Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/15032#discussion_r78267647
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/AggregationIterator.scala
---
@@ -181,11 +182,7 @@ abstract class AggregationIterator(
// Process all expression-based aggregate functions.
updateProjection.target(currentBuffer)(joinedRow(currentBuffer,
row))
// Process all imperative aggregate functions.
- var i = 0
- while (i < updateFunctions.length) {
- updateFunctions(i)(currentBuffer, row)
- i += 1
- }
+ updateFunctions.foreach(updateFunction =>
updateFunction(currentBuffer, row))
--- End diff --
For [1], it's written as below and it seems including functional
transformations
> Use while loops instead of for loops or functional transformations (e.g.
`map`, `foreach`).
Then, could you then confirm the bytecode is virtually the same or more
efficient? My point was that I think we need a clear reason in this case.
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