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LGTM, once #20983 is committed and we can pull in the tests from that PR.
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retest this please
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Discussed with @cloud-fan offline. The conclusion is that we can use simple
factory pattern for data factory, so that we can avoid redundant code easily
and stop using `PartitionedFile =>
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Sounds like this approach is just racy by nature. There's a similar test in
SparkContextSuite ("Cancelling stages/jobs with custom reasons") where I fixed
a similar issue using a semaphore. Sounds
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The latest commit is just to add new comments in the code. The previous
test already passed.
Merged to master/2.3
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retest this please
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Can we add them to the file based test suites instead?
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@WeichenXu123 thanks for checking it out. I've resolved the conflicts,
build is green.
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@HyukjinKwon Thank you for the review. I really appreciate that.
> Trust me, I don't usually try to get in the way hard like this.
No doubt.
> If you really don't know, I
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[SPARK-23916][SQL] Add array_join function
## What changes were proposed in this pull request?
The PR adds the SQL function `array_join`. The behavior of the function is
based on
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retest this please
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--- Diff: python/pyspark/sql/udf.py ---
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typo in summary: "On top of data" --> "On top of that" (I think)
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@WeichenXu123 Executing `test("FPGrowth fit and transform with different
data types")` with Byte data type produces an
`org.apache.spark.sql.AnalysisException: cannot resolve 'CAST(`items`
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retest this please.
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retest this please
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Can't reproduce it locally and seems to unrelated...
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GitHub user wangyum opened a pull request:
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[SPARK-23900][SQL] format_number support user specifed format as argument
## What changes were proposed in this pull request?
`format_number` support user specifed format as argument. For
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--- Diff:
core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala ---
@@ -234,8 +244,22 @@ private[spark] class EventLoggingListener(
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Github user squito commented on a diff in the pull request:
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--- Diff:
core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala ---
@@ -234,8 +244,22 @@ private[spark] class EventLoggingListener(
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