[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.
This commit is contained in:
Yin Huai
Michael Armbrust
parent
ee569a0c71
commit
94a102acb8
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@ -35,7 +35,7 @@ import org.apache.spark.sql.types._
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* This is currently included mostly for illustrative purposes. Users wanting more complete support
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* for a SQL like language should checkout the HiveQL support in the sql/hive sub-project.
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*/
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class SqlParser extends AbstractSparkSQLParser {
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class SqlParser extends AbstractSparkSQLParser with DataTypeParser {
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def parseExpression(input: String): Expression = {
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// Initialize the Keywords.
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@ -61,11 +61,8 @@ class SqlParser extends AbstractSparkSQLParser {
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protected val CAST = Keyword("CAST")
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protected val COALESCE = Keyword("COALESCE")
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protected val COUNT = Keyword("COUNT")
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protected val DATE = Keyword("DATE")
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protected val DECIMAL = Keyword("DECIMAL")
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protected val DESC = Keyword("DESC")
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protected val DISTINCT = Keyword("DISTINCT")
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protected val DOUBLE = Keyword("DOUBLE")
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protected val ELSE = Keyword("ELSE")
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protected val END = Keyword("END")
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protected val EXCEPT = Keyword("EXCEPT")
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@ -78,7 +75,6 @@ class SqlParser extends AbstractSparkSQLParser {
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protected val IF = Keyword("IF")
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protected val IN = Keyword("IN")
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protected val INNER = Keyword("INNER")
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protected val INT = Keyword("INT")
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protected val INSERT = Keyword("INSERT")
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protected val INTERSECT = Keyword("INTERSECT")
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protected val INTO = Keyword("INTO")
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@ -105,13 +101,11 @@ class SqlParser extends AbstractSparkSQLParser {
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protected val SELECT = Keyword("SELECT")
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protected val SEMI = Keyword("SEMI")
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protected val SQRT = Keyword("SQRT")
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protected val STRING = Keyword("STRING")
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protected val SUBSTR = Keyword("SUBSTR")
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protected val SUBSTRING = Keyword("SUBSTRING")
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protected val SUM = Keyword("SUM")
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protected val TABLE = Keyword("TABLE")
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protected val THEN = Keyword("THEN")
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protected val TIMESTAMP = Keyword("TIMESTAMP")
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protected val TRUE = Keyword("TRUE")
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protected val UNION = Keyword("UNION")
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protected val UPPER = Keyword("UPPER")
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@ -315,7 +309,9 @@ class SqlParser extends AbstractSparkSQLParser {
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)
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protected lazy val cast: Parser[Expression] =
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CAST ~ "(" ~> expression ~ (AS ~> dataType) <~ ")" ^^ { case exp ~ t => Cast(exp, t) }
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CAST ~ "(" ~> expression ~ (AS ~> dataType) <~ ")" ^^ {
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case exp ~ t => Cast(exp, t)
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}
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protected lazy val literal: Parser[Literal] =
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( numericLiteral
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@ -387,19 +383,4 @@ class SqlParser extends AbstractSparkSQLParser {
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(ident <~ ".") ~ ident ~ rep("." ~> ident) ^^ {
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case i1 ~ i2 ~ rest => UnresolvedAttribute((Seq(i1, i2) ++ rest).mkString("."))
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}
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protected lazy val dataType: Parser[DataType] =
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( STRING ^^^ StringType
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| TIMESTAMP ^^^ TimestampType
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| DOUBLE ^^^ DoubleType
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| fixedDecimalType
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| DECIMAL ^^^ DecimalType.Unlimited
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| DATE ^^^ DateType
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| INT ^^^ IntegerType
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)
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protected lazy val fixedDecimalType: Parser[DataType] =
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(DECIMAL ~ "(" ~> numericLit) ~ ("," ~> numericLit <~ ")") ^^ {
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case precision ~ scale => DecimalType(precision.toInt, scale.toInt)
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}
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}
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@ -0,0 +1,115 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.spark.sql.types
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import scala.language.implicitConversions
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import scala.util.matching.Regex
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import scala.util.parsing.combinator.syntactical.StandardTokenParsers
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import org.apache.spark.sql.catalyst.SqlLexical
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/**
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* This is a data type parser that can be used to parse string representations of data types
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* provided in SQL queries. This parser is mixed in with DDLParser and SqlParser.
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*/
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private[sql] trait DataTypeParser extends StandardTokenParsers {
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// This is used to create a parser from a regex. We are using regexes for data type strings
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// since these strings can be also used as column names or field names.
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import lexical.Identifier
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implicit def regexToParser(regex: Regex): Parser[String] = acceptMatch(
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s"identifier matching regex ${regex}",
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{ case Identifier(str) if regex.unapplySeq(str).isDefined => str }
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)
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protected lazy val primitiveType: Parser[DataType] =
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"(?i)string".r ^^^ StringType |
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"(?i)float".r ^^^ FloatType |
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"(?i)int".r ^^^ IntegerType |
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"(?i)tinyint".r ^^^ ByteType |
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"(?i)smallint".r ^^^ ShortType |
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"(?i)double".r ^^^ DoubleType |
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"(?i)bigint".r ^^^ LongType |
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"(?i)binary".r ^^^ BinaryType |
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"(?i)boolean".r ^^^ BooleanType |
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fixedDecimalType |
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"(?i)decimal".r ^^^ DecimalType.Unlimited |
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"(?i)date".r ^^^ DateType |
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"(?i)timestamp".r ^^^ TimestampType |
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varchar
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protected lazy val fixedDecimalType: Parser[DataType] =
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("(?i)decimal".r ~> "(" ~> numericLit) ~ ("," ~> numericLit <~ ")") ^^ {
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case precision ~ scale =>
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DecimalType(precision.toInt, scale.toInt)
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}
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protected lazy val varchar: Parser[DataType] =
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"(?i)varchar".r ~> "(" ~> (numericLit <~ ")") ^^^ StringType
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protected lazy val arrayType: Parser[DataType] =
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"(?i)array".r ~> "<" ~> dataType <~ ">" ^^ {
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case tpe => ArrayType(tpe)
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}
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protected lazy val mapType: Parser[DataType] =
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"(?i)map".r ~> "<" ~> dataType ~ "," ~ dataType <~ ">" ^^ {
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case t1 ~ _ ~ t2 => MapType(t1, t2)
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}
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protected lazy val structField: Parser[StructField] =
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ident ~ ":" ~ dataType ^^ {
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case name ~ _ ~ tpe => StructField(name, tpe, nullable = true)
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}
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protected lazy val structType: Parser[DataType] =
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("(?i)struct".r ~> "<" ~> repsep(structField, ",") <~ ">" ^^ {
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case fields => new StructType(fields.toArray)
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}) |
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("(?i)struct".r ~ "<>" ^^^ StructType(Nil))
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protected lazy val dataType: Parser[DataType] =
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arrayType |
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mapType |
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structType |
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primitiveType
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def toDataType(dataTypeString: String): DataType = synchronized {
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phrase(dataType)(new lexical.Scanner(dataTypeString)) match {
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case Success(result, _) => result
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case failure: NoSuccess => throw new DataTypeException(failMessage(dataTypeString))
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}
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}
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private def failMessage(dataTypeString: String): String = {
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s"Unsupported dataType: $dataTypeString. If you have a struct and a field name of it has " +
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"any special characters, please use backticks (`) to quote that field name, e.g. `x+y`. " +
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"Please note that backtick itself is not supported in a field name."
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}
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}
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private[sql] object DataTypeParser {
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lazy val dataTypeParser = new DataTypeParser {
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override val lexical = new SqlLexical
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}
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def apply(dataTypeString: String): DataType = dataTypeParser.toDataType(dataTypeString)
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}
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/** The exception thrown from the [[DataTypeParser]]. */
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protected[sql] class DataTypeException(message: String) extends Exception(message)
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@ -0,0 +1,116 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.spark.sql.types
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import org.scalatest.FunSuite
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class DataTypeParserSuite extends FunSuite {
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def checkDataType(dataTypeString: String, expectedDataType: DataType): Unit = {
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test(s"parse ${dataTypeString.replace("\n", "")}") {
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assert(DataTypeParser(dataTypeString) === expectedDataType)
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}
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}
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def unsupported(dataTypeString: String): Unit = {
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test(s"$dataTypeString is not supported") {
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intercept[DataTypeException](DataTypeParser(dataTypeString))
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}
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}
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checkDataType("int", IntegerType)
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checkDataType("BooLean", BooleanType)
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checkDataType("tinYint", ByteType)
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checkDataType("smallINT", ShortType)
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checkDataType("INT", IntegerType)
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checkDataType("bigint", LongType)
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checkDataType("float", FloatType)
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checkDataType("dOUBle", DoubleType)
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checkDataType("decimal(10, 5)", DecimalType(10, 5))
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checkDataType("decimal", DecimalType.Unlimited)
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checkDataType("DATE", DateType)
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checkDataType("timestamp", TimestampType)
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checkDataType("string", StringType)
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checkDataType("varchAr(20)", StringType)
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checkDataType("BINARY", BinaryType)
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checkDataType("array<doublE>", ArrayType(DoubleType, true))
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checkDataType("Array<map<int, tinYint>>", ArrayType(MapType(IntegerType, ByteType, true), true))
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checkDataType(
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"array<struct<tinYint:tinyint>>",
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ArrayType(StructType(StructField("tinYint", ByteType, true) :: Nil), true)
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)
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checkDataType("MAP<int, STRING>", MapType(IntegerType, StringType, true))
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checkDataType("MAp<int, ARRAY<double>>", MapType(IntegerType, ArrayType(DoubleType), true))
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checkDataType(
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"MAP<int, struct<varchar:string>>",
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MapType(IntegerType, StructType(StructField("varchar", StringType, true) :: Nil), true)
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)
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checkDataType(
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"struct<intType: int, ts:timestamp>",
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StructType(
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StructField("intType", IntegerType, true) ::
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StructField("ts", TimestampType, true) :: Nil)
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)
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// It is fine to use the data type string as the column name.
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checkDataType(
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"Struct<int: int, timestamp:timestamp>",
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StructType(
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StructField("int", IntegerType, true) ::
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StructField("timestamp", TimestampType, true) :: Nil)
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)
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checkDataType(
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"""
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|struct<
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| struct:struct<deciMal:DECimal, anotherDecimal:decimAL(5,2)>,
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| MAP:Map<timestamp, varchar(10)>,
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| arrAy:Array<double>>
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""".stripMargin,
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StructType(
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StructField("struct",
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StructType(
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StructField("deciMal", DecimalType.Unlimited, true) ::
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StructField("anotherDecimal", DecimalType(5, 2), true) :: Nil), true) ::
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StructField("MAP", MapType(TimestampType, StringType), true) ::
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StructField("arrAy", ArrayType(DoubleType, true), true) :: Nil)
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)
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// A column name can be a reserved word in our DDL parser and SqlParser.
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checkDataType(
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"Struct<TABLE: string, CASE:boolean>",
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StructType(
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StructField("TABLE", StringType, true) ::
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StructField("CASE", BooleanType, true) :: Nil)
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)
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// Use backticks to quote column names having special characters.
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checkDataType(
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"struct<`x+y`:int, `!@#$%^&*()`:string, `1_2.345<>:\"`:varchar(20)>",
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StructType(
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StructField("x+y", IntegerType, true) ::
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StructField("!@#$%^&*()", StringType, true) ::
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StructField("1_2.345<>:\"", StringType, true) :: Nil)
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)
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// Empty struct.
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checkDataType("strUCt<>", StructType(Nil))
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unsupported("it is not a data type")
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unsupported("struct<x+y: int, 1.1:timestamp>")
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unsupported("struct<x: int")
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unsupported("struct<x int, y string>")
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unsupported("struct<`x``y` int>")
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}
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@ -624,20 +624,7 @@ class Column(protected[sql] val expr: Expression) {
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*
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* @group expr_ops
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*/
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def cast(to: String): Column = cast(to.toLowerCase match {
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case "string" | "str" => StringType
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case "boolean" => BooleanType
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case "byte" => ByteType
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case "short" => ShortType
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case "int" => IntegerType
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case "long" => LongType
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case "float" => FloatType
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case "double" => DoubleType
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case "decimal" => DecimalType.Unlimited
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case "date" => DateType
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case "timestamp" => TimestampType
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case _ => throw new RuntimeException(s"""Unsupported cast type: "$to"""")
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})
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def cast(to: String): Column = cast(DataTypeParser(to))
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/**
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* Returns an ordering used in sorting.
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@ -34,7 +34,8 @@ import org.apache.spark.util.Utils
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* A parser for foreign DDL commands.
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*/
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private[sql] class DDLParser(
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parseQuery: String => LogicalPlan) extends AbstractSparkSQLParser with Logging {
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parseQuery: String => LogicalPlan)
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extends AbstractSparkSQLParser with DataTypeParser with Logging {
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def apply(input: String, exceptionOnError: Boolean): Option[LogicalPlan] = {
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try {
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@ -46,14 +47,6 @@ private[sql] class DDLParser(
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}
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}
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def parseType(input: String): DataType = {
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lexical.initialize(reservedWords)
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phrase(dataType)(new lexical.Scanner(input)) match {
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case Success(r, x) => r
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case x => throw new DDLException(s"Unsupported dataType: $x")
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}
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}
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// Keyword is a convention with AbstractSparkSQLParser, which will scan all of the `Keyword`
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// properties via reflection the class in runtime for constructing the SqlLexical object
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protected val CREATE = Keyword("CREATE")
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@ -70,24 +63,6 @@ private[sql] class DDLParser(
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protected val COMMENT = Keyword("COMMENT")
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protected val REFRESH = Keyword("REFRESH")
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// Data types.
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protected val STRING = Keyword("STRING")
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protected val BINARY = Keyword("BINARY")
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protected val BOOLEAN = Keyword("BOOLEAN")
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protected val TINYINT = Keyword("TINYINT")
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protected val SMALLINT = Keyword("SMALLINT")
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protected val INT = Keyword("INT")
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protected val BIGINT = Keyword("BIGINT")
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protected val FLOAT = Keyword("FLOAT")
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protected val DOUBLE = Keyword("DOUBLE")
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protected val DECIMAL = Keyword("DECIMAL")
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protected val DATE = Keyword("DATE")
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protected val TIMESTAMP = Keyword("TIMESTAMP")
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protected val VARCHAR = Keyword("VARCHAR")
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protected val ARRAY = Keyword("ARRAY")
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protected val MAP = Keyword("MAP")
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protected val STRUCT = Keyword("STRUCT")
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protected lazy val ddl: Parser[LogicalPlan] = createTable | describeTable | refreshTable
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protected def start: Parser[LogicalPlan] = ddl
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@ -189,58 +164,9 @@ private[sql] class DDLParser(
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new MetadataBuilder().putString(COMMENT.str.toLowerCase, comment).build()
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case None => Metadata.empty
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}
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StructField(columnName, typ, nullable = true, meta)
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}
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protected lazy val primitiveType: Parser[DataType] =
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STRING ^^^ StringType |
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BINARY ^^^ BinaryType |
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BOOLEAN ^^^ BooleanType |
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TINYINT ^^^ ByteType |
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SMALLINT ^^^ ShortType |
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INT ^^^ IntegerType |
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BIGINT ^^^ LongType |
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FLOAT ^^^ FloatType |
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DOUBLE ^^^ DoubleType |
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fixedDecimalType | // decimal with precision/scale
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DECIMAL ^^^ DecimalType.Unlimited | // decimal with no precision/scale
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DATE ^^^ DateType |
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TIMESTAMP ^^^ TimestampType |
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VARCHAR ~ "(" ~ numericLit ~ ")" ^^^ StringType
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protected lazy val fixedDecimalType: Parser[DataType] =
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(DECIMAL ~ "(" ~> numericLit) ~ ("," ~> numericLit <~ ")") ^^ {
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case precision ~ scale => DecimalType(precision.toInt, scale.toInt)
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}
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protected lazy val arrayType: Parser[DataType] =
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ARRAY ~> "<" ~> dataType <~ ">" ^^ {
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case tpe => ArrayType(tpe)
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}
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protected lazy val mapType: Parser[DataType] =
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MAP ~> "<" ~> dataType ~ "," ~ dataType <~ ">" ^^ {
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case t1 ~ _ ~ t2 => MapType(t1, t2)
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}
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|
||||
protected lazy val structField: Parser[StructField] =
|
||||
ident ~ ":" ~ dataType ^^ {
|
||||
case fieldName ~ _ ~ tpe => StructField(fieldName, tpe, nullable = true)
|
||||
}
|
||||
|
||||
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 {
|
||||
|
|
|
|||
|
|
@ -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)}>"
|
||||
|
|
|
|||
Loading…
Reference in a new issue