From 43b15e01c46ea1971569f74c9201a55de39e8917 Mon Sep 17 00:00:00 2001
From: Wenchen Fan <wenchen@databricks.com>
Date: Fri, 25 Mar 2016 09:50:06 -0700
Subject: [PATCH] [SPARK-14061][SQL] implement CreateMap
## What changes were proposed in this pull request?
As we have `CreateArray` and `CreateStruct`, we should also have `CreateMap`. This PR adds the `CreateMap` expression, and the DataFrame API, and python API.
## How was this patch tested?
various new tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes #11879 from cloud-fan/create_map.
---
python/pyspark/sql/functions.py | 20 +++++
.../catalyst/analysis/FunctionRegistry.scala | 1 +
.../catalyst/analysis/HiveTypeCoercion.scala | 35 +++++++-
.../expressions/complexTypeCreator.scala | 83 ++++++++++++++++++-
.../sql/catalyst/util/ArrayBasedMapData.scala | 5 +-
.../ExpressionTypeCheckingSuite.scala | 16 +++-
.../analysis/HiveTypeCoercionSuite.scala | 61 ++++++++++++++
.../expressions/ComplexTypeSuite.scala | 40 +++++++++
.../org/apache/spark/sql/functions.scala | 11 +++
.../spark/sql/DataFrameComplexTypeSuite.scala | 8 +-
.../spark/sql/DataFrameFunctionsSuite.scala | 15 ++--
.../spark/sql/hive/ExpressionToSQLSuite.scala | 1 +
12 files changed, 277 insertions(+), 19 deletions(-)
diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py
index dee3d536be..f5d959ef98 100644
--- a/python/pyspark/sql/functions.py
+++ b/python/pyspark/sql/functions.py
@@ -1498,6 +1498,26 @@ def translate(srcCol, matching, replace):
# ---------------------- Collection functions ------------------------------
+@ignore_unicode_prefix
+@since(2.0)
+def create_map(*cols):
+ """Creates a new map column.
+
+ :param cols: list of column names (string) or list of :class:`Column` expressions that grouped
+ as key-value pairs, e.g. (key1, value1, key2, value2, ...).
+
+ >>> df.select(create_map('name', 'age').alias("map")).collect()
+ [Row(map={u'Alice': 2}), Row(map={u'Bob': 5})]
+ >>> df.select(create_map([df.name, df.age]).alias("map")).collect()
+ [Row(map={u'Alice': 2}), Row(map={u'Bob': 5})]
+ """
+ sc = SparkContext._active_spark_context
+ if len(cols) == 1 and isinstance(cols[0], (list, set)):
+ cols = cols[0]
+ jc = sc._jvm.functions.map(_to_seq(sc, cols, _to_java_column))
+ return Column(jc)
+
+
@since(1.4)
def array(*cols):
"""Creates a new array column.
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
index 26bb96eb08..f584a4b73a 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
@@ -126,6 +126,7 @@ object FunctionRegistry {
expression[IsNull]("isnull"),
expression[IsNotNull]("isnotnull"),
expression[Least]("least"),
+ expression[CreateMap]("map"),
expression[CreateNamedStruct]("named_struct"),
expression[NaNvl]("nanvl"),
expression[Coalesce]("nvl"),
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala
index 0f85f44ffa..823d2495fa 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala
@@ -160,6 +160,9 @@ object HiveTypeCoercion {
})
}
+ private def haveSameType(exprs: Seq[Expression]): Boolean =
+ exprs.map(_.dataType).distinct.length == 1
+
/**
* Applies any changes to [[AttributeReference]] data types that are made by other rules to
* instances higher in the query tree.
@@ -443,13 +446,37 @@ object HiveTypeCoercion {
// Skip nodes who's children have not been resolved yet.
case e if !e.childrenResolved => e
- case a @ CreateArray(children) if children.map(_.dataType).distinct.size > 1 =>
+ case a @ CreateArray(children) if !haveSameType(children) =>
val types = children.map(_.dataType)
findTightestCommonTypeAndPromoteToString(types) match {
case Some(finalDataType) => CreateArray(children.map(Cast(_, finalDataType)))
case None => a
}
+ case m @ CreateMap(children) if m.keys.length == m.values.length &&
+ (!haveSameType(m.keys) || !haveSameType(m.values)) =>
+ val newKeys = if (haveSameType(m.keys)) {
+ m.keys
+ } else {
+ val types = m.keys.map(_.dataType)
+ findTightestCommonTypeAndPromoteToString(types) match {
+ case Some(finalDataType) => m.keys.map(Cast(_, finalDataType))
+ case None => m.keys
+ }
+ }
+
+ val newValues = if (haveSameType(m.values)) {
+ m.values
+ } else {
+ val types = m.values.map(_.dataType)
+ findTightestCommonTypeAndPromoteToString(types) match {
+ case Some(finalDataType) => m.values.map(Cast(_, finalDataType))
+ case None => m.values
+ }
+ }
+
+ CreateMap(newKeys.zip(newValues).flatMap { case (k, v) => Seq(k, v) })
+
// Promote SUM, SUM DISTINCT and AVERAGE to largest types to prevent overflows.
case s @ Sum(e @ DecimalType()) => s // Decimal is already the biggest.
case Sum(e @ IntegralType()) if e.dataType != LongType => Sum(Cast(e, LongType))
@@ -468,21 +495,21 @@ object HiveTypeCoercion {
// Coalesce should return the first non-null value, which could be any column
// from the list. So we need to make sure the return type is deterministic and
// compatible with every child column.
- case c @ Coalesce(es) if es.map(_.dataType).distinct.size > 1 =>
+ case c @ Coalesce(es) if !haveSameType(es) =>
val types = es.map(_.dataType)
findWiderCommonType(types) match {
case Some(finalDataType) => Coalesce(es.map(Cast(_, finalDataType)))
case None => c
}
- case g @ Greatest(children) if children.map(_.dataType).distinct.size > 1 =>
+ case g @ Greatest(children) if !haveSameType(children) =>
val types = children.map(_.dataType)
findTightestCommonType(types) match {
case Some(finalDataType) => Greatest(children.map(Cast(_, finalDataType)))
case None => g
}
- case l @ Least(children) if children.map(_.dataType).distinct.size > 1 =>
+ case l @ Least(children) if !haveSameType(children) =>
val types = children.map(_.dataType)
findTightestCommonType(types) match {
case Some(finalDataType) => Least(children.map(Cast(_, finalDataType)))
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala
index efd75295b2..c299586dde 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala
@@ -20,7 +20,7 @@ package org.apache.spark.sql.catalyst.expressions
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.analysis.TypeCheckResult
import org.apache.spark.sql.catalyst.expressions.codegen._
-import org.apache.spark.sql.catalyst.util.{GenericArrayData, TypeUtils}
+import org.apache.spark.sql.catalyst.util.{ArrayBasedMapData, GenericArrayData, TypeUtils}
import org.apache.spark.sql.types._
import org.apache.spark.unsafe.types.UTF8String
@@ -69,6 +69,87 @@ case class CreateArray(children: Seq[Expression]) extends Expression {
override def prettyName: String = "array"
}
+/**
+ * Returns a catalyst Map containing the evaluation of all children expressions as keys and values.
+ * The children are a flatted sequence of kv pairs, e.g. (key1, value1, key2, value2, ...)
+ */
+case class CreateMap(children: Seq[Expression]) extends Expression {
+ private[sql] lazy val keys = children.indices.filter(_ % 2 == 0).map(children)
+ private[sql] lazy val values = children.indices.filter(_ % 2 != 0).map(children)
+
+ override def foldable: Boolean = children.forall(_.foldable)
+
+ override def checkInputDataTypes(): TypeCheckResult = {
+ if (children.size % 2 != 0) {
+ TypeCheckResult.TypeCheckFailure(s"$prettyName expects an positive even number of arguments.")
+ } else if (keys.map(_.dataType).distinct.length > 1) {
+ TypeCheckResult.TypeCheckFailure("The given keys of function map should all be the same " +
+ "type, but they are " + keys.map(_.dataType.simpleString).mkString("[", ", ", "]"))
+ } else if (values.map(_.dataType).distinct.length > 1) {
+ TypeCheckResult.TypeCheckFailure("The given values of function map should all be the same " +
+ "type, but they are " + values.map(_.dataType.simpleString).mkString("[", ", ", "]"))
+ } else {
+ TypeCheckResult.TypeCheckSuccess
+ }
+ }
+
+ override def dataType: DataType = {
+ MapType(
+ keyType = keys.headOption.map(_.dataType).getOrElse(NullType),
+ valueType = values.headOption.map(_.dataType).getOrElse(NullType),
+ valueContainsNull = values.exists(_.nullable))
+ }
+
+ override def nullable: Boolean = false
+
+ override def eval(input: InternalRow): Any = {
+ val keyArray = keys.map(_.eval(input)).toArray
+ if (keyArray.contains(null)) {
+ throw new RuntimeException("Cannot use null as map key!")
+ }
+ val valueArray = values.map(_.eval(input)).toArray
+ new ArrayBasedMapData(new GenericArrayData(keyArray), new GenericArrayData(valueArray))
+ }
+
+ override def genCode(ctx: CodegenContext, ev: ExprCode): String = {
+ val arrayClass = classOf[GenericArrayData].getName
+ val mapClass = classOf[ArrayBasedMapData].getName
+ val keyArray = ctx.freshName("keyArray")
+ val valueArray = ctx.freshName("valueArray")
+ val keyData = s"new $arrayClass($keyArray)"
+ val valueData = s"new $arrayClass($valueArray)"
+ s"""
+ final boolean ${ev.isNull} = false;
+ final Object[] $keyArray = new Object[${keys.size}];
+ final Object[] $valueArray = new Object[${values.size}];
+ """ + keys.zipWithIndex.map {
+ case (key, i) =>
+ val eval = key.gen(ctx)
+ s"""
+ ${eval.code}
+ if (${eval.isNull}) {
+ throw new RuntimeException("Cannot use null as map key!");
+ } else {
+ $keyArray[$i] = ${eval.value};
+ }
+ """
+ }.mkString("\n") + values.zipWithIndex.map {
+ case (value, i) =>
+ val eval = value.gen(ctx)
+ s"""
+ ${eval.code}
+ if (${eval.isNull}) {
+ $valueArray[$i] = null;
+ } else {
+ $valueArray[$i] = ${eval.value};
+ }
+ """
+ }.mkString("\n") + s"final MapData ${ev.value} = new $mapClass($keyData, $valueData);"
+ }
+
+ override def prettyName: String = "map"
+}
+
/**
* Returns a Row containing the evaluation of all children expressions.
*/
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ArrayBasedMapData.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ArrayBasedMapData.scala
index d85b72ed83..d46f03ad8f 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ArrayBasedMapData.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ArrayBasedMapData.scala
@@ -24,7 +24,6 @@ class ArrayBasedMapData(val keyArray: ArrayData, val valueArray: ArrayData) exte
override def copy(): MapData = new ArrayBasedMapData(keyArray.copy(), valueArray.copy())
- // We need to check equality of map type in tests.
override def equals(o: Any): Boolean = {
if (!o.isInstanceOf[ArrayBasedMapData]) {
return false
@@ -35,11 +34,11 @@ class ArrayBasedMapData(val keyArray: ArrayData, val valueArray: ArrayData) exte
return false
}
- ArrayBasedMapData.toScalaMap(this) == ArrayBasedMapData.toScalaMap(other)
+ this.keyArray == other.keyArray && this.valueArray == other.valueArray
}
override def hashCode: Int = {
- ArrayBasedMapData.toScalaMap(this).hashCode()
+ keyArray.hashCode() * 37 + valueArray.hashCode()
}
override def toString: String = {
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/ExpressionTypeCheckingSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/ExpressionTypeCheckingSuite.scala
index 92c8496fde..ace6e10c6e 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/ExpressionTypeCheckingSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/ExpressionTypeCheckingSuite.scala
@@ -173,13 +173,23 @@ class ExpressionTypeCheckingSuite extends SparkFunSuite {
CreateNamedStruct(Seq("a", "b", 2.0)), "even number of arguments")
assertError(
CreateNamedStruct(Seq(1, "a", "b", 2.0)),
- "Only foldable StringType expressions are allowed to appear at odd position")
+ "Only foldable StringType expressions are allowed to appear at odd position")
assertError(
CreateNamedStruct(Seq('a.string.at(0), "a", "b", 2.0)),
- "Only foldable StringType expressions are allowed to appear at odd position")
+ "Only foldable StringType expressions are allowed to appear at odd position")
assertError(
CreateNamedStruct(Seq(Literal.create(null, StringType), "a")),
- "Field name should not be null")
+ "Field name should not be null")
+ }
+
+ test("check types for CreateMap") {
+ assertError(CreateMap(Seq("a", "b", 2.0)), "even number of arguments")
+ assertError(
+ CreateMap(Seq('intField, 'stringField, 'booleanField, 'stringField)),
+ "keys of function map should all be the same type")
+ assertError(
+ CreateMap(Seq('stringField, 'intField, 'stringField, 'booleanField)),
+ "values of function map should all be the same type")
}
test("check types for ROUND") {
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala
index 6f289dcc47..883ef48984 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala
@@ -250,6 +250,67 @@ class HiveTypeCoercionSuite extends PlanTest {
:: Nil))
}
+ test("CreateArray casts") {
+ ruleTest(HiveTypeCoercion.FunctionArgumentConversion,
+ CreateArray(Literal(1.0)
+ :: Literal(1)
+ :: Literal.create(1.0, FloatType)
+ :: Nil),
+ CreateArray(Cast(Literal(1.0), DoubleType)
+ :: Cast(Literal(1), DoubleType)
+ :: Cast(Literal.create(1.0, FloatType), DoubleType)
+ :: Nil))
+
+ ruleTest(HiveTypeCoercion.FunctionArgumentConversion,
+ CreateArray(Literal(1.0)
+ :: Literal(1)
+ :: Literal("a")
+ :: Nil),
+ CreateArray(Cast(Literal(1.0), StringType)
+ :: Cast(Literal(1), StringType)
+ :: Cast(Literal("a"), StringType)
+ :: Nil))
+ }
+
+ test("CreateMap casts") {
+ // type coercion for map keys
+ ruleTest(HiveTypeCoercion.FunctionArgumentConversion,
+ CreateMap(Literal(1)
+ :: Literal("a")
+ :: Literal.create(2.0, FloatType)
+ :: Literal("b")
+ :: Nil),
+ CreateMap(Cast(Literal(1), FloatType)
+ :: Literal("a")
+ :: Cast(Literal.create(2.0, FloatType), FloatType)
+ :: Literal("b")
+ :: Nil))
+ // type coercion for map values
+ ruleTest(HiveTypeCoercion.FunctionArgumentConversion,
+ CreateMap(Literal(1)
+ :: Literal("a")
+ :: Literal(2)
+ :: Literal(3.0)
+ :: Nil),
+ CreateMap(Literal(1)
+ :: Cast(Literal("a"), StringType)
+ :: Literal(2)
+ :: Cast(Literal(3.0), StringType)
+ :: Nil))
+ // type coercion for both map keys and values
+ ruleTest(HiveTypeCoercion.FunctionArgumentConversion,
+ CreateMap(Literal(1)
+ :: Literal("a")
+ :: Literal(2.0)
+ :: Literal(3.0)
+ :: Nil),
+ CreateMap(Cast(Literal(1), DoubleType)
+ :: Cast(Literal("a"), StringType)
+ :: Cast(Literal(2.0), DoubleType)
+ :: Cast(Literal(3.0), StringType)
+ :: Nil))
+ }
+
test("greatest/least cast") {
for (operator <- Seq[(Seq[Expression] => Expression)](Greatest, Least)) {
ruleTest(HiveTypeCoercion.FunctionArgumentConversion,
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 9c1688b261..7c009a7360 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
@@ -134,6 +134,46 @@ class ComplexTypeSuite extends SparkFunSuite with ExpressionEvalHelper {
checkEvaluation(CreateArray(Literal.create(null, IntegerType) :: Nil), null :: Nil)
}
+ test("CreateMap") {
+ def interlace(keys: Seq[Literal], values: Seq[Literal]): Seq[Literal] = {
+ keys.zip(values).flatMap { case (k, v) => Seq(k, v) }
+ }
+
+ def createMap(keys: Seq[Any], values: Seq[Any]): Map[Any, Any] = {
+ // catalyst map is order-sensitive, so we create ListMap here to preserve the elements order.
+ scala.collection.immutable.ListMap(keys.zip(values): _*)
+ }
+
+ val intSeq = Seq(5, 10, 15, 20, 25)
+ val longSeq = intSeq.map(_.toLong)
+ val strSeq = intSeq.map(_.toString)
+ checkEvaluation(CreateMap(Nil), Map.empty)
+ checkEvaluation(
+ CreateMap(interlace(intSeq.map(Literal(_)), longSeq.map(Literal(_)))),
+ createMap(intSeq, longSeq))
+ checkEvaluation(
+ CreateMap(interlace(strSeq.map(Literal(_)), longSeq.map(Literal(_)))),
+ createMap(strSeq, longSeq))
+ checkEvaluation(
+ CreateMap(interlace(longSeq.map(Literal(_)), strSeq.map(Literal(_)))),
+ createMap(longSeq, strSeq))
+
+ val strWithNull = strSeq.drop(1).map(Literal(_)) :+ Literal.create(null, StringType)
+ checkEvaluation(
+ CreateMap(interlace(intSeq.map(Literal(_)), strWithNull)),
+ createMap(intSeq, strWithNull.map(_.value)))
+ intercept[RuntimeException] {
+ checkEvaluationWithoutCodegen(
+ CreateMap(interlace(strWithNull, intSeq.map(Literal(_)))),
+ null, null)
+ }
+ intercept[RuntimeException] {
+ checkEvalutionWithUnsafeProjection(
+ CreateMap(interlace(strWithNull, intSeq.map(Literal(_)))),
+ null, null)
+ }
+ }
+
test("CreateStruct") {
val row = create_row(1, 2, 3)
val c1 = 'a.int.at(0)
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
index 304d747d4f..8abb9d7e4a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
@@ -904,6 +904,17 @@ object functions {
array((colName +: colNames).map(col) : _*)
}
+ /**
+ * Creates a new map column. The input columns must be grouped as key-value pairs, e.g.
+ * (key1, value1, key2, value2, ...). The key columns must all have the same data type, and can't
+ * be null. The value columns must all have the same data type.
+ *
+ * @group normal_funcs
+ * @since 2.0
+ */
+ @scala.annotation.varargs
+ def map(cols: Column*): Column = withExpr { CreateMap(cols.map(_.expr)) }
+
/**
* Marks a DataFrame as small enough for use in broadcast joins.
*
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameComplexTypeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameComplexTypeSuite.scala
index b76fc73b7f..72f676e622 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameComplexTypeSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameComplexTypeSuite.scala
@@ -41,7 +41,13 @@ class DataFrameComplexTypeSuite extends QueryTest with SharedSQLContext {
test("UDF on array") {
val f = udf((a: String) => a)
val df = sparkContext.parallelize(Seq((1, 1))).toDF("a", "b")
- df.select(array($"a").as("s")).select(f(expr("s[0]"))).collect()
+ df.select(array($"a").as("s")).select(f($"s".getItem(0))).collect()
+ }
+
+ test("UDF on map") {
+ val f = udf((a: String) => a)
+ val df = Seq("a" -> 1).toDF("a", "b")
+ df.select(map($"a", $"b").as("s")).select(f($"s".getItem("a"))).collect()
}
test("SPARK-12477 accessing null element in array field") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
index 2aa6f8d4ac..746e25a0c3 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
@@ -44,15 +44,16 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {
val expectedType = ArrayType(IntegerType, containsNull = false)
assert(row.schema(0).dataType === expectedType)
- assert(row.getAs[Seq[Int]](0) === Seq(0, 2))
+ assert(row.getSeq[Int](0) === Seq(0, 2))
}
- // Turn this on once we add a rule to the analyzer to throw a friendly exception
- ignore("array: throw exception if putting columns of different types into an array") {
- val df = Seq((0, "str")).toDF("a", "b")
- intercept[AnalysisException] {
- df.select(array("a", "b"))
- }
+ test("map with column expressions") {
+ val df = Seq(1 -> "a").toDF("a", "b")
+ val row = df.select(map($"a" + 1, $"b")).first()
+
+ val expectedType = MapType(IntegerType, StringType, valueContainsNull = true)
+ assert(row.schema(0).dataType === expectedType)
+ assert(row.getMap[Int, String](0) === Map(2 -> "a"))
}
test("struct with column name") {
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/ExpressionToSQLSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/ExpressionToSQLSuite.scala
index 4c9c48a25c..75930086ff 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/ExpressionToSQLSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/ExpressionToSQLSuite.scala
@@ -100,6 +100,7 @@ class ExpressionToSQLSuite extends SQLBuilderTest with SQLTestUtils {
checkSqlGeneration("SELECT isnull(null), isnull('a')")
checkSqlGeneration("SELECT isnotnull(null), isnotnull('a')")
checkSqlGeneration("SELECT least(1,null,3)")
+ checkSqlGeneration("SELECT map(1, 'a', 2, 'b')")
checkSqlGeneration("SELECT named_struct('c1',1,'c2',2,'c3',3)")
checkSqlGeneration("SELECT nanvl(a, 5), nanvl(b, 10), nanvl(d, c) from t2")
checkSqlGeneration("SELECT nvl(null, 1, 2)")
--
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