[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[asfgit]

Github user asfgit closed the pull request at:

https://github.com/apache/spark/pull/21282


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[ueshin]

Github user ueshin commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r193958595
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -308,6 +309,234 @@ case class MapEntries(child: Expression) extends 
UnaryExpression with ExpectsInp
   override def prettyName: String = "map_entries"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression {
+
+  @transient
+  private lazy val dataTypeDetails: Option[(MapType, Boolean, Boolean)] = 
child.dataType match {
+case ArrayType(
+  StructType(Array(
+StructField(_, keyType, keyNullable, _),
+StructField(_, valueType, valueNullable, _))),
+  containsNull) => Some((MapType(keyType, valueType, valueNullable), 
keyNullable, containsNull))
+case _ => None
+  }
+
+  private def nullEntries: Boolean = dataTypeDetails.get._3
+
+  override def dataType: MapType = dataTypeDetails.get._1
+
+  override def checkInputDataTypes(): TypeCheckResult = dataTypeDetails 
match {
+case Some(_) => TypeCheckResult.TypeCheckSuccess
+case None => TypeCheckResult.TypeCheckFailure(s"'${child.sql}' is of " 
+
+  s"${child.dataType.simpleString} type. $prettyName accepts only 
arrays of pair structs.")
+  }
+
+  override protected def nullSafeEval(input: Any): Any = {
+val arrayData = input.asInstanceOf[ArrayData]
+val length = arrayData.numElements()
+val numEntries = if (nullEntries) (0 until 
length).count(!arrayData.isNullAt(_)) else length
+val keyArray = new Array[AnyRef](numEntries)
+val valueArray = new Array[AnyRef](numEntries)
+var i = 0
+var j = 0
+while (i < length) {
+  if (!arrayData.isNullAt(i)) {
--- End diff --

Yeah, that sounds reasonable. Thanks.


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[mn-mikke]

Github user mn-mikke commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r192875181
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -308,6 +309,234 @@ case class MapEntries(child: Expression) extends 
UnaryExpression with ExpectsInp
   override def prettyName: String = "map_entries"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression {
+
+  @transient
+  private lazy val dataTypeDetails: Option[(MapType, Boolean, Boolean)] = 
child.dataType match {
+case ArrayType(
+  StructType(Array(
+StructField(_, keyType, keyNullable, _),
+StructField(_, valueType, valueNullable, _))),
+  containsNull) => Some((MapType(keyType, valueType, valueNullable), 
keyNullable, containsNull))
+case _ => None
+  }
+
+  private def nullEntries: Boolean = dataTypeDetails.get._3
+
+  override def dataType: MapType = dataTypeDetails.get._1
+
+  override def checkInputDataTypes(): TypeCheckResult = dataTypeDetails 
match {
+case Some(_) => TypeCheckResult.TypeCheckSuccess
+case None => TypeCheckResult.TypeCheckFailure(s"'${child.sql}' is of " 
+
+  s"${child.dataType.simpleString} type. $prettyName accepts only 
arrays of pair structs.")
+  }
+
+  override protected def nullSafeEval(input: Any): Any = {
+val arrayData = input.asInstanceOf[ArrayData]
+val length = arrayData.numElements()
+val numEntries = if (nullEntries) (0 until 
length).count(!arrayData.isNullAt(_)) else length
+val keyArray = new Array[AnyRef](numEntries)
+val valueArray = new Array[AnyRef](numEntries)
+var i = 0
+var j = 0
+while (i < length) {
+  if (!arrayData.isNullAt(i)) {
--- End diff --

Hi @ueshin,
wouldn't it be better return `null` in this case? And follow null handling 
of other functions like `flatten`? 

```
flatten(array(array(1,2), null, array(3,4))) => null
```
WDYT?
   


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[ueshin]

Github user ueshin commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r192861844
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -308,6 +309,234 @@ case class MapEntries(child: Expression) extends 
UnaryExpression with ExpectsInp
   override def prettyName: String = "map_entries"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression {
+
+  @transient
+  private lazy val dataTypeDetails: Option[(MapType, Boolean, Boolean)] = 
child.dataType match {
+case ArrayType(
+  StructType(Array(
+StructField(_, keyType, keyNullable, _),
+StructField(_, valueType, valueNullable, _))),
+  containsNull) => Some((MapType(keyType, valueType, valueNullable), 
keyNullable, containsNull))
+case _ => None
+  }
+
+  private def nullEntries: Boolean = dataTypeDetails.get._3
+
+  override def dataType: MapType = dataTypeDetails.get._1
+
+  override def checkInputDataTypes(): TypeCheckResult = dataTypeDetails 
match {
+case Some(_) => TypeCheckResult.TypeCheckSuccess
+case None => TypeCheckResult.TypeCheckFailure(s"'${child.sql}' is of " 
+
+  s"${child.dataType.simpleString} type. $prettyName accepts only 
arrays of pair structs.")
+  }
+
+  override protected def nullSafeEval(input: Any): Any = {
+val arrayData = input.asInstanceOf[ArrayData]
+val length = arrayData.numElements()
+val numEntries = if (nullEntries) (0 until 
length).count(!arrayData.isNullAt(_)) else length
+val keyArray = new Array[AnyRef](numEntries)
+val valueArray = new Array[AnyRef](numEntries)
+var i = 0
+var j = 0
+while (i < length) {
+  if (!arrayData.isNullAt(i)) {
--- End diff --

We should throw an exception if `arrayData.isNullAt(i)`?


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[mn-mikke]

Github user mn-mikke commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r192573167
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -118,6 +120,229 @@ case class MapValues(child: Expression)
   override def prettyName: String = "map_values"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression
+{
+  private lazy val resolvedDataType: Option[MapType] = child.dataType 
match {
+case ArrayType(
+  StructType(Array(
+StructField(_, keyType, false, _),
+StructField(_, valueType, valueNullable, _))),
+  false) => Some(MapType(keyType, valueType, valueNullable))
+case _ => None
+  }
+
+  override def dataType: MapType = resolvedDataType.get
+
+  override def checkInputDataTypes(): TypeCheckResult = resolvedDataType 
match {
+case Some(_) => TypeCheckResult.TypeCheckSuccess
+case None => TypeCheckResult.TypeCheckFailure(s"'${child.sql}' is of " 
+
+  s"${child.dataType.simpleString} type. $prettyName accepts only 
null-free arrays " +
+  "of pair structs. Values of the first struct field can't contain 
nulls and produce " +
+  "duplicates.")
+  }
+
+  override protected def nullSafeEval(input: Any): Any = {
+val arrayData = input.asInstanceOf[ArrayData]
+val length = arrayData.numElements()
+val keyArray = new Array[AnyRef](length)
+val keySet = new OpenHashSet[AnyRef]()
+val valueArray = new Array[AnyRef](length)
+var i = 0;
+while (i < length) {
+  val entry = arrayData.getStruct(i, 2)
+  val key = entry.get(0, dataType.keyType)
+  if (key == null) {
+throw new RuntimeException("The first field from a struct (key) 
can't be null.")
+  }
+  if (keySet.contains(key)) {
--- End diff --

Ok, no problem. I've removed duplicity checks.


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[ueshin]

Github user ueshin commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r192531374
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -118,6 +120,229 @@ case class MapValues(child: Expression)
   override def prettyName: String = "map_values"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression
+{
+  private lazy val resolvedDataType: Option[MapType] = child.dataType 
match {
+case ArrayType(
+  StructType(Array(
+StructField(_, keyType, false, _),
+StructField(_, valueType, valueNullable, _))),
+  false) => Some(MapType(keyType, valueType, valueNullable))
+case _ => None
+  }
+
+  override def dataType: MapType = resolvedDataType.get
+
+  override def checkInputDataTypes(): TypeCheckResult = resolvedDataType 
match {
+case Some(_) => TypeCheckResult.TypeCheckSuccess
+case None => TypeCheckResult.TypeCheckFailure(s"'${child.sql}' is of " 
+
+  s"${child.dataType.simpleString} type. $prettyName accepts only 
null-free arrays " +
+  "of pair structs. Values of the first struct field can't contain 
nulls and produce " +
+  "duplicates.")
+  }
+
+  override protected def nullSafeEval(input: Any): Any = {
+val arrayData = input.asInstanceOf[ArrayData]
+val length = arrayData.numElements()
+val keyArray = new Array[AnyRef](length)
+val keySet = new OpenHashSet[AnyRef]()
+val valueArray = new Array[AnyRef](length)
+var i = 0;
+while (i < length) {
+  val entry = arrayData.getStruct(i, 2)
+  val key = entry.get(0, dataType.keyType)
+  if (key == null) {
+throw new RuntimeException("The first field from a struct (key) 
can't be null.")
+  }
+  if (keySet.contains(key)) {
--- End diff --

I'm sorry for the super delay.
Let's just ignore the duplicated key like `CreateMap` for now. We will need 
to discuss map-related topics, such as duplicate keys, equality or ordering, 
etc.


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[adrian-wang]

Github user adrian-wang commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r187291692
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -118,6 +120,229 @@ case class MapValues(child: Expression)
   override def prettyName: String = "map_values"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression
+{
--- End diff --

Nit: style


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[mn-mikke]

Github user mn-mikke commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r187282249
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -118,6 +120,229 @@ case class MapValues(child: Expression)
   override def prettyName: String = "map_values"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression
+{
+  private lazy val resolvedDataType: Option[MapType] = child.dataType 
match {
+case ArrayType(
+  StructType(Array(
+StructField(_, keyType, false, _),
+StructField(_, valueType, valueNullable, _))),
+  false) => Some(MapType(keyType, valueType, valueNullable))
+case _ => None
+  }
+
+  override def dataType: MapType = resolvedDataType.get
+
+  override def checkInputDataTypes(): TypeCheckResult = resolvedDataType 
match {
+case Some(_) => TypeCheckResult.TypeCheckSuccess
+case None => TypeCheckResult.TypeCheckFailure(s"'${child.sql}' is of " 
+
+  s"${child.dataType.simpleString} type. $prettyName accepts only 
null-free arrays " +
+  "of pair structs. Values of the first struct field can't contain 
nulls and produce " +
+  "duplicates.")
+  }
+
+  override protected def nullSafeEval(input: Any): Any = {
+val arrayData = input.asInstanceOf[ArrayData]
+val length = arrayData.numElements()
+val keyArray = new Array[AnyRef](length)
+val keySet = new OpenHashSet[AnyRef]()
+val valueArray = new Array[AnyRef](length)
+var i = 0;
+while (i < length) {
+  val entry = arrayData.getStruct(i, 2)
+  val key = entry.get(0, dataType.keyType)
+  if (key == null) {
+throw new RuntimeException("The first field from a struct (key) 
can't be null.")
+  }
+  if (keySet.contains(key)) {
--- End diff --

Yeah, we've already touched this topic in [your PR for SPARK-23933](
https://github.com/apache/spark/pull/21258). I think if some hashing is 
added into maps in future, these duplicity checks will have to be introduced 
anyway. So if we add it now, we can avoid breaking changes in future. But I 
understand your point of view.

Presto also doesn't support duplicates:
```
presto:default> SELECT map_from_entries(ARRAY[(1, 'x'), (1, 'y')]);
Query 20180510_090536_5_468a9 failed: Duplicate keys (1) are not allowed
```

WDYT @ueshin @gatorsmile


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[ueshin]

Github user ueshin commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r187258000
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -118,6 +120,229 @@ case class MapValues(child: Expression)
   override def prettyName: String = "map_values"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression
+{
+  private lazy val resolvedDataType: Option[MapType] = child.dataType 
match {
--- End diff --

`@transient`?


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[ueshin]

Github user ueshin commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r187263146
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -118,6 +120,229 @@ case class MapValues(child: Expression)
   override def prettyName: String = "map_values"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression
+{
+  private lazy val resolvedDataType: Option[MapType] = child.dataType 
match {
+case ArrayType(
+  StructType(Array(
+StructField(_, keyType, false, _),
--- End diff --

We don't need key field to be `nullable = false` because we check the 
nullability when creating an array?


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[ueshin]

Github user ueshin commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r187264919
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -118,6 +120,229 @@ case class MapValues(child: Expression)
   override def prettyName: String = "map_values"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression
+{
+  private lazy val resolvedDataType: Option[MapType] = child.dataType 
match {
+case ArrayType(
+  StructType(Array(
+StructField(_, keyType, false, _),
+StructField(_, valueType, valueNullable, _))),
+  false) => Some(MapType(keyType, valueType, valueNullable))
--- End diff --

Can we reject an array with `containsNull = true` here? The array might not 
contain `null`s.


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[kiszk]

Github user kiszk commented on a diff in the pull request:

https://github.com/apache/spark/pull/21282#discussion_r187234431
  
--- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
 ---
@@ -118,6 +120,229 @@ case class MapValues(child: Expression)
   override def prettyName: String = "map_values"
 }
 
+/**
+ * Returns a map created from the given array of entries.
+ */
+@ExpressionDescription(
+  usage = "_FUNC_(arrayOfEntries) - Returns a map created from the given 
array of entries.",
+  examples = """
+Examples:
+  > SELECT _FUNC_(array(struct(1, 'a'), struct(2, 'b')));
+   {1:"a",2:"b"}
+  """,
+  since = "2.4.0")
+case class MapFromEntries(child: Expression) extends UnaryExpression
+{
+  private lazy val resolvedDataType: Option[MapType] = child.dataType 
match {
+case ArrayType(
+  StructType(Array(
+StructField(_, keyType, false, _),
+StructField(_, valueType, valueNullable, _))),
+  false) => Some(MapType(keyType, valueType, valueNullable))
+case _ => None
+  }
+
+  override def dataType: MapType = resolvedDataType.get
+
+  override def checkInputDataTypes(): TypeCheckResult = resolvedDataType 
match {
+case Some(_) => TypeCheckResult.TypeCheckSuccess
+case None => TypeCheckResult.TypeCheckFailure(s"'${child.sql}' is of " 
+
+  s"${child.dataType.simpleString} type. $prettyName accepts only 
null-free arrays " +
+  "of pair structs. Values of the first struct field can't contain 
nulls and produce " +
+  "duplicates.")
+  }
+
+  override protected def nullSafeEval(input: Any): Any = {
+val arrayData = input.asInstanceOf[ArrayData]
+val length = arrayData.numElements()
+val keyArray = new Array[AnyRef](length)
+val keySet = new OpenHashSet[AnyRef]()
+val valueArray = new Array[AnyRef](length)
+var i = 0;
+while (i < length) {
+  val entry = arrayData.getStruct(i, 2)
+  val key = entry.get(0, dataType.keyType)
+  if (key == null) {
+throw new RuntimeException("The first field from a struct (key) 
can't be null.")
+  }
+  if (keySet.contains(key)) {
--- End diff --

Is this check necessary for now? This is because other operations (e.g. 
`CreateMap`) allows us to create a map with duplicated key. Is it better to be 
consistent in Spark?


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[GitHub] spark pull request #21282: [SPARK-23934][SQL] Adding map_from_entries functi...

[mn-mikke]

GitHub user mn-mikke opened a pull request:

https://github.com/apache/spark/pull/21282

[SPARK-23934][SQL] Adding map_from_entries function

## What changes were proposed in this pull request?
The PR adds the `map_from_entries` function that returns a map created from 
the given array of entries.

## How was this patch tested?
New tests added into:
- `CollectionExpressionSuite`
- `DataFrameFunctionSuite`

## Note
The proposed behavior doesn't allow duplicated keys in contrast with `map` 
function.



You can merge this pull request into a Git repository by running:

$ git pull https://github.com/AbsaOSS/spark 
feature/array-api-map_from_entries-to-master

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/spark/pull/21282.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

This closes #21282


commit 8c6039c7b7f31f0343c4b0098a4e12dfff125128
Author: Marek Novotny 
Date:   2018-05-07T12:23:18Z

[SPARK-23934][SQL] Adding map_from_entries function




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