils.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/PartitioningUtils.scala @@ -25,12 +25,11 @@ import scala.util.Try import org.apache.hadoop.fs.Path import org.apache.hadoop.util.Shell - -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.{Cast, Literal} import org.apache.spark.sql.types._ -private[sql] case class Partition(values: Row, path: String) +private[sql] case class Partition(values: InternalRow, path: String) private[sql] case class PartitionSpec(partitionColumns: StructType, partitions: Seq[Partition]) @@ -100,7 +99,7 @@ private[sql] object PartitioningUtils { // Finally, we create `Partition`s based on paths and resolved partition values. val partitions = resolvedPartitionValues.zip(pathsWithPartitionValues).map { case (PartitionValues(_, literals), (path, _)) => - Partition(Row.fromSeq(literals.map(_.value)), path.toString) + Partition(InternalRow.fromSeq(literals.map(_.value)), path.toString) } PartitionSpec(StructType(fields), partitions) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/commands.scala index c94199bfcd..1763cee419 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/commands.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/commands.scala @@ -36,7 +36,7 @@ import org.apache.spark.sql.catalyst.expressions.codegen.GenerateProjection import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Project} import org.apache.spark.sql.execution.RunnableCommand import org.apache.spark.sql.types.StructType -import org.apache.spark.sql.{DataFrame, SQLConf, SQLContext, SaveMode} +import org.apache.spark.sql.{DataFrame, Row, SQLConf, SQLContext, SaveMode} private[sql] case class InsertIntoDataSource( logicalRelation: LogicalRelation, @@ -44,18 +44,17 @@ private[sql] case class InsertIntoDataSource( overwrite: Boolean) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { val relation = logicalRelation.relation.asInstanceOf[InsertableRelation] val data = DataFrame(sqlContext, query) // Apply the schema of the existing table to the new data. - val df = sqlContext.createDataFrame( - data.queryExecution.toRdd, logicalRelation.schema, needsConversion = false) + val df = sqlContext.internalCreateDataFrame(data.queryExecution.toRdd, logicalRelation.schema) relation.insert(df, overwrite) // Invalidate the cache. sqlContext.cacheManager.invalidateCache(logicalRelation) - Seq.empty[Row] + Seq.empty[InternalRow] } } @@ -65,7 +64,7 @@ private[sql] case class InsertIntoHadoopFsRelation( mode: SaveMode) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { require( relation.paths.length == 1, s"Cannot write to multiple destinations: ${relation.paths.mkString(",")}") @@ -90,7 +89,7 @@ private[sql] case class InsertIntoHadoopFsRelation( if (doInsertion) { val job = new Job(hadoopConf) job.setOutputKeyClass(classOf[Void]) - job.setOutputValueClass(classOf[Row]) + job.setOutputValueClass(classOf[InternalRow]) FileOutputFormat.setOutputPath(job, qualifiedOutputPath) // We create a DataFrame by applying the schema of relation to the data to make sure. @@ -103,10 +102,8 @@ private[sql] case class InsertIntoHadoopFsRelation( val project = Project( relation.schema.map(field => new UnresolvedAttribute(Seq(field.name))), query) - sqlContext.createDataFrame( - DataFrame(sqlContext, project).queryExecution.toRdd, - relation.schema, - needsConversion = false) + sqlContext.internalCreateDataFrame( + DataFrame(sqlContext, project).queryExecution.toRdd, relation.schema) } val partitionColumns = relation.partitionColumns.fieldNames @@ -119,7 +116,7 @@ private[sql] case class InsertIntoHadoopFsRelation( } } - Seq.empty[Row] + Seq.empty[InternalRow] } private def insert(writerContainer: BaseWriterContainer, df: DataFrame): Unit = { @@ -141,22 +138,19 @@ private[sql] case class InsertIntoHadoopFsRelation( throw new SparkException("Job aborted.", cause) } - def writeRows(taskContext: TaskContext, iterator: Iterator[Row]): Unit = { + def writeRows(taskContext: TaskContext, iterator: Iterator[InternalRow]): Unit = { // If anything below fails, we should abort the task. try { writerContainer.executorSideSetup(taskContext) - if (needsConversion) { - val converter = CatalystTypeConverters.createToScalaConverter(dataSchema) - while (iterator.hasNext) { - val row = converter(iterator.next()).asInstanceOf[Row] - writerContainer.outputWriterForRow(row).write(row) - } + val converter = if (needsConversion) { + CatalystTypeConverters.createToScalaConverter(dataSchema).asInstanceOf[InternalRow => Row] } else { - while (iterator.hasNext) { - val row = iterator.next() - writerContainer.outputWriterForRow(row).write(row) - } + r: InternalRow => r.asInstanceOf[Row] + } + while (iterator.hasNext) { + val row = converter(iterator.next()) + writerContainer.outputWriterForRow(row).write(row) } writerContainer.commitTask() @@ -210,32 +204,28 @@ private[sql] case class InsertIntoHadoopFsRelation( throw new SparkException("Job aborted.", cause) } - def writeRows(taskContext: TaskContext, iterator: Iterator[Row]): Unit = { + def writeRows(taskContext: TaskContext, iterator: Iterator[InternalRow]): Unit = { // If anything below fails, we should abort the task. try { writerContainer.executorSideSetup(taskContext) val partitionProj = newProjection(codegenEnabled, partitionOutput, output) val dataProj = newProjection(codegenEnabled, dataOutput, output) - - if (needsConversion) { - val converter = CatalystTypeConverters.createToScalaConverter(dataSchema) - while (iterator.hasNext) { - val row = iterator.next() - val partitionPart = partitionProj(row) - val dataPart = dataProj(row) - val convertedDataPart = converter(dataPart).asInstanceOf[Row] - writerContainer.outputWriterForRow(partitionPart).write(convertedDataPart) - } + val dataConverter: InternalRow => Row = if (needsConversion) { + CatalystTypeConverters.createToScalaConverter(dataSchema).asInstanceOf[InternalRow => Row] } else { - val partitionSchema = StructType.fromAttributes(partitionOutput) - val converter = CatalystTypeConverters.createToScalaConverter(partitionSchema) - while (iterator.hasNext) { - val row = iterator.next() - val partitionPart = converter(partitionProj(row)).asInstanceOf[Row] - val dataPart = dataProj(row) - writerContainer.outputWriterForRow(partitionPart).write(dataPart) - } + r: InternalRow => r.asInstanceOf[Row] + } + val partitionSchema = StructType.fromAttributes(partitionOutput) + val partConverter: InternalRow => Row = + CatalystTypeConverters.createToScalaConverter(partitionSchema) + .asInstanceOf[InternalRow => Row] + + while (iterator.hasNext) { + val row = iterator.next() + val partitionPart = partConverter(partitionProj(row)) + val dataPart = dataConverter(dataProj(row)) + writerContainer.outputWriterForRow(partitionPart).write(dataPart) } writerContainer.commitTask() diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala index 20afd60cb7..01c67db232 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala @@ -26,7 +26,7 @@ import org.apache.spark.Logging import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.sql.catalyst.AbstractSparkSQLParser import org.apache.spark.sql.catalyst.analysis.UnresolvedRelation -import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference, Row} +import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference, InternalRow} import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.execution.RunnableCommand import org.apache.spark.sql.types._ @@ -404,7 +404,7 @@ private[sql] case class CreateTempTableUsing( provider: String, options: Map[String, String]) extends RunnableCommand { - def run(sqlContext: SQLContext): Seq[Row] = { + def run(sqlContext: SQLContext): Seq[InternalRow] = { val resolved = ResolvedDataSource( sqlContext, userSpecifiedSchema, Array.empty[String], provider, options) sqlContext.registerDataFrameAsTable( @@ -421,7 +421,7 @@ private[sql] case class CreateTempTableUsingAsSelect( options: Map[String, String], query: LogicalPlan) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { val df = DataFrame(sqlContext, query) val resolved = ResolvedDataSource(sqlContext, provider, partitionColumns, mode, options, df) sqlContext.registerDataFrameAsTable( @@ -434,7 +434,7 @@ private[sql] case class CreateTempTableUsingAsSelect( private[sql] case class RefreshTable(databaseName: String, tableName: String) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { // Refresh the given table's metadata first. sqlContext.catalog.refreshTable(databaseName, tableName) @@ -453,7 +453,7 @@ private[sql] case class RefreshTable(databaseName: String, tableName: String) sqlContext.cacheManager.cacheQuery(df, Some(tableName)) } - Seq.empty[Row] + Seq.empty[InternalRow] } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala index d1547fb1e4..27534a1f48 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala @@ -28,7 +28,8 @@ import org.apache.spark.annotation.{DeveloperApi, Experimental} import org.apache.spark.broadcast.Broadcast import org.apache.spark.rdd.RDD import org.apache.spark.SerializableWritable -import org.apache.spark.sql.{Row, _} +import org.apache.spark.sql.execution.RDDConversions +import org.apache.spark.sql.{DataFrame, Row, SaveMode, SQLContext} import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection import org.apache.spark.sql.types.StructType @@ -195,6 +196,8 @@ abstract class BaseRelation { * java.lang.String -> UTF8String * java.lang.Decimal -> Decimal * + * If `needConversion` is `false`, buildScan() should return an [[RDD]] of [[InternalRow]] + * * Note: The internal representation is not stable across releases and thus data sources outside * of Spark SQL should leave this as true. * @@ -443,7 +446,7 @@ abstract class HadoopFsRelation private[sql](maybePartitionSpec: Option[Partitio val castedValues = partitionSchema.zip(literals).map { case (field, literal) => Cast(literal, field.dataType).eval() } - p.copy(values = Row.fromSeq(castedValues)) + p.copy(values = InternalRow.fromSeq(castedValues)) } PartitionSpec(partitionSchema, castedPartitions) } @@ -579,15 +582,21 @@ abstract class HadoopFsRelation private[sql](maybePartitionSpec: Option[Partitio BoundReference(dataSchema.fieldIndex(col), field.dataType, field.nullable) }.toSeq - buildScan(inputFiles).mapPartitions { rows => + val rdd = buildScan(inputFiles) + val converted = + if (needConversion) { + RDDConversions.rowToRowRdd(rdd, dataSchema.fields.map(_.dataType)) + } else { + rdd.map(_.asInstanceOf[InternalRow]) + } + converted.mapPartitions { rows => val buildProjection = if (codegenEnabled) { GenerateMutableProjection.generate(requiredOutput, dataSchema.toAttributes) } else { () => new InterpretedMutableProjection(requiredOutput, dataSchema.toAttributes) } - val mutableProjection = buildProjection() - rows.map(mutableProjection) + rows.map(r => mutableProjection(r).asInstanceOf[Row]) } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala index 17a3cec48b..eb3e913322 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala @@ -94,7 +94,7 @@ class CachedTableSuite extends QueryTest { } test("too big for memory") { - val data = "*" * 10000 + val data = "*" * 1000 ctx.sparkContext.parallelize(1 to 200000, 1).map(_ => BigData(data)).toDF() .registerTempTable("bigData") ctx.table("bigData").persist(StorageLevel.MEMORY_AND_DISK) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala index 16836628cb..1f37455dd0 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala @@ -18,25 +18,28 @@ package org.apache.spark.sql.columnar import org.apache.spark.SparkFunSuite -import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.catalyst.expressions.InternalRow import org.apache.spark.sql.types._ class ColumnStatsSuite extends SparkFunSuite { - testColumnStats(classOf[ByteColumnStats], BYTE, Row(Byte.MaxValue, Byte.MinValue, 0)) - testColumnStats(classOf[ShortColumnStats], SHORT, Row(Short.MaxValue, Short.MinValue, 0)) - testColumnStats(classOf[IntColumnStats], INT, Row(Int.MaxValue, Int.MinValue, 0)) - testColumnStats(classOf[LongColumnStats], LONG, Row(Long.MaxValue, Long.MinValue, 0)) - testColumnStats(classOf[FloatColumnStats], FLOAT, Row(Float.MaxValue, Float.MinValue, 0)) - testColumnStats(classOf[DoubleColumnStats], DOUBLE, Row(Double.MaxValue, Double.MinValue, 0)) - testColumnStats(classOf[FixedDecimalColumnStats], FIXED_DECIMAL(15, 10), Row(null, null, 0)) - testColumnStats(classOf[StringColumnStats], STRING, Row(null, null, 0)) - testColumnStats(classOf[DateColumnStats], DATE, Row(Int.MaxValue, Int.MinValue, 0)) - testColumnStats(classOf[TimestampColumnStats], TIMESTAMP, Row(Long.MaxValue, Long.MinValue, 0)) + testColumnStats(classOf[ByteColumnStats], BYTE, InternalRow(Byte.MaxValue, Byte.MinValue, 0)) + testColumnStats(classOf[ShortColumnStats], SHORT, InternalRow(Short.MaxValue, Short.MinValue, 0)) + testColumnStats(classOf[IntColumnStats], INT, InternalRow(Int.MaxValue, Int.MinValue, 0)) + testColumnStats(classOf[LongColumnStats], LONG, InternalRow(Long.MaxValue, Long.MinValue, 0)) + testColumnStats(classOf[FloatColumnStats], FLOAT, InternalRow(Float.MaxValue, Float.MinValue, 0)) + testColumnStats(classOf[DoubleColumnStats], DOUBLE, + InternalRow(Double.MaxValue, Double.MinValue, 0)) + testColumnStats(classOf[FixedDecimalColumnStats], + FIXED_DECIMAL(15, 10), InternalRow(null, null, 0)) + testColumnStats(classOf[StringColumnStats], STRING, InternalRow(null, null, 0)) + testColumnStats(classOf[DateColumnStats], DATE, InternalRow(Int.MaxValue, Int.MinValue, 0)) + testColumnStats(classOf[TimestampColumnStats], TIMESTAMP, + InternalRow(Long.MaxValue, Long.MinValue, 0)) def testColumnStats[T <: AtomicType, U <: ColumnStats]( columnStatsClass: Class[U], columnType: NativeColumnType[T], - initialStatistics: Row): Unit = { + initialStatistics: InternalRow): Unit = { val columnStatsName = columnStatsClass.getSimpleName diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala index 1bc7eb3631..7c86eae3f7 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala @@ -19,14 +19,11 @@ package org.apache.spark.sql.columnar import scala.collection.immutable.HashSet import scala.util.Random - -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.GenericMutableRow -import org.apache.spark.sql.types.{AtomicType, DataType, Decimal} import org.apache.spark.sql.types.{DataType, Decimal, AtomicType} import org.apache.spark.unsafe.types.UTF8String - object ColumnarTestUtils { def makeNullRow(length: Int): GenericMutableRow = { val row = new GenericMutableRow(length) @@ -79,9 +76,9 @@ object ColumnarTestUtils { def makeRandomRow( head: ColumnType[_ <: DataType, _], - tail: ColumnType[_ <: DataType, _]*): Row = makeRandomRow(Seq(head) ++ tail) + tail: ColumnType[_ <: DataType, _]*): InternalRow = makeRandomRow(Seq(head) ++ tail) - def makeRandomRow(columnTypes: Seq[ColumnType[_ <: DataType, _]]): Row = { + def makeRandomRow(columnTypes: Seq[ColumnType[_ <: DataType, _]]): InternalRow = { val row = new GenericMutableRow(columnTypes.length) makeRandomValues(columnTypes).zipWithIndex.foreach { case (value, index) => row(index) = value diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala index fa3b8144c0..12f95eb557 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala @@ -20,9 +20,8 @@ package org.apache.spark.sql.columnar import java.sql.{Date, Timestamp} import org.apache.spark.sql.TestData._ -import org.apache.spark.sql.catalyst.expressions.Row import org.apache.spark.sql.types._ -import org.apache.spark.sql.{QueryTest, TestData} +import org.apache.spark.sql.{QueryTest, Row, TestData} import org.apache.spark.storage.StorageLevel.MEMORY_ONLY class InMemoryColumnarQuerySuite extends QueryTest { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/BooleanBitSetSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/BooleanBitSetSuite.scala index 20d65a74e3..f606e2133b 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/BooleanBitSetSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/BooleanBitSetSuite.scala @@ -18,10 +18,10 @@ package org.apache.spark.sql.columnar.compression import org.apache.spark.SparkFunSuite -import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.GenericMutableRow -import org.apache.spark.sql.columnar.{NoopColumnStats, BOOLEAN} import org.apache.spark.sql.columnar.ColumnarTestUtils._ +import org.apache.spark.sql.columnar.{BOOLEAN, NoopColumnStats} class BooleanBitSetSuite extends SparkFunSuite { import BooleanBitSet._ @@ -32,7 +32,7 @@ class BooleanBitSetSuite extends SparkFunSuite { // ------------- val builder = TestCompressibleColumnBuilder(new NoopColumnStats, BOOLEAN, BooleanBitSet) - val rows = Seq.fill[Row](count)(makeRandomRow(BOOLEAN)) + val rows = Seq.fill[InternalRow](count)(makeRandomRow(BOOLEAN)) val values = rows.map(_(0)) rows.foreach(builder.appendFrom(_, 0)) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala index 45a7e8fe68..3e27f58a92 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala @@ -18,16 +18,15 @@ package org.apache.spark.sql.execution import org.apache.spark.SparkFunSuite -import org.apache.spark.sql.{SQLConf, execution} -import org.apache.spark.sql.functions._ import org.apache.spark.sql.TestData._ -import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans._ import org.apache.spark.sql.execution.joins.{BroadcastHashJoin, ShuffledHashJoin} +import org.apache.spark.sql.functions._ import org.apache.spark.sql.test.TestSQLContext._ import org.apache.spark.sql.test.TestSQLContext.implicits._ import org.apache.spark.sql.test.TestSQLContext.planner._ import org.apache.spark.sql.types._ +import org.apache.spark.sql.{Row, SQLConf, execution} class PlannerSuite extends SparkFunSuite { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/joins/HashedRelationSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/joins/HashedRelationSuite.scala index 5290c28cfc..71db6a2159 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/joins/HashedRelationSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/joins/HashedRelationSuite.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.execution.joins import org.apache.spark.SparkFunSuite -import org.apache.spark.sql.catalyst.expressions.{Projection, Row} +import org.apache.spark.sql.catalyst.expressions.{Projection, InternalRow} import org.apache.spark.util.collection.CompactBuffer @@ -26,37 +26,37 @@ class HashedRelationSuite extends SparkFunSuite { // Key is simply the record itself private val keyProjection = new Projection { - override def apply(row: Row): Row = row + override def apply(row: InternalRow): InternalRow = row } test("GeneralHashedRelation") { - val data = Array(Row(0), Row(1), Row(2), Row(2)) + val data = Array(InternalRow(0), InternalRow(1), InternalRow(2), InternalRow(2)) val hashed = HashedRelation(data.iterator, keyProjection) assert(hashed.isInstanceOf[GeneralHashedRelation]) - assert(hashed.get(data(0)) == CompactBuffer[Row](data(0))) - assert(hashed.get(data(1)) == CompactBuffer[Row](data(1))) - assert(hashed.get(Row(10)) === null) + assert(hashed.get(data(0)) == CompactBuffer[InternalRow](data(0))) + assert(hashed.get(data(1)) == CompactBuffer[InternalRow](data(1))) + assert(hashed.get(InternalRow(10)) === null) - val data2 = CompactBuffer[Row](data(2)) + val data2 = CompactBuffer[InternalRow](data(2)) data2 += data(2) assert(hashed.get(data(2)) == data2) } test("UniqueKeyHashedRelation") { - val data = Array(Row(0), Row(1), Row(2)) + val data = Array(InternalRow(0), InternalRow(1), InternalRow(2)) val hashed = HashedRelation(data.iterator, keyProjection) assert(hashed.isInstanceOf[UniqueKeyHashedRelation]) - assert(hashed.get(data(0)) == CompactBuffer[Row](data(0))) - assert(hashed.get(data(1)) == CompactBuffer[Row](data(1))) - assert(hashed.get(data(2)) == CompactBuffer[Row](data(2))) - assert(hashed.get(Row(10)) === null) + assert(hashed.get(data(0)) == CompactBuffer[InternalRow](data(0))) + assert(hashed.get(data(1)) == CompactBuffer[InternalRow](data(1))) + assert(hashed.get(data(2)) == CompactBuffer[InternalRow](data(2))) + assert(hashed.get(InternalRow(10)) === null) val uniqHashed = hashed.asInstanceOf[UniqueKeyHashedRelation] assert(uniqHashed.getValue(data(0)) == data(0)) assert(uniqHashed.getValue(data(1)) == data(1)) assert(uniqHashed.getValue(data(2)) == data(2)) - assert(uniqHashed.getValue(Row(10)) == null) + assert(uniqHashed.getValue(InternalRow(10)) == null) } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala index 17f5f9a491..fa5d4eca05 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala @@ -26,7 +26,7 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.planning.PhysicalOperation import org.apache.spark.sql.sources.LogicalRelation import org.apache.spark.sql.types._ -import org.apache.spark.sql.{Column, DataFrame, QueryTest, SQLConf} +import org.apache.spark.sql.{Column, DataFrame, QueryTest, Row, SQLConf} /** * A test suite that tests Parquet filter2 API based filter pushdown optimization. diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala index 46b25859d9..fc827bc4ca 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala @@ -35,11 +35,10 @@ import org.apache.parquet.schema.{MessageType, MessageTypeParser} import org.scalatest.BeforeAndAfterAll import org.apache.spark.SparkException +import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.ScalaReflection -import org.apache.spark.sql.catalyst.expressions.Row import org.apache.spark.sql.catalyst.util.DateUtils import org.apache.spark.sql.types._ -import org.apache.spark.sql.{DataFrame, QueryTest, SQLConf, SaveMode} // Write support class for nested groups: ParquetWriter initializes GroupWriteSupport // with an empty configuration (it is after all not intended to be used in this way?) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetPartitionDiscoverySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetPartitionDiscoverySuite.scala index 3240079483..01df189d1f 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetPartitionDiscoverySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetPartitionDiscoverySuite.scala @@ -26,11 +26,13 @@ import scala.collection.mutable.ArrayBuffer import com.google.common.io.Files import org.apache.hadoop.fs.Path +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.catalyst.expressions.Literal import org.apache.spark.sql.sources.PartitioningUtils._ import org.apache.spark.sql.sources.{LogicalRelation, Partition, PartitionSpec} import org.apache.spark.sql.types._ -import org.apache.spark.sql.{Column, QueryTest, Row, SQLContext} +import org.apache.spark.sql._ +import org.apache.spark.unsafe.types.UTF8String // The data where the partitioning key exists only in the directory structure. case class ParquetData(intField: Int, stringField: String) @@ -114,7 +116,8 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructType(Seq( StructField("a", IntegerType), StructField("b", StringType))), - Seq(Partition(Row(10, "hello"), "hdfs://host:9000/path/a=10/b=hello")))) + Seq(Partition(InternalRow(10, UTF8String.fromString("hello")), + "hdfs://host:9000/path/a=10/b=hello")))) check(Seq( "hdfs://host:9000/path/a=10/b=20", @@ -124,8 +127,10 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructField("a", DoubleType), StructField("b", StringType))), Seq( - Partition(Row(10, "20"), "hdfs://host:9000/path/a=10/b=20"), - Partition(Row(10.5, "hello"), "hdfs://host:9000/path/a=10.5/b=hello")))) + Partition(InternalRow(10, UTF8String.fromString("20")), + "hdfs://host:9000/path/a=10/b=20"), + Partition(InternalRow(10.5, UTF8String.fromString("hello")), + "hdfs://host:9000/path/a=10.5/b=hello")))) check(Seq( "hdfs://host:9000/path/_temporary", @@ -143,8 +148,10 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructField("a", DoubleType), StructField("b", StringType))), Seq( - Partition(Row(10, "20"), "hdfs://host:9000/path/a=10/b=20"), - Partition(Row(10.5, "hello"), "hdfs://host:9000/path/a=10.5/b=hello")))) + Partition(InternalRow(10, UTF8String.fromString("20")), + "hdfs://host:9000/path/a=10/b=20"), + Partition(InternalRow(10.5, UTF8String.fromString("hello")), + "hdfs://host:9000/path/a=10.5/b=hello")))) check(Seq( s"hdfs://host:9000/path/a=10/b=20", @@ -154,8 +161,10 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructField("a", IntegerType), StructField("b", StringType))), Seq( - Partition(Row(10, "20"), s"hdfs://host:9000/path/a=10/b=20"), - Partition(Row(null, "hello"), s"hdfs://host:9000/path/a=$defaultPartitionName/b=hello")))) + Partition(InternalRow(10, UTF8String.fromString("20")), + s"hdfs://host:9000/path/a=10/b=20"), + Partition(InternalRow(null, UTF8String.fromString("hello")), + s"hdfs://host:9000/path/a=$defaultPartitionName/b=hello")))) check(Seq( s"hdfs://host:9000/path/a=10/b=$defaultPartitionName", @@ -165,8 +174,9 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructField("a", DoubleType), StructField("b", StringType))), Seq( - Partition(Row(10, null), s"hdfs://host:9000/path/a=10/b=$defaultPartitionName"), - Partition(Row(10.5, null), s"hdfs://host:9000/path/a=10.5/b=$defaultPartitionName")))) + Partition(InternalRow(10, null), s"hdfs://host:9000/path/a=10/b=$defaultPartitionName"), + Partition(InternalRow(10.5, null), + s"hdfs://host:9000/path/a=10.5/b=$defaultPartitionName")))) check(Seq( s"hdfs://host:9000/path1", @@ -185,7 +195,8 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructType(Seq( StructField("a", StringType), StructField("b", StringType))), - Seq(Partition(Row("10", "hello"), "hdfs://host:9000/path/a=10/b=hello")))) + Seq(Partition(InternalRow(UTF8String.fromString("10"), UTF8String.fromString("hello")), + "hdfs://host:9000/path/a=10/b=hello")))) check(Seq( "hdfs://host:9000/path/a=10/b=20", @@ -195,8 +206,10 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructField("a", StringType), StructField("b", StringType))), Seq( - Partition(Row("10", "20"), "hdfs://host:9000/path/a=10/b=20"), - Partition(Row("10.5", "hello"), "hdfs://host:9000/path/a=10.5/b=hello")))) + Partition(InternalRow(UTF8String.fromString("10"), UTF8String.fromString("20")), + "hdfs://host:9000/path/a=10/b=20"), + Partition(InternalRow(UTF8String.fromString("10.5"), UTF8String.fromString("hello")), + "hdfs://host:9000/path/a=10.5/b=hello")))) check(Seq( "hdfs://host:9000/path/_temporary", @@ -214,8 +227,10 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructField("a", StringType), StructField("b", StringType))), Seq( - Partition(Row("10", "20"), "hdfs://host:9000/path/a=10/b=20"), - Partition(Row("10.5", "hello"), "hdfs://host:9000/path/a=10.5/b=hello")))) + Partition(InternalRow(UTF8String.fromString("10"), UTF8String.fromString("20")), + "hdfs://host:9000/path/a=10/b=20"), + Partition(InternalRow(UTF8String.fromString("10.5"), UTF8String.fromString("hello")), + "hdfs://host:9000/path/a=10.5/b=hello")))) check(Seq( s"hdfs://host:9000/path/a=10/b=20", @@ -225,8 +240,10 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructField("a", StringType), StructField("b", StringType))), Seq( - Partition(Row("10", "20"), s"hdfs://host:9000/path/a=10/b=20"), - Partition(Row(null, "hello"), s"hdfs://host:9000/path/a=$defaultPartitionName/b=hello")))) + Partition(InternalRow(UTF8String.fromString("10"), UTF8String.fromString("20")), + s"hdfs://host:9000/path/a=10/b=20"), + Partition(InternalRow(null, UTF8String.fromString("hello")), + s"hdfs://host:9000/path/a=$defaultPartitionName/b=hello")))) check(Seq( s"hdfs://host:9000/path/a=10/b=$defaultPartitionName", @@ -236,8 +253,10 @@ class ParquetPartitionDiscoverySuite extends QueryTest with ParquetTest { StructField("a", StringType), StructField("b", StringType))), Seq( - Partition(Row("10", null), s"hdfs://host:9000/path/a=10/b=$defaultPartitionName"), - Partition(Row("10.5", null), s"hdfs://host:9000/path/a=10.5/b=$defaultPartitionName")))) + Partition(InternalRow(UTF8String.fromString("10"), null), + s"hdfs://host:9000/path/a=10/b=$defaultPartitionName"), + Partition(InternalRow(UTF8String.fromString("10.5"), null), + s"hdfs://host:9000/path/a=10.5/b=$defaultPartitionName")))) check(Seq( s"hdfs://host:9000/path1", diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala index de0107a361..be3b34d5b9 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala @@ -20,15 +20,13 @@ package org.apache.spark.sql.parquet import org.scalatest.BeforeAndAfterAll import org.apache.spark.sql.types._ -import org.apache.spark.sql.{SQLConf, QueryTest} -import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.{QueryTest, Row, SQLConf} /** * A test suite that tests various Parquet queries. */ class ParquetQuerySuiteBase extends QueryTest with ParquetTest { lazy val sqlContext = org.apache.spark.sql.test.TestSQLContext - import sqlContext.implicits._ import sqlContext.sql test("simple select queries") { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/DDLTestSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/DDLTestSuite.scala index 51d22b6a13..5fc53f7012 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/sources/DDLTestSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/DDLTestSuite.scala @@ -19,7 +19,9 @@ package org.apache.spark.sql.sources import org.apache.spark.rdd.RDD import org.apache.spark.sql._ +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.types._ +import org.apache.spark.unsafe.types.UTF8String class DDLScanSource extends RelationProvider { override def createRelation( @@ -56,9 +58,12 @@ case class SimpleDDLScan(from: Int, to: Int, table: String)(@transient val sqlCo ) )) + override def needConversion: Boolean = false override def buildScan(): RDD[Row] = { - sqlContext.sparkContext.parallelize(from to to).map(e => Row(s"people$e", e * 2)) + sqlContext.sparkContext.parallelize(from to to).map { e => + InternalRow(UTF8String.fromString(s"people$e"), e * 2) + } } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala index 5d4ecd8108..4a4d8d2548 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala @@ -19,9 +19,13 @@ package org.apache.spark.sql.sources import java.sql.{Timestamp, Date} + import org.apache.spark.rdd.RDD import org.apache.spark.sql._ +import org.apache.spark.sql.catalyst.util.DateUtils +import org.apache.spark.sql.catalyst.InternalRow import org.apache.spark.sql.types._ +import org.apache.spark.unsafe.types.UTF8String class DefaultSource extends SimpleScanSource @@ -60,10 +64,12 @@ case class AllDataTypesScan( override def schema: StructType = userSpecifiedSchema + override def needConversion: Boolean = false + override def buildScan(): RDD[Row] = { sqlContext.sparkContext.parallelize(from to to).map { i => - Row( - s"str_$i", + InternalRow( + UTF8String.fromString(s"str_$i"), s"str_$i".getBytes(), i % 2 == 0, i.toByte, @@ -72,17 +78,18 @@ case class AllDataTypesScan( i.toLong, i.toFloat, i.toDouble, - new java.math.BigDecimal(i), - new java.math.BigDecimal(i), - new Date(1970, 1, 1), - new Timestamp(20000 + i), - s"varchar_$i", + Decimal(new java.math.BigDecimal(i)), + Decimal(new java.math.BigDecimal(i)), + DateUtils.fromJavaDate(new Date(1970, 1, 1)), + DateUtils.fromJavaTimestamp(new Timestamp(20000 + i)), + UTF8String.fromString(s"varchar_$i"), Seq(i, i + 1), - Seq(Map(s"str_$i" -> Row(i.toLong))), + Seq(Map(UTF8String.fromString(s"str_$i") -> InternalRow(i.toLong))), Map(i -> i.toString), - Map(Map(s"str_$i" -> i.toFloat) -> Row(i.toLong)), + Map(Map(UTF8String.fromString(s"str_$i") -> i.toFloat) -> InternalRow(i.toLong)), Row(i, i.toString), - Row(Seq(s"str_$i", s"str_${i + 1}"), Row(Seq(new Date(1970, 1, i + 1))))) + Row(Seq(UTF8String.fromString(s"str_$i"), UTF8String.fromString(s"str_${i + 1}")), + InternalRow(Seq(DateUtils.fromJavaDate(new Date(1970, 1, i + 1)))))) } } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala index fd01a8722b..d4f1ae8ee0 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala @@ -366,7 +366,7 @@ private[hive] trait HiveInspectors { (o: Any) => { if (o != null) { val struct = soi.create() - (soi.getAllStructFieldRefs, wrappers, o.asInstanceOf[Row].toSeq).zipped.foreach { + (soi.getAllStructFieldRefs, wrappers, o.asInstanceOf[InternalRow].toSeq).zipped.foreach { (field, wrapper, data) => soi.setStructFieldData(struct, field, wrapper(data)) } struct @@ -474,7 +474,7 @@ private[hive] trait HiveInspectors { } case x: SettableStructObjectInspector => val fieldRefs = x.getAllStructFieldRefs - val row = a.asInstanceOf[Row] + val row = a.asInstanceOf[InternalRow] // 1. create the pojo (most likely) object val result = x.create() var i = 0 @@ -490,7 +490,7 @@ private[hive] trait HiveInspectors { result case x: StructObjectInspector => val fieldRefs = x.getAllStructFieldRefs - val row = a.asInstanceOf[Row] + val row = a.asInstanceOf[InternalRow] val result = new java.util.ArrayList[AnyRef](fieldRefs.length) var i = 0 while (i < fieldRefs.length) { @@ -517,7 +517,7 @@ private[hive] trait HiveInspectors { } def wrap( - row: Row, + row: InternalRow, inspectors: Seq[ObjectInspector], cache: Array[AnyRef]): Array[AnyRef] = { var i = 0 diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala index 5a4651a887..619ef63223 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala @@ -302,7 +302,7 @@ private[hive] class HiveMetastoreCatalog(val client: ClientInterface, hive: Hive val partitionColumnDataTypes = partitionSchema.map(_.dataType) val partitions = metastoreRelation.hiveQlPartitions.map { p => val location = p.getLocation - val values = Row.fromSeq(p.getValues.zip(partitionColumnDataTypes).map { + val values = InternalRow.fromSeq(p.getValues.zip(partitionColumnDataTypes).map { case (rawValue, dataType) => Cast(Literal(rawValue), dataType).eval(null) }) ParquetPartition(values, location) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala index c6b6510645..452b7f0bcc 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala @@ -24,7 +24,7 @@ import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.CatalystTypeConverters import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute import org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate -import org.apache.spark.sql.catalyst.expressions.{Row, _} +import org.apache.spark.sql.catalyst.expressions.{InternalRow, _} import org.apache.spark.sql.catalyst.planning._ import org.apache.spark.sql.catalyst.plans._ import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan @@ -137,7 +137,7 @@ private[hive] trait HiveStrategies { val partitionLocations = partitions.map(_.getLocation) if (partitionLocations.isEmpty) { - PhysicalRDD(plan.output, sparkContext.emptyRDD[Row]) :: Nil + PhysicalRDD(plan.output, sparkContext.emptyRDD[InternalRow]) :: Nil } else { hiveContext .read.parquet(partitionLocations: _*) @@ -165,7 +165,7 @@ private[hive] trait HiveStrategies { // TODO: Remove this hack for Spark 1.3. case iae: java.lang.IllegalArgumentException if iae.getMessage.contains("Can not create a Path from an empty string") => - PhysicalRDD(plan.output, sparkContext.emptyRDD[Row]) :: Nil + PhysicalRDD(plan.output, sparkContext.emptyRDD[InternalRow]) :: Nil } case _ => Nil } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala index d3c82d8c2e..485810320f 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala @@ -41,9 +41,9 @@ import org.apache.spark.util.Utils * A trait for subclasses that handle table scans. */ private[hive] sealed trait TableReader { - def makeRDDForTable(hiveTable: HiveTable): RDD[Row] + def makeRDDForTable(hiveTable: HiveTable): RDD[InternalRow] - def makeRDDForPartitionedTable(partitions: Seq[HivePartition]): RDD[Row] + def makeRDDForPartitionedTable(partitions: Seq[HivePartition]): RDD[InternalRow] } @@ -74,7 +74,7 @@ class HadoopTableReader( private val _broadcastedHiveConf = sc.sparkContext.broadcast(new SerializableWritable(hiveExtraConf)) - override def makeRDDForTable(hiveTable: HiveTable): RDD[Row] = + override def makeRDDForTable(hiveTable: HiveTable): RDD[InternalRow] = makeRDDForTable( hiveTable, Class.forName( @@ -94,7 +94,7 @@ class HadoopTableReader( def makeRDDForTable( hiveTable: HiveTable, deserializerClass: Class[_ <: Deserializer], - filterOpt: Option[PathFilter]): RDD[Row] = { + filterOpt: Option[PathFilter]): RDD[InternalRow] = { assert(!hiveTable.isPartitioned, """makeRDDForTable() cannot be called on a partitioned table, since input formats may differ across partitions. Use makeRDDForTablePartitions() instead.""") @@ -125,7 +125,7 @@ class HadoopTableReader( deserializedHadoopRDD } - override def makeRDDForPartitionedTable(partitions: Seq[HivePartition]): RDD[Row] = { + override def makeRDDForPartitionedTable(partitions: Seq[HivePartition]): RDD[InternalRow] = { val partitionToDeserializer = partitions.map(part => (part, part.getDeserializer.getClass.asInstanceOf[Class[Deserializer]])).toMap makeRDDForPartitionedTable(partitionToDeserializer, filterOpt = None) @@ -144,7 +144,7 @@ class HadoopTableReader( def makeRDDForPartitionedTable( partitionToDeserializer: Map[HivePartition, Class[_ <: Deserializer]], - filterOpt: Option[PathFilter]): RDD[Row] = { + filterOpt: Option[PathFilter]): RDD[InternalRow] = { // SPARK-5068:get FileStatus and do the filtering locally when the path is not exists def verifyPartitionPath( @@ -243,7 +243,7 @@ class HadoopTableReader( // Even if we don't use any partitions, we still need an empty RDD if (hivePartitionRDDs.size == 0) { - new EmptyRDD[Row](sc.sparkContext) + new EmptyRDD[InternalRow](sc.sparkContext) } else { new UnionRDD(hivePartitionRDDs(0).context, hivePartitionRDDs) } @@ -319,7 +319,7 @@ private[hive] object HadoopTableReader extends HiveInspectors with Logging { rawDeser: Deserializer, nonPartitionKeyAttrs: Seq[(Attribute, Int)], mutableRow: MutableRow, - tableDeser: Deserializer): Iterator[Row] = { + tableDeser: Deserializer): Iterator[InternalRow] = { val soi = if (rawDeser.getObjectInspector.equals(tableDeser.getObjectInspector)) { rawDeser.getObjectInspector.asInstanceOf[StructObjectInspector] @@ -391,7 +391,7 @@ private[hive] object HadoopTableReader extends HiveInspectors with Logging { i += 1 } - mutableRow: Row + mutableRow: InternalRow } } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala index 87c36a8b61..0e4a2427a9 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.hive.execution import org.apache.spark.annotation.Experimental import org.apache.spark.sql.{AnalysisException, SQLContext} -import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.catalyst.expressions.InternalRow import org.apache.spark.sql.catalyst.plans.logical.{InsertIntoTable, LogicalPlan} import org.apache.spark.sql.execution.RunnableCommand import org.apache.spark.sql.hive.client.{HiveTable, HiveColumn} @@ -42,7 +42,7 @@ case class CreateTableAsSelect( def database: String = tableDesc.database def tableName: String = tableDesc.name - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { val hiveContext = sqlContext.asInstanceOf[HiveContext] lazy val metastoreRelation: MetastoreRelation = { import org.apache.hadoop.hive.serde2.`lazy`.LazySimpleSerDe @@ -89,7 +89,7 @@ case class CreateTableAsSelect( hiveContext.executePlan(InsertIntoTable(metastoreRelation, Map(), query, true, false)).toRdd } - Seq.empty[Row] + Seq.empty[InternalRow] } override def argString: String = { diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/DescribeHiveTableCommand.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/DescribeHiveTableCommand.scala index 6fce69b58b..a89381000a 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/DescribeHiveTableCommand.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/DescribeHiveTableCommand.scala @@ -21,12 +21,10 @@ import scala.collection.JavaConversions._ import org.apache.hadoop.hive.metastore.api.FieldSchema -import org.apache.spark.annotation.DeveloperApi -import org.apache.spark.sql.catalyst.expressions.{Attribute, Row} -import org.apache.spark.sql.execution.{SparkPlan, RunnableCommand} -import org.apache.spark.sql.hive.{HiveContext, MetastoreRelation} -import org.apache.spark.sql.hive.HiveShim import org.apache.spark.sql.SQLContext +import org.apache.spark.sql.catalyst.expressions.{Attribute, InternalRow} +import org.apache.spark.sql.execution.RunnableCommand +import org.apache.spark.sql.hive.MetastoreRelation /** * Implementation for "describe [extended] table". @@ -37,7 +35,7 @@ case class DescribeHiveTableCommand( override val output: Seq[Attribute], isExtended: Boolean) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { // Trying to mimic the format of Hive's output. But not exactly the same. var results: Seq[(String, String, String)] = Nil @@ -59,7 +57,7 @@ case class DescribeHiveTableCommand( } results.map { case (name, dataType, comment) => - Row(name, dataType, comment) + InternalRow(name, dataType, comment) } } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala index 60a9bb630d..87f8e3f7fc 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala @@ -1,34 +1,34 @@ -/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements. See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.spark.sql.hive.execution
-
-import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Row}
-import org.apache.spark.sql.execution.RunnableCommand
-import org.apache.spark.sql.hive.HiveContext
-import org.apache.spark.sql.SQLContext
-import org.apache.spark.sql.types.StringType
-
-private[hive]
-case class HiveNativeCommand(sql: String) extends RunnableCommand {
-
- override def output: Seq[AttributeReference] =
- Seq(AttributeReference("result", StringType, nullable = false)())
-
- override def run(sqlContext: SQLContext): Seq[Row] =
- sqlContext.asInstanceOf[HiveContext].runSqlHive(sql).map(Row(_))
-}
+/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.hive.execution + +import org.apache.spark.sql.catalyst.expressions.{AttributeReference, InternalRow} +import org.apache.spark.sql.execution.RunnableCommand +import org.apache.spark.sql.hive.HiveContext +import org.apache.spark.sql.SQLContext +import org.apache.spark.sql.types.StringType + +private[hive] +case class HiveNativeCommand(sql: String) extends RunnableCommand { + + override def output: Seq[AttributeReference] = + Seq(AttributeReference("result", StringType, nullable = false)()) + + override def run(sqlContext: SQLContext): Seq[InternalRow] = + sqlContext.asInstanceOf[HiveContext].runSqlHive(sql).map(InternalRow(_)) +} diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala index 11ee550314..1f5e4af2e4 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala @@ -129,7 +129,7 @@ case class HiveTableScan( } } - protected override def doExecute(): RDD[Row] = if (!relation.hiveQlTable.isPartitioned) { + protected override def doExecute(): RDD[InternalRow] = if (!relation.hiveQlTable.isPartitioned) { hadoopReader.makeRDDForTable(relation.hiveQlTable) } else { hadoopReader.makeRDDForPartitionedTable(prunePartitions(relation.hiveQlPartitions)) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala index eeb472602b..1d306c5d10 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala @@ -30,7 +30,8 @@ import org.apache.hadoop.hive.serde2.objectinspector._ import org.apache.hadoop.mapred.{FileOutputFormat, JobConf} import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.expressions.{Attribute, Row} +import org.apache.spark.sql.Row +import org.apache.spark.sql.catalyst.expressions.{Attribute, InternalRow} import org.apache.spark.sql.execution.{UnaryNode, SparkPlan} import org.apache.spark.sql.hive.HiveShim.{ShimFileSinkDesc => FileSinkDesc} import org.apache.spark.sql.hive._ @@ -60,7 +61,7 @@ case class InsertIntoHiveTable( def output: Seq[Attribute] = child.output def saveAsHiveFile( - rdd: RDD[Row], + rdd: RDD[InternalRow], valueClass: Class[_], fileSinkConf: FileSinkDesc, conf: SerializableWritable[JobConf], @@ -82,7 +83,7 @@ case class InsertIntoHiveTable( writerContainer.commitJob() // Note that this function is executed on executor side - def writeToFile(context: TaskContext, iterator: Iterator[Row]): Unit = { + def writeToFile(context: TaskContext, iterator: Iterator[InternalRow]): Unit = { val serializer = newSerializer(fileSinkConf.getTableInfo) val standardOI = ObjectInspectorUtils .getStandardObjectInspector( @@ -119,7 +120,7 @@ case class InsertIntoHiveTable( * * Note: this is run once and then kept to avoid double insertions. */ - protected[sql] lazy val sideEffectResult: Seq[Row] = { + protected[sql] lazy val sideEffectResult: Seq[InternalRow] = { // Have to pass the TableDesc object to RDD.mapPartitions and then instantiate new serializer // instances within the closure, since Serializer is not serializable while TableDesc is. val tableDesc = table.tableDesc @@ -250,12 +251,13 @@ case class InsertIntoHiveTable( // however for now we return an empty list to simplify compatibility checks with hive, which // does not return anything for insert operations. // TODO: implement hive compatibility as rules. - Seq.empty[Row] + Seq.empty[InternalRow] } - override def executeCollect(): Array[Row] = sideEffectResult.toArray + override def executeCollect(): Array[Row] = + sideEffectResult.toArray - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { sqlContext.sparkContext.parallelize(sideEffectResult, 1) } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformation.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformation.scala index 28792db768..9d8872aa47 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformation.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformation.scala @@ -55,7 +55,7 @@ case class ScriptTransformation( override def otherCopyArgs: Seq[HiveContext] = sc :: Nil - protected override def doExecute(): RDD[Row] = { + protected override def doExecute(): RDD[InternalRow] = { child.execute().mapPartitions { iter => val cmd = List("/bin/bash", "-c", script) val builder = new ProcessBuilder(cmd) @@ -72,8 +72,8 @@ case class ScriptTransformation( val (outputSerde, outputSoi) = ioschema.initOutputSerDe(output) - val iterator: Iterator[Row] = new Iterator[Row] with HiveInspectors { - var cacheRow: Row = null + val iterator: Iterator[InternalRow] = new Iterator[InternalRow] with HiveInspectors { + var cacheRow: InternalRow = null var curLine: String = null var eof: Boolean = false @@ -90,7 +90,7 @@ case class ScriptTransformation( } } - def deserialize(): Row = { + def deserialize(): InternalRow = { if (cacheRow != null) return cacheRow val mutableRow = new SpecificMutableRow(output.map(_.dataType)) @@ -120,7 +120,7 @@ case class ScriptTransformation( } } - override def next(): Row = { + override def next(): InternalRow = { if (!hasNext) { throw new NoSuchElementException } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala index 0ba94d7b7c..195e5752c3 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala @@ -22,7 +22,7 @@ import org.apache.spark.sql.catalyst.analysis.EliminateSubQueries import org.apache.spark.sql.catalyst.util._ import org.apache.spark.sql.sources._ import org.apache.spark.sql.{SaveMode, DataFrame, SQLContext} -import org.apache.spark.sql.catalyst.expressions.{Attribute, Row} +import org.apache.spark.sql.catalyst.expressions.{Attribute, InternalRow} import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.execution.RunnableCommand import org.apache.spark.sql.hive.HiveContext @@ -39,9 +39,9 @@ import org.apache.spark.util.Utils private[hive] case class AnalyzeTable(tableName: String) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { sqlContext.asInstanceOf[HiveContext].analyze(tableName) - Seq.empty[Row] + Seq.empty[InternalRow] } } @@ -53,7 +53,7 @@ case class DropTable( tableName: String, ifExists: Boolean) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { val hiveContext = sqlContext.asInstanceOf[HiveContext] val ifExistsClause = if (ifExists) "IF EXISTS " else "" try { @@ -70,7 +70,7 @@ case class DropTable( hiveContext.invalidateTable(tableName) hiveContext.runSqlHive(s"DROP TABLE $ifExistsClause$tableName") hiveContext.catalog.unregisterTable(Seq(tableName)) - Seq.empty[Row] + Seq.empty[InternalRow] } } @@ -83,7 +83,7 @@ case class AddJar(path: String) extends RunnableCommand { schema.toAttributes } - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { val hiveContext = sqlContext.asInstanceOf[HiveContext] val currentClassLoader = Utils.getContextOrSparkClassLoader @@ -99,18 +99,18 @@ case class AddJar(path: String) extends RunnableCommand { // Add jar to executors hiveContext.sparkContext.addJar(path) - Seq(Row(0)) + Seq(InternalRow(0)) } } private[hive] case class AddFile(path: String) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { val hiveContext = sqlContext.asInstanceOf[HiveContext] hiveContext.runSqlHive(s"ADD FILE $path") hiveContext.sparkContext.addFile(path) - Seq.empty[Row] + Seq.empty[InternalRow] } } @@ -123,12 +123,12 @@ case class CreateMetastoreDataSource( allowExisting: Boolean, managedIfNoPath: Boolean) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { val hiveContext = sqlContext.asInstanceOf[HiveContext] if (hiveContext.catalog.tableExists(tableName :: Nil)) { if (allowExisting) { - return Seq.empty[Row] + return Seq.empty[InternalRow] } else { throw new AnalysisException(s"Table $tableName already exists.") } @@ -151,7 +151,7 @@ case class CreateMetastoreDataSource( optionsWithPath, isExternal) - Seq.empty[Row] + Seq.empty[InternalRow] } } @@ -164,7 +164,7 @@ case class CreateMetastoreDataSourceAsSelect( options: Map[String, String], query: LogicalPlan) extends RunnableCommand { - override def run(sqlContext: SQLContext): Seq[Row] = { + override def run(sqlContext: SQLContext): Seq[InternalRow] = { val hiveContext = sqlContext.asInstanceOf[HiveContext] var createMetastoreTable = false var isExternal = true @@ -188,7 +188,7 @@ case class CreateMetastoreDataSourceAsSelect( s"Or, if you are using SQL CREATE TABLE, you need to drop $tableName first.") case SaveMode.Ignore => // Since the table already exists and the save mode is Ignore, we will just return. - return Seq.empty[Row] + return Seq.empty[InternalRow] case SaveMode.Append => // Check if the specified data source match the data source of the existing table. val resolved = ResolvedDataSource( @@ -230,7 +230,7 @@ case class CreateMetastoreDataSourceAsSelect( val data = DataFrame(hiveContext, query) val df = existingSchema match { // If we are inserting into an existing table, just use the existing schema. - case Some(schema) => sqlContext.createDataFrame(data.queryExecution.toRdd, schema) + case Some(schema) => sqlContext.internalCreateDataFrame(data.queryExecution.toRdd, schema) case None => data } @@ -253,6 +253,6 @@ case class CreateMetastoreDataSourceAsSelect( // Refresh the cache of the table in the catalog. hiveContext.refreshTable(tableName) - Seq.empty[Row] + Seq.empty[InternalRow] } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala index a46ee9da90..c40dd4e4b9 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala @@ -121,7 +121,7 @@ private[hive] case class HiveSimpleUdf(funcWrapper: HiveFunctionWrapper, childre protected lazy val cached: Array[AnyRef] = new Array[AnyRef](children.length) // TODO: Finish input output types. - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { unwrap( FunctionRegistry.invoke(method, function, conversionHelper .convertIfNecessary(wrap(children.map(c => c.eval(input)), arguments, cached): _*): _*), @@ -178,7 +178,7 @@ private[hive] case class HiveGenericUdf(funcWrapper: HiveFunctionWrapper, childr lazy val dataType: DataType = inspectorToDataType(returnInspector) - override def eval(input: Row): Any = { + override def eval(input: InternalRow): Any = { returnInspector // Make sure initialized. var i = 0 @@ -345,7 +345,7 @@ private[hive] case class HiveWindowFunction( def nullable: Boolean = true - override def eval(input: Row): Any = + override def eval(input: InternalRow): Any = throw new TreeNodeException(this, s"No function to evaluate expression. type: ${this.nodeName}") @transient @@ -369,7 +369,7 @@ private[hive] case class HiveWindowFunction( evaluator.reset(hiveEvaluatorBuffer) } - override def prepareInputParameters(input: Row): AnyRef = { + override def prepareInputParameters(input: InternalRow): AnyRef = { wrap(inputProjection(input), inputInspectors, new Array[AnyRef](children.length)) } // Add input parameters for a single row. @@ -512,7 +512,7 @@ private[hive] case class HiveGenericUdtf( field => (inspectorToDataType(field.getFieldObjectInspector), true) } - override def eval(input: Row): TraversableOnce[Row] = { + override def eval(input: InternalRow): TraversableOnce[InternalRow] = { outputInspector // Make sure initialized. val inputProjection = new InterpretedProjection(children) @@ -522,23 +522,23 @@ private[hive] case class HiveGenericUdtf( } protected class UDTFCollector extends Collector { - var collected = new ArrayBuffer[Row] + var collected = new ArrayBuffer[InternalRow] override def collect(input: java.lang.Object) { // We need to clone the input here because implementations of // GenericUDTF reuse the same object. Luckily they are always an array, so // it is easy to clone. - collected += unwrap(input, outputInspector).asInstanceOf[Row] + collected += unwrap(input, outputInspector).asInstanceOf[InternalRow] } - def collectRows(): Seq[Row] = { + def collectRows(): Seq[InternalRow] = { val toCollect = collected - collected = new ArrayBuffer[Row] + collected = new ArrayBuffer[InternalRow] toCollect } } - override def terminate(): TraversableOnce[Row] = { + override def terminate(): TraversableOnce[InternalRow] = { outputInspector // Make sure initialized. function.close() collector.collectRows() @@ -578,7 +578,7 @@ private[hive] case class HiveUdafFunction( private val buffer = function.getNewAggregationBuffer - override def eval(input: Row): Any = unwrap(function.evaluate(buffer), returnInspector) + override def eval(input: InternalRow): Any = unwrap(function.evaluate(buffer), returnInspector) @transient val inputProjection = new InterpretedProjection(exprs) @@ -586,7 +586,7 @@ private[hive] case class HiveUdafFunction( @transient protected lazy val cached = new Array[AnyRef](exprs.length) - def update(input: Row): Unit = { + def update(input: InternalRow): Unit = { val inputs = inputProjection(input) function.iterate(buffer, wrap(inputs, inspectors, cached)) } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala index df137e7b2b..aff0456b37 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala @@ -28,8 +28,9 @@ import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectIn import org.apache.hadoop.io.LongWritable import org.apache.spark.SparkFunSuite -import org.apache.spark.sql.catalyst.expressions.{Literal, Row} +import org.apache.spark.sql.catalyst.expressions.{Literal, InternalRow} import org.apache.spark.sql.types._ +import org.apache.spark.sql.Row class HiveInspectorSuite extends SparkFunSuite with HiveInspectors { test("Test wrap SettableStructObjectInspector") { @@ -45,7 +46,7 @@ class HiveInspectorSuite extends SparkFunSuite with HiveInspectors { classOf[UDAFPercentile.State], ObjectInspectorOptions.JAVA).asInstanceOf[StructObjectInspector] - val a = unwrap(state, soi).asInstanceOf[Row] + val a = unwrap(state, soi).asInstanceOf[InternalRow] val b = wrap(a, soi).asInstanceOf[UDAFPercentile.State] val sfCounts = soi.getStructFieldRef("counts") @@ -127,7 +128,7 @@ class HiveInspectorSuite extends SparkFunSuite with HiveInspectors { } } - def checkValues(row1: Seq[Any], row2: Row): Unit = { + def checkValues(row1: Seq[Any], row2: InternalRow): Unit = { row1.zip(row2.toSeq).foreach { case (r1, r2) => checkValue(r1, r2) } @@ -203,7 +204,7 @@ class HiveInspectorSuite extends SparkFunSuite with HiveInspectors { }) checkValues(row, - unwrap(wrap(Row.fromSeq(row), toInspector(dt)), toInspector(dt)).asInstanceOf[Row]) + unwrap(wrap(Row.fromSeq(row), toInspector(dt)), toInspector(dt)).asInstanceOf[InternalRow]) checkValue(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveParquetSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveParquetSuite.scala index 5a5ea10e3c..a0d80dc39c 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveParquetSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveParquetSuite.scala @@ -17,10 +17,9 @@ package org.apache.spark.sql.hive -import org.apache.spark.sql.catalyst.expressions.Row import org.apache.spark.sql.hive.test.TestHive import org.apache.spark.sql.parquet.ParquetTest -import org.apache.spark.sql.{QueryTest, SQLConf} +import org.apache.spark.sql.{QueryTest, Row, SQLConf} case class Cases(lower: String, UPPER: String) diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcPartitionDiscoverySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcPartitionDiscoverySuite.scala index 0e63d84e98..8707f9f936 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcPartitionDiscoverySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcPartitionDiscoverySuite.scala @@ -21,7 +21,7 @@ import java.io.File import org.apache.hadoop.hive.conf.HiveConf.ConfVars import org.apache.spark.SparkFunSuite import org.apache.spark.sql._ -import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.catalyst.expressions.InternalRow import org.apache.spark.sql.hive.test.TestHive import org.apache.spark.sql.hive.test.TestHive._ import org.apache.spark.sql.hive.test.TestHive.implicits._ diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcQuerySuite.scala index b384fb39f3..267d22c6b5 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcQuerySuite.scala @@ -25,7 +25,7 @@ import org.scalatest.BeforeAndAfterAll import org.apache.spark.SparkFunSuite import org.apache.spark.sql._ -import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.catalyst.expressions.InternalRow import org.apache.spark.sql.hive.test.TestHive import org.apache.spark.sql.hive.test.TestHive._ import org.apache.spark.sql.hive.test.TestHive.implicits._ diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala index e62ac909cb..3864349cdb 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/parquetSuites.scala @@ -21,8 +21,6 @@ import java.io.File import org.scalatest.BeforeAndAfterAll -import org.apache.spark.sql.catalyst.expressions.Row -import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.execution.{ExecutedCommand, PhysicalRDD} import org.apache.spark.sql.hive.execution.HiveTableScan import org.apache.spark.sql.hive.test.TestHive._ @@ -30,7 +28,7 @@ import org.apache.spark.sql.hive.test.TestHive.implicits._ import org.apache.spark.sql.parquet.{ParquetRelation2, ParquetTableScan} import org.apache.spark.sql.sources.{InsertIntoDataSource, InsertIntoHadoopFsRelation, LogicalRelation} import org.apache.spark.sql.types._ -import org.apache.spark.sql.{DataFrame, QueryTest, SQLConf, SaveMode} +import org.apache.spark.sql.{DataFrame, QueryTest, Row, SQLConf, SaveMode} import org.apache.spark.util.Utils // The data where the partitioning key exists only in the directory structure. |