Github user viirya commented on the issue:
https://github.com/apache/spark/pull/15596
@JoshRosen After few tries, I think to replace `CollectLimitExec` with
`GlobalLimitExec` is not a good idea.
The main reason is whole stage codegen. Since `GlobalLimitExec` supports
whole stage codegen, it will be wrapped in a `WholeStageCodegenExec`. So we
will call `executeCollect()` on `WholeStageCodegenExec` wrapping
`GlobalLimitExec` when we do `collect()` on `df.limit(1).collect()`, for
example.
`WholeStageCodegenExec.executeCollect()` is `SparkPlan.executeCollect()`
actually. So we will do shuffling and retrieve the results. It doesn't harm to
anything, but fails few tests, as the Jenkins test results showed.
Of course we can change the tests to fit it. But I don't think it is
necessary and good way to do.
Another workaround is to override `WholeStageCodegenExec.executeCollect()`.
But as @rxin pointed out in previous comment, it is confusing.
So based on such facts, I think we better keep `CollectLimitExec` but just
remove its shuffling code as I did in initial commit.
What do you think?
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