diff options
author | Yin Huai <yhuai@databricks.com> | 2015-03-21 13:27:53 -0700 |
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committer | Michael Armbrust <michael@databricks.com> | 2015-03-21 13:27:53 -0700 |
commit | 94a102acb80a7c77f57409ece1f8dbbba791b774 (patch) | |
tree | 334a3c7028af526bfd1954e05eb4e1148cfdb8ab /sql | |
parent | ee569a0c7171d149eee52877def902378eaf695e (diff) | |
download | spark-94a102acb80a7c77f57409ece1f8dbbba791b774.tar.gz spark-94a102acb80a7c77f57409ece1f8dbbba791b774.tar.bz2 spark-94a102acb80a7c77f57409ece1f8dbbba791b774.zip |
[SPARK-6250][SPARK-6146][SPARK-5911][SQL] Types are now reserved words in DDL parser.
This PR creates a trait `DataTypeParser` used to parse data types. This trait aims to be single place to provide the functionality of parsing data types' string representation. It is currently mixed in with `DDLParser` and `SqlParser`. It is also used to parse the data type for `DataFrame.cast` and to convert Hive metastore's data type string back to a `DataType`.
JIRA: https://issues.apache.org/jira/browse/SPARK-6250
Author: Yin Huai <yhuai@databricks.com>
Closes #5078 from yhuai/ddlKeywords and squashes the following commits:
0e66097 [Yin Huai] Special handle struct<>.
fea6012 [Yin Huai] Style.
c9733fb [Yin Huai] Create a trait to parse data types.
Diffstat (limited to 'sql')
6 files changed, 241 insertions, 120 deletions
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala index 54ab13ca35..ea7d44a372 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala @@ -35,7 +35,7 @@ import org.apache.spark.sql.types._ * This is currently included mostly for illustrative purposes. Users wanting more complete support * for a SQL like language should checkout the HiveQL support in the sql/hive sub-project. */ -class SqlParser extends AbstractSparkSQLParser { +class SqlParser extends AbstractSparkSQLParser with DataTypeParser { def parseExpression(input: String): Expression = { // Initialize the Keywords. @@ -61,11 +61,8 @@ class SqlParser extends AbstractSparkSQLParser { protected val CAST = Keyword("CAST") protected val COALESCE = Keyword("COALESCE") protected val COUNT = Keyword("COUNT") - protected val DATE = Keyword("DATE") - protected val DECIMAL = Keyword("DECIMAL") protected val DESC = Keyword("DESC") protected val DISTINCT = Keyword("DISTINCT") - protected val DOUBLE = Keyword("DOUBLE") protected val ELSE = Keyword("ELSE") protected val END = Keyword("END") protected val EXCEPT = Keyword("EXCEPT") @@ -78,7 +75,6 @@ class SqlParser extends AbstractSparkSQLParser { protected val IF = Keyword("IF") protected val IN = Keyword("IN") protected val INNER = Keyword("INNER") - protected val INT = Keyword("INT") protected val INSERT = Keyword("INSERT") protected val INTERSECT = Keyword("INTERSECT") protected val INTO = Keyword("INTO") @@ -105,13 +101,11 @@ class SqlParser extends AbstractSparkSQLParser { protected val SELECT = Keyword("SELECT") protected val SEMI = Keyword("SEMI") protected val SQRT = Keyword("SQRT") - protected val STRING = Keyword("STRING") protected val SUBSTR = Keyword("SUBSTR") protected val SUBSTRING = Keyword("SUBSTRING") protected val SUM = Keyword("SUM") protected val TABLE = Keyword("TABLE") protected val THEN = Keyword("THEN") - protected val TIMESTAMP = Keyword("TIMESTAMP") protected val TRUE = Keyword("TRUE") protected val UNION = Keyword("UNION") protected val UPPER = Keyword("UPPER") @@ -315,7 +309,9 @@ class SqlParser extends AbstractSparkSQLParser { ) protected lazy val cast: Parser[Expression] = - CAST ~ "(" ~> expression ~ (AS ~> dataType) <~ ")" ^^ { case exp ~ t => Cast(exp, t) } + CAST ~ "(" ~> expression ~ (AS ~> dataType) <~ ")" ^^ { + case exp ~ t => Cast(exp, t) + } protected lazy val literal: Parser[Literal] = ( numericLiteral @@ -387,19 +383,4 @@ class SqlParser extends AbstractSparkSQLParser { (ident <~ ".") ~ ident ~ rep("." ~> ident) ^^ { case i1 ~ i2 ~ rest => UnresolvedAttribute((Seq(i1, i2) ++ rest).mkString(".")) } - - protected lazy val dataType: Parser[DataType] = - ( STRING ^^^ StringType - | TIMESTAMP ^^^ TimestampType - | DOUBLE ^^^ DoubleType - | fixedDecimalType - | DECIMAL ^^^ DecimalType.Unlimited - | DATE ^^^ DateType - | INT ^^^ IntegerType - ) - - protected lazy val fixedDecimalType: Parser[DataType] = - (DECIMAL ~ "(" ~> numericLit) ~ ("," ~> numericLit <~ ")") ^^ { - case precision ~ scale => DecimalType(precision.toInt, scale.toInt) - } } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeParser.scala new file mode 100644 index 0000000000..89278f7dbc --- /dev/null +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeParser.scala @@ -0,0 +1,115 @@ +/* + * 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.types + +import scala.language.implicitConversions +import scala.util.matching.Regex +import scala.util.parsing.combinator.syntactical.StandardTokenParsers + +import org.apache.spark.sql.catalyst.SqlLexical + +/** + * This is a data type parser that can be used to parse string representations of data types + * provided in SQL queries. This parser is mixed in with DDLParser and SqlParser. + */ +private[sql] trait DataTypeParser extends StandardTokenParsers { + + // This is used to create a parser from a regex. We are using regexes for data type strings + // since these strings can be also used as column names or field names. + import lexical.Identifier + implicit def regexToParser(regex: Regex): Parser[String] = acceptMatch( + s"identifier matching regex ${regex}", + { case Identifier(str) if regex.unapplySeq(str).isDefined => str } + ) + + protected lazy val primitiveType: Parser[DataType] = + "(?i)string".r ^^^ StringType | + "(?i)float".r ^^^ FloatType | + "(?i)int".r ^^^ IntegerType | + "(?i)tinyint".r ^^^ ByteType | + "(?i)smallint".r ^^^ ShortType | + "(?i)double".r ^^^ DoubleType | + "(?i)bigint".r ^^^ LongType | + "(?i)binary".r ^^^ BinaryType | + "(?i)boolean".r ^^^ BooleanType | + fixedDecimalType | + "(?i)decimal".r ^^^ DecimalType.Unlimited | + "(?i)date".r ^^^ DateType | + "(?i)timestamp".r ^^^ TimestampType | + varchar + + protected lazy val fixedDecimalType: Parser[DataType] = + ("(?i)decimal".r ~> "(" ~> numericLit) ~ ("," ~> numericLit <~ ")") ^^ { + case precision ~ scale => + DecimalType(precision.toInt, scale.toInt) + } + + protected lazy val varchar: Parser[DataType] = + "(?i)varchar".r ~> "(" ~> (numericLit <~ ")") ^^^ StringType + + protected lazy val arrayType: Parser[DataType] = + "(?i)array".r ~> "<" ~> dataType <~ ">" ^^ { + case tpe => ArrayType(tpe) + } + + protected lazy val mapType: Parser[DataType] = + "(?i)map".r ~> "<" ~> dataType ~ "," ~ dataType <~ ">" ^^ { + case t1 ~ _ ~ t2 => MapType(t1, t2) + } + + protected lazy val structField: Parser[StructField] = + ident ~ ":" ~ dataType ^^ { + case name ~ _ ~ tpe => StructField(name, tpe, nullable = true) + } + + protected lazy val structType: Parser[DataType] = + ("(?i)struct".r ~> "<" ~> repsep(structField, ",") <~ ">" ^^ { + case fields => new StructType(fields.toArray) + }) | + ("(?i)struct".r ~ "<>" ^^^ StructType(Nil)) + + protected lazy val dataType: Parser[DataType] = + arrayType | + mapType | + structType | + primitiveType + + def toDataType(dataTypeString: String): DataType = synchronized { + phrase(dataType)(new lexical.Scanner(dataTypeString)) match { + case Success(result, _) => result + case failure: NoSuccess => throw new DataTypeException(failMessage(dataTypeString)) + } + } + + private def failMessage(dataTypeString: String): String = { + s"Unsupported dataType: $dataTypeString. If you have a struct and a field name of it has " + + "any special characters, please use backticks (`) to quote that field name, e.g. `x+y`. " + + "Please note that backtick itself is not supported in a field name." + } +} + +private[sql] object DataTypeParser { + lazy val dataTypeParser = new DataTypeParser { + override val lexical = new SqlLexical + } + + def apply(dataTypeString: String): DataType = dataTypeParser.toDataType(dataTypeString) +} + +/** The exception thrown from the [[DataTypeParser]]. */ +protected[sql] class DataTypeException(message: String) extends Exception(message) diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeParserSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeParserSuite.scala new file mode 100644 index 0000000000..1ba21b6460 --- /dev/null +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeParserSuite.scala @@ -0,0 +1,116 @@ +/* +* 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.types + +import org.scalatest.FunSuite + +class DataTypeParserSuite extends FunSuite { + + def checkDataType(dataTypeString: String, expectedDataType: DataType): Unit = { + test(s"parse ${dataTypeString.replace("\n", "")}") { + assert(DataTypeParser(dataTypeString) === expectedDataType) + } + } + + def unsupported(dataTypeString: String): Unit = { + test(s"$dataTypeString is not supported") { + intercept[DataTypeException](DataTypeParser(dataTypeString)) + } + } + + checkDataType("int", IntegerType) + checkDataType("BooLean", BooleanType) + checkDataType("tinYint", ByteType) + checkDataType("smallINT", ShortType) + checkDataType("INT", IntegerType) + checkDataType("bigint", LongType) + checkDataType("float", FloatType) + checkDataType("dOUBle", DoubleType) + checkDataType("decimal(10, 5)", DecimalType(10, 5)) + checkDataType("decimal", DecimalType.Unlimited) + checkDataType("DATE", DateType) + checkDataType("timestamp", TimestampType) + checkDataType("string", StringType) + checkDataType("varchAr(20)", StringType) + checkDataType("BINARY", BinaryType) + + checkDataType("array<doublE>", ArrayType(DoubleType, true)) + checkDataType("Array<map<int, tinYint>>", ArrayType(MapType(IntegerType, ByteType, true), true)) + checkDataType( + "array<struct<tinYint:tinyint>>", + ArrayType(StructType(StructField("tinYint", ByteType, true) :: Nil), true) + ) + checkDataType("MAP<int, STRING>", MapType(IntegerType, StringType, true)) + checkDataType("MAp<int, ARRAY<double>>", MapType(IntegerType, ArrayType(DoubleType), true)) + checkDataType( + "MAP<int, struct<varchar:string>>", + MapType(IntegerType, StructType(StructField("varchar", StringType, true) :: Nil), true) + ) + + checkDataType( + "struct<intType: int, ts:timestamp>", + StructType( + StructField("intType", IntegerType, true) :: + StructField("ts", TimestampType, true) :: Nil) + ) + // It is fine to use the data type string as the column name. + checkDataType( + "Struct<int: int, timestamp:timestamp>", + StructType( + StructField("int", IntegerType, true) :: + StructField("timestamp", TimestampType, true) :: Nil) + ) + checkDataType( + """ + |struct< + | struct:struct<deciMal:DECimal, anotherDecimal:decimAL(5,2)>, + | MAP:Map<timestamp, varchar(10)>, + | arrAy:Array<double>> + """.stripMargin, + StructType( + StructField("struct", + StructType( + StructField("deciMal", DecimalType.Unlimited, true) :: + StructField("anotherDecimal", DecimalType(5, 2), true) :: Nil), true) :: + StructField("MAP", MapType(TimestampType, StringType), true) :: + StructField("arrAy", ArrayType(DoubleType, true), true) :: Nil) + ) + // A column name can be a reserved word in our DDL parser and SqlParser. + checkDataType( + "Struct<TABLE: string, CASE:boolean>", + StructType( + StructField("TABLE", StringType, true) :: + StructField("CASE", BooleanType, true) :: Nil) + ) + // Use backticks to quote column names having special characters. + checkDataType( + "struct<`x+y`:int, `!@#$%^&*()`:string, `1_2.345<>:\"`:varchar(20)>", + StructType( + StructField("x+y", IntegerType, true) :: + StructField("!@#$%^&*()", StringType, true) :: + StructField("1_2.345<>:\"", StringType, true) :: Nil) + ) + // Empty struct. + checkDataType("strUCt<>", StructType(Nil)) + + unsupported("it is not a data type") + unsupported("struct<x+y: int, 1.1:timestamp>") + unsupported("struct<x: int") + unsupported("struct<x int, y string>") + unsupported("struct<`x``y` int>") +} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/Column.scala b/sql/core/src/main/scala/org/apache/spark/sql/Column.scala index b7a13a1b26..ec7d15f5bc 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/Column.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/Column.scala @@ -624,20 +624,7 @@ class Column(protected[sql] val expr: Expression) { * * @group expr_ops */ - def cast(to: String): Column = cast(to.toLowerCase match { - case "string" | "str" => StringType - case "boolean" => BooleanType - case "byte" => ByteType - case "short" => ShortType - case "int" => IntegerType - case "long" => LongType - case "float" => FloatType - case "double" => DoubleType - case "decimal" => DecimalType.Unlimited - case "date" => DateType - case "timestamp" => TimestampType - case _ => throw new RuntimeException(s"""Unsupported cast type: "$to"""") - }) + def cast(to: String): Column = cast(DataTypeParser(to)) /** * Returns an ordering used in sorting. 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 d57406645e..d2e807d3a6 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 @@ -34,7 +34,8 @@ import org.apache.spark.util.Utils * A parser for foreign DDL commands. */ private[sql] class DDLParser( - parseQuery: String => LogicalPlan) extends AbstractSparkSQLParser with Logging { + parseQuery: String => LogicalPlan) + extends AbstractSparkSQLParser with DataTypeParser with Logging { def apply(input: String, exceptionOnError: Boolean): Option[LogicalPlan] = { try { @@ -46,14 +47,6 @@ private[sql] class DDLParser( } } - def parseType(input: String): DataType = { - lexical.initialize(reservedWords) - phrase(dataType)(new lexical.Scanner(input)) match { - case Success(r, x) => r - case x => throw new DDLException(s"Unsupported dataType: $x") - } - } - // Keyword is a convention with AbstractSparkSQLParser, which will scan all of the `Keyword` // properties via reflection the class in runtime for constructing the SqlLexical object protected val CREATE = Keyword("CREATE") @@ -70,24 +63,6 @@ private[sql] class DDLParser( protected val COMMENT = Keyword("COMMENT") protected val REFRESH = Keyword("REFRESH") - // Data types. - protected val STRING = Keyword("STRING") - protected val BINARY = Keyword("BINARY") - protected val BOOLEAN = Keyword("BOOLEAN") - protected val TINYINT = Keyword("TINYINT") - protected val SMALLINT = Keyword("SMALLINT") - protected val INT = Keyword("INT") - protected val BIGINT = Keyword("BIGINT") - protected val FLOAT = Keyword("FLOAT") - protected val DOUBLE = Keyword("DOUBLE") - protected val DECIMAL = Keyword("DECIMAL") - protected val DATE = Keyword("DATE") - protected val TIMESTAMP = Keyword("TIMESTAMP") - protected val VARCHAR = Keyword("VARCHAR") - protected val ARRAY = Keyword("ARRAY") - protected val MAP = Keyword("MAP") - protected val STRUCT = Keyword("STRUCT") - protected lazy val ddl: Parser[LogicalPlan] = createTable | describeTable | refreshTable protected def start: Parser[LogicalPlan] = ddl @@ -189,58 +164,9 @@ private[sql] class DDLParser( new MetadataBuilder().putString(COMMENT.str.toLowerCase, comment).build() case None => Metadata.empty } - StructField(columnName, typ, nullable = true, meta) - } - - protected lazy val primitiveType: Parser[DataType] = - STRING ^^^ StringType | - BINARY ^^^ BinaryType | - BOOLEAN ^^^ BooleanType | - TINYINT ^^^ ByteType | - SMALLINT ^^^ ShortType | - INT ^^^ IntegerType | - BIGINT ^^^ LongType | - FLOAT ^^^ FloatType | - DOUBLE ^^^ DoubleType | - fixedDecimalType | // decimal with precision/scale - DECIMAL ^^^ DecimalType.Unlimited | // decimal with no precision/scale - DATE ^^^ DateType | - TIMESTAMP ^^^ TimestampType | - VARCHAR ~ "(" ~ numericLit ~ ")" ^^^ StringType - - protected lazy val fixedDecimalType: Parser[DataType] = - (DECIMAL ~ "(" ~> numericLit) ~ ("," ~> numericLit <~ ")") ^^ { - case precision ~ scale => DecimalType(precision.toInt, scale.toInt) - } - - protected lazy val arrayType: Parser[DataType] = - ARRAY ~> "<" ~> dataType <~ ">" ^^ { - case tpe => ArrayType(tpe) - } - protected lazy val mapType: Parser[DataType] = - MAP ~> "<" ~> dataType ~ "," ~ dataType <~ ">" ^^ { - case t1 ~ _ ~ t2 => MapType(t1, t2) - } - - protected lazy val structField: Parser[StructField] = - ident ~ ":" ~ dataType ^^ { - case fieldName ~ _ ~ tpe => StructField(fieldName, tpe, nullable = true) + StructField(columnName, typ, nullable = true, meta) } - - protected lazy val structType: Parser[DataType] = - (STRUCT ~> "<" ~> repsep(structField, ",") <~ ">" ^^ { - case fields => StructType(fields) - }) | - (STRUCT ~> "<>" ^^ { - case fields => StructType(Nil) - }) - - private[sql] lazy val dataType: Parser[DataType] = - arrayType | - mapType | - structType | - primitiveType } private[sql] object ResolvedDataSource { 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 fe86bd206a..949a4e54e6 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 @@ -756,7 +756,7 @@ private[hive] case class MetastoreRelation implicit class SchemaAttribute(f: FieldSchema) { def toAttribute = AttributeReference( f.getName, - sqlContext.ddlParser.parseType(f.getType), + HiveMetastoreTypes.toDataType(f.getType), // Since data can be dumped in randomly with no validation, everything is nullable. nullable = true )(qualifiers = Seq(alias.getOrElse(tableName))) @@ -779,11 +779,7 @@ private[hive] case class MetastoreRelation private[hive] object HiveMetastoreTypes { - protected val ddlParser = new DDLParser(HiveQl.parseSql(_)) - - def toDataType(metastoreType: String): DataType = synchronized { - ddlParser.parseType(metastoreType) - } + def toDataType(metastoreType: String): DataType = DataTypeParser(metastoreType) def toMetastoreType(dt: DataType): String = dt match { case ArrayType(elementType, _) => s"array<${toMetastoreType(elementType)}>" |