Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/9038#discussion_r41647560
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TungstenAggregationIterator.scala
---
@@ -170,10 +232,27 @@ class TungstenAggregationIterator(
val bufferRowSize: Int = bufferSchema.length
val genericMutableBuffer = new GenericMutableRow(bufferRowSize)
- val unsafeProjection =
- UnsafeProjection.create(bufferSchema.map(_.dataType))
- val buffer = unsafeProjection.apply(genericMutableBuffer)
- initialProjection.target(buffer)(EmptyRow)
+ // TODO(josh): figure out whether we have to use
+ val useUnsafeBuffer =
bufferSchema.map(_.dataType).forall(UnsafeRow.isMutable)
+
+ val buffer = /* if (useUnsafeBuffer) */ {
--- End diff --
When we do hash-based aggregation, the buffer is an UnsafeRow anyway. So, I
guess it is fine to let InterpretedAggregate functions to work with UnsafeRows
directly. When a developer adds an new InterpretedAggregate function whose
aggregate buffer data types are compatible with TungstenAggregate, if he/she
uses `update`, he/she will get the exception while testing the function, right?
If so, it is safe to say that the code committed in master will not use
`update`.
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