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[SPARK-19254][SQL] Support Seq, Map, and Struct in functions.lit #16610

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ca2e07f
Add a new create with TypeTag in Literal
maropu Nov 14, 2016
8d26e8b
Rename lit2 to typedlit
maropu Feb 9, 2017
4f65fe2
Apply review comments
maropu Feb 20, 2017
028b19b
Add tests in ColumnExpressionSuite
maropu Feb 20, 2017
af2d70a
Update desc in typedLit
maropu Mar 2, 2017
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9 changes: 8 additions & 1 deletion sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala
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Expand Up @@ -32,11 +32,12 @@ import java.util.Objects
import javax.xml.bind.DatatypeConverter

import scala.math.{BigDecimal, BigInt}
import scala.reflect.runtime.universe.TypeTag

import org.json4s.JsonAST._

import org.apache.spark.sql.AnalysisException
import org.apache.spark.sql.catalyst.{CatalystTypeConverters, InternalRow}
import org.apache.spark.sql.catalyst.{CatalystTypeConverters, InternalRow, ScalaReflection}
import org.apache.spark.sql.catalyst.expressions.codegen._
import org.apache.spark.sql.catalyst.util.DateTimeUtils
import org.apache.spark.sql.types._
Expand Down Expand Up @@ -153,6 +154,12 @@ object Literal {
Literal(CatalystTypeConverters.convertToCatalyst(v), dataType)
}

def create[T : TypeTag](v: T): Literal = {
val ScalaReflection.Schema(dataType, _) = ScalaReflection.schemaFor[T]
val convert = CatalystTypeConverters.createToCatalystConverter(dataType)
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@hvanhovell hvanhovell Feb 9, 2017

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Call create(v, dataType) instead?

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@maropu maropu Feb 9, 2017

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Aha, you're right. I'll fix this.

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@maropu maropu Feb 9, 2017

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Oh, my bad. I found the code you suggested made some tests fail. Actually, CatalystTypeConverters.convertToCatalyst does not do the same thing with CatalystTypeConverters.createToCatalystConverter(dataType). For instance, CatalystTypeConverters.convertToCatalyst does not convert TupleX to GenericInternalRow.

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@hvanhovell hvanhovell Feb 9, 2017

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Ah ok.

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@hvanhovell hvanhovell Feb 9, 2017

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Shouldn't you be going to talks :)

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@maropu maropu Feb 9, 2017

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haha, actually I'm joining the dev talk now ;)

Literal(convert(v), dataType)
}

/**
* Create a literal with default value for given DataType
*/
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90 changes: 79 additions & 11 deletions ...yst/src/test/scala/org/apache/spark/sql/catalyst/expressions/LiteralExpressionSuite.scala
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Expand Up @@ -19,9 +19,11 @@ package org.apache.spark.sql.catalyst.expressions

import java.nio.charset.StandardCharsets

import scala.reflect.runtime.universe.{typeTag, TypeTag}

import org.apache.spark.SparkFunSuite
import org.apache.spark.sql.Row
import org.apache.spark.sql.catalyst.CatalystTypeConverters
import org.apache.spark.sql.catalyst.{CatalystTypeConverters, ScalaReflection}
import org.apache.spark.sql.catalyst.encoders.ExamplePointUDT
import org.apache.spark.sql.catalyst.util.DateTimeUtils
import org.apache.spark.sql.types._
Expand Down Expand Up @@ -75,6 +77,9 @@ class LiteralExpressionSuite extends SparkFunSuite with ExpressionEvalHelper {
test("boolean literals") {
checkEvaluation(Literal(true), true)
checkEvaluation(Literal(false), false)

checkEvaluation(Literal.create(true), true)
checkEvaluation(Literal.create(false), false)
}

test("int literals") {
Expand All @@ -83,36 +88,60 @@ class LiteralExpressionSuite extends SparkFunSuite with ExpressionEvalHelper {
checkEvaluation(Literal(d.toLong), d.toLong)
checkEvaluation(Literal(d.toShort), d.toShort)
checkEvaluation(Literal(d.toByte), d.toByte)

checkEvaluation(Literal.create(d), d)
checkEvaluation(Literal.create(d.toLong), d.toLong)
checkEvaluation(Literal.create(d.toShort), d.toShort)
checkEvaluation(Literal.create(d.toByte), d.toByte)
}
checkEvaluation(Literal(Long.MinValue), Long.MinValue)
checkEvaluation(Literal(Long.MaxValue), Long.MaxValue)

checkEvaluation(Literal.create(Long.MinValue), Long.MinValue)
checkEvaluation(Literal.create(Long.MaxValue), Long.MaxValue)
}

test("double literals") {
List(0.0, -0.0, Double.NegativeInfinity, Double.PositiveInfinity).foreach { d =>
checkEvaluation(Literal(d), d)
checkEvaluation(Literal(d.toFloat), d.toFloat)

checkEvaluation(Literal.create(d), d)
checkEvaluation(Literal.create(d.toFloat), d.toFloat)
}
checkEvaluation(Literal(Double.MinValue), Double.MinValue)
checkEvaluation(Literal(Double.MaxValue), Double.MaxValue)
checkEvaluation(Literal(Float.MinValue), Float.MinValue)
checkEvaluation(Literal(Float.MaxValue), Float.MaxValue)

checkEvaluation(Literal.create(Double.MinValue), Double.MinValue)
checkEvaluation(Literal.create(Double.MaxValue), Double.MaxValue)
checkEvaluation(Literal.create(Float.MinValue), Float.MinValue)
checkEvaluation(Literal.create(Float.MaxValue), Float.MaxValue)

}

test("string literals") {
checkEvaluation(Literal(""), "")
checkEvaluation(Literal("test"), "test")
checkEvaluation(Literal("\u0000"), "\u0000")

checkEvaluation(Literal.create(""), "")
checkEvaluation(Literal.create("test"), "test")
checkEvaluation(Literal.create("\u0000"), "\u0000")
}

test("sum two literals") {
checkEvaluation(Add(Literal(1), Literal(1)), 2)
checkEvaluation(Add(Literal.create(1), Literal.create(1)), 2)
}

test("binary literals") {
checkEvaluation(Literal.create(new Array[Byte](0), BinaryType), new Array[Byte](0))
checkEvaluation(Literal.create(new Array[Byte](2), BinaryType), new Array[Byte](2))

checkEvaluation(Literal.create(new Array[Byte](0)), new Array[Byte](0))
checkEvaluation(Literal.create(new Array[Byte](2)), new Array[Byte](2))
}

test("decimal") {
Expand All @@ -124,24 +153,63 @@ class LiteralExpressionSuite extends SparkFunSuite with ExpressionEvalHelper {
Decimal((d * 1000L).toLong, 10, 3))
checkEvaluation(Literal(BigDecimal(d.toString)), Decimal(d))
checkEvaluation(Literal(new java.math.BigDecimal(d.toString)), Decimal(d))

checkEvaluation(Literal.create(Decimal(d)), Decimal(d))
checkEvaluation(Literal.create(Decimal(d.toInt)), Decimal(d.toInt))
checkEvaluation(Literal.create(Decimal(d.toLong)), Decimal(d.toLong))
checkEvaluation(Literal.create(Decimal((d * 1000L).toLong, 10, 3)),
Decimal((d * 1000L).toLong, 10, 3))
checkEvaluation(Literal.create(BigDecimal(d.toString)), Decimal(d))
checkEvaluation(Literal.create(new java.math.BigDecimal(d.toString)), Decimal(d))

}
}

private def toCatalyst[T: TypeTag](value: T): Any = {
val ScalaReflection.Schema(dataType, _) = ScalaReflection.schemaFor[T]
CatalystTypeConverters.createToCatalystConverter(dataType)(value)
}

test("array") {
def checkArrayLiteral(a: Array[_], elementType: DataType): Unit = {
val toCatalyst = (a: Array[_], elementType: DataType) => {
CatalystTypeConverters.createToCatalystConverter(ArrayType(elementType))(a)
}
checkEvaluation(Literal(a), toCatalyst(a, elementType))
def checkArrayLiteral[T: TypeTag](a: Array[T]): Unit = {
checkEvaluation(Literal(a), toCatalyst(a))
checkEvaluation(Literal.create(a), toCatalyst(a))
}
checkArrayLiteral(Array(1, 2, 3))
checkArrayLiteral(Array("a", "b", "c"))
checkArrayLiteral(Array(1.0, 4.0))
checkArrayLiteral(Array(CalendarInterval.MICROS_PER_DAY, CalendarInterval.MICROS_PER_HOUR))
}

test("seq") {
def checkSeqLiteral[T: TypeTag](a: Seq[T], elementType: DataType): Unit = {
checkEvaluation(Literal.create(a), toCatalyst(a))
}
checkArrayLiteral(Array(1, 2, 3), IntegerType)
checkArrayLiteral(Array("a", "b", "c"), StringType)
checkArrayLiteral(Array(1.0, 4.0), DoubleType)
checkArrayLiteral(Array(CalendarInterval.MICROS_PER_DAY, CalendarInterval.MICROS_PER_HOUR),
checkSeqLiteral(Seq(1, 2, 3), IntegerType)
checkSeqLiteral(Seq("a", "b", "c"), StringType)
checkSeqLiteral(Seq(1.0, 4.0), DoubleType)
checkSeqLiteral(Seq(CalendarInterval.MICROS_PER_DAY, CalendarInterval.MICROS_PER_HOUR),
CalendarIntervalType)
}

test("unsupported types (map and struct) in literals") {
test("map") {
def checkMapLiteral[T: TypeTag](m: T): Unit = {
checkEvaluation(Literal.create(m), toCatalyst(m))
}
checkMapLiteral(Map("a" -> 1, "b" -> 2, "c" -> 3))
checkMapLiteral(Map("1" -> 1.0, "2" -> 2.0, "3" -> 3.0))
}

test("struct") {
def checkStructLiteral[T: TypeTag](s: T): Unit = {
checkEvaluation(Literal.create(s), toCatalyst(s))
}
checkStructLiteral((1, 3.0, "abcde"))
checkStructLiteral(("de", 1, 2.0f))
checkStructLiteral((1, ("fgh", 3.0)))
}

test("unsupported types (map and struct) in Literal.apply") {
def checkUnsupportedTypeInLiteral(v: Any): Unit = {
val errMsgMap = intercept[RuntimeException] {
Literal(v)
Expand Down
21 changes: 21 additions & 0 deletions sql/core/src/main/scala/org/apache/spark/sql/functions.scala
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Expand Up @@ -102,6 +102,27 @@ object functions {
Column(literalExpr)
}

/**
* Creates a [[Column]] of literal value.
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@hvanhovell hvanhovell Mar 2, 2017

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We should explain when you want to use this method instead of lit.

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@maropu maropu Mar 2, 2017

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okay, I'll update

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@maropu maropu Mar 2, 2017

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updated

*
* The passed in object is returned directly if it is already a [[Column]].
* If the object is a Scala Symbol, it is converted into a [[Column]] also.
* Otherwise, a new [[Column]] is created to represent the literal value.
*
* @group normal_funcs
* @since 2.2.0
*/
def typedLit[T : TypeTag](literal: T): Column = {
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@hvanhovell hvanhovell Feb 20, 2017

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cc @cloud-fan WDYT?

literal match {
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@hvanhovell hvanhovell Feb 20, 2017 •
edited
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This match statement is slightly hair raising (I know this is copied from lit(..)), how about:

literal match {
  case c: Column => c
  case s: Symbol => new ColumnName(s.name)
  case _ => Column(Literal.create(literal))
}

You could also consider mapping the untyped lit(..) function to this function.

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@maropu maropu Feb 20, 2017

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okay, I'll update

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@maropu maropu Feb 20, 2017

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@hvanhovell How about the fix? 4f65fe2

case c: Column => return c
case s: Symbol => return new ColumnName(literal.asInstanceOf[Symbol].name)
case _ => // continue
}

val literalExpr = Literal.create(literal)
Column(literalExpr)
}

//////////////////////////////////////////////////////////////////////////////////////////////
// Sort functions
//////////////////////////////////////////////////////////////////////////////////////////////
Expand Down