Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/16541#discussion_r95922004
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/objects/objects.scala
---
@@ -589,6 +590,171 @@ case class MapObjects private(
}
}
+object CollectObjects {
+ private val curId = new java.util.concurrent.atomic.AtomicInteger()
+
+ /**
+ * Construct an instance of CollectObjects case class.
+ *
+ * @param function The function applied on the collection elements.
+ * @param inputData An expression that when evaluated returns a
collection object.
+ * @param elementType The data type of elements in the collection.
+ * @param collClass The type of the resulting collection.
+ */
+ def apply(
+ function: Expression => Expression,
+ inputData: Expression,
+ elementType: DataType,
+ collClass: Class[_]): CollectObjects = {
+ val loopValue = "CollectObjects_loopValue" + curId.getAndIncrement()
+ val loopIsNull = "CollectObjects_loopIsNull" + curId.getAndIncrement()
+ val loopVar = LambdaVariable(loopValue, loopIsNull, elementType)
+ val builderValue = "CollectObjects_builderValue" +
curId.getAndIncrement()
+ CollectObjects(loopValue, loopIsNull, elementType, function(loopVar),
inputData,
+ collClass, builderValue)
+ }
+}
+
+/**
+ * An equivalent to the [[MapObjects]] case class but returning an
ObjectType containing
+ * a Scala collection constructed using the associated builder, obtained
by calling `newBuilder`
+ * on the collection's companion object.
+ *
+ * @param loopValue the name of the loop variable that used when iterate
the collection, and used
+ * as input for the `lambdaFunction`
+ * @param loopIsNull the nullity of the loop variable that used when
iterate the collection, and
+ * used as input for the `lambdaFunction`
+ * @param loopVarDataType the data type of the loop variable that used
when iterate the collection,
+ * and used as input for the `lambdaFunction`
+ * @param lambdaFunction A function that take the `loopVar` as input, and
used as lambda function
+ * to handle collection elements.
+ * @param inputData An expression that when evaluated returns a collection
object.
+ * @param collClass The type of the resulting collection.
+ * @param builderValue The name of the builder variable used to construct
the resulting collection.
+ */
+case class CollectObjects private(
+ loopValue: String,
+ loopIsNull: String,
+ loopVarDataType: DataType,
+ lambdaFunction: Expression,
+ inputData: Expression,
+ collClass: Class[_],
+ builderValue: String) extends Expression with NonSQLExpression {
+
+ override def nullable: Boolean = inputData.nullable
+
+ override def children: Seq[Expression] = lambdaFunction :: inputData ::
Nil
+
+ override def eval(input: InternalRow): Any =
+ throw new UnsupportedOperationException("Only code-generated
evaluation is supported")
+
+ override def dataType: DataType = ObjectType(collClass)
+
+ override def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
+ val collObjectName = s"${collClass.getName}$$.MODULE$$"
+ val getBuilderVar = s"$collObjectName.newBuilder()"
--- End diff --
Yeah, I see. Although we can't deserialize back to `Range`, as there is no
problem to serialize it into internal format in SparkSQL, we still can convert
the dataset to a dataframe. With `RowEncoder`, we can deserialize back to
`Row`. That it what I do in #16546.
I will try if the `Seq` builder fallback work for that pr. Thanks.
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