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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