From f7d2143705c8c1baeed0bc62940f9dba636e705b Mon Sep 17 00:00:00 2001 From: hyukjinkwon Date: Fri, 9 Sep 2016 14:23:05 -0700 Subject: [SPARK-17354] [SQL] Partitioning by dates/timestamps should work with Parquet vectorized reader ## What changes were proposed in this pull request? This PR fixes `ColumnVectorUtils.populate` so that Parquet vectorized reader can read partitioned table with dates/timestamps. This works fine with Parquet normal reader. This is being only called within [VectorizedParquetRecordReader.java#L185](https://github.com/apache/spark/blob/master/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedParquetRecordReader.java#L185). When partition column types are explicitly given to `DateType` or `TimestampType` (rather than inferring the type of partition column), this fails with the exception below: ``` 16/09/01 10:30:07 ERROR Executor: Exception in task 0.0 in stage 5.0 (TID 6) java.lang.ClassCastException: java.lang.Integer cannot be cast to java.sql.Date at org.apache.spark.sql.execution.vectorized.ColumnVectorUtils.populate(ColumnVectorUtils.java:89) at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:185) at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initBatch(VectorizedParquetRecordReader.java:204) at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReader$1.apply(ParquetFileFormat.scala:362) ... ``` ## How was this patch tested? Unit tests in `SQLQuerySuite`. Author: hyukjinkwon Closes #14919 from HyukjinKwon/SPARK-17354. --- .../execution/vectorized/ColumnVectorUtils.java | 5 ++- .../sql/execution/vectorized/ColumnarBatch.java | 6 +++ .../datasources/parquet/ParquetIOSuite.scala | 49 +++++++++++++++++++++- .../spark/sql/hive/execution/SQLQuerySuite.scala | 21 ++++++++++ 4 files changed, 78 insertions(+), 3 deletions(-) diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVectorUtils.java b/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVectorUtils.java index 2fa476b9cf..900d7c431e 100644 --- a/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVectorUtils.java +++ b/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVectorUtils.java @@ -86,8 +86,9 @@ public class ColumnVectorUtils { col.getChildColumn(0).putInts(0, capacity, c.months); col.getChildColumn(1).putLongs(0, capacity, c.microseconds); } else if (t instanceof DateType) { - Date date = (Date)row.get(fieldIdx, t); - col.putInts(0, capacity, DateTimeUtils.fromJavaDate(date)); + col.putInts(0, capacity, row.getInt(fieldIdx)); + } else if (t instanceof TimestampType) { + col.putLongs(0, capacity, row.getLong(fieldIdx)); } } } diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnarBatch.java b/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnarBatch.java index f3afa8f938..62abc2a821 100644 --- a/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnarBatch.java +++ b/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnarBatch.java @@ -137,6 +137,10 @@ public final class ColumnarBatch { DataType dt = columns[i].dataType(); if (dt instanceof BooleanType) { row.setBoolean(i, getBoolean(i)); + } else if (dt instanceof ByteType) { + row.setByte(i, getByte(i)); + } else if (dt instanceof ShortType) { + row.setShort(i, getShort(i)); } else if (dt instanceof IntegerType) { row.setInt(i, getInt(i)); } else if (dt instanceof LongType) { @@ -154,6 +158,8 @@ public final class ColumnarBatch { row.setDecimal(i, getDecimal(i, t.precision(), t.scale()), t.precision()); } else if (dt instanceof DateType) { row.setInt(i, getInt(i)); + } else if (dt instanceof TimestampType) { + row.setLong(i, getLong(i)); } else { throw new RuntimeException("Not implemented. " + dt); } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala index 4aa046bd91..3161a630af 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala @@ -38,11 +38,12 @@ import org.apache.parquet.schema.{MessageType, MessageTypeParser} import org.apache.spark.SparkException import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.{InternalRow, ScalaReflection} -import org.apache.spark.sql.catalyst.expressions.UnsafeRow +import org.apache.spark.sql.catalyst.expressions.{GenericMutableRow, UnsafeRow} import org.apache.spark.sql.catalyst.util.DateTimeUtils import org.apache.spark.sql.internal.SQLConf import org.apache.spark.sql.test.SharedSQLContext import org.apache.spark.sql.types._ +import org.apache.spark.unsafe.types.UTF8String // 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?) @@ -689,6 +690,52 @@ class ParquetIOSuite extends QueryTest with ParquetTest with SharedSQLContext { } } } + + test("VectorizedParquetRecordReader - partition column types") { + withTempPath { dir => + Seq(1).toDF().repartition(1).write.parquet(dir.getCanonicalPath) + + val dataTypes = + Seq(StringType, BooleanType, ByteType, ShortType, IntegerType, LongType, + FloatType, DoubleType, DecimalType(25, 5), DateType, TimestampType) + + val constantValues = + Seq( + UTF8String.fromString("a string"), + true, + 1.toByte, + 2.toShort, + 3, + Long.MaxValue, + 0.25.toFloat, + 0.75D, + Decimal("1234.23456"), + DateTimeUtils.fromJavaDate(java.sql.Date.valueOf("2015-01-01")), + DateTimeUtils.fromJavaTimestamp(java.sql.Timestamp.valueOf("2015-01-01 23:50:59.123"))) + + dataTypes.zip(constantValues).foreach { case (dt, v) => + val schema = StructType(StructField("pcol", dt) :: Nil) + val vectorizedReader = new VectorizedParquetRecordReader + val partitionValues = new GenericMutableRow(Array(v)) + val file = SpecificParquetRecordReaderBase.listDirectory(dir).get(0) + + try { + vectorizedReader.initialize(file, null) + vectorizedReader.initBatch(schema, partitionValues) + vectorizedReader.nextKeyValue() + val row = vectorizedReader.getCurrentValue.asInstanceOf[InternalRow] + + // Use `GenericMutableRow` by explicitly copying rather than `ColumnarBatch` + // in order to use get(...) method which is not implemented in `ColumnarBatch`. + val actual = row.copy().get(1, dt) + val expected = v + assert(actual == expected) + } finally { + vectorizedReader.close() + } + } + } + } } class JobCommitFailureParquetOutputCommitter(outputPath: Path, context: TaskAttemptContext) diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala index 05d0687fb7..dc4d099f0f 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala @@ -1787,6 +1787,27 @@ class SQLQuerySuite extends QueryTest with SQLTestUtils with TestHiveSingleton { } } + test("SPARK-17354: Partitioning by dates/timestamps works with Parquet vectorized reader") { + withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> "true") { + sql( + """CREATE TABLE order(id INT) + |PARTITIONED BY (pd DATE, pt TIMESTAMP) + |STORED AS PARQUET + """.stripMargin) + + sql("set hive.exec.dynamic.partition.mode=nonstrict") + sql( + """INSERT INTO TABLE order PARTITION(pd, pt) + |SELECT 1 AS id, CAST('1990-02-24' AS DATE) AS pd, CAST('1990-02-24' AS TIMESTAMP) AS pt + """.stripMargin) + val actual = sql("SELECT * FROM order") + val expected = sql( + "SELECT 1 AS id, CAST('1990-02-24' AS DATE) AS pd, CAST('1990-02-24' AS TIMESTAMP) AS pt") + checkAnswer(actual, expected) + sql("DROP TABLE order") + } + } + def testCommandAvailable(command: String): Boolean = { val attempt = Try(Process(command).run(ProcessLogger(_ => ())).exitValue()) attempt.isSuccess && attempt.get == 0 -- cgit v1.2.3