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[SPARK-22681]Accumulator should only updated once for each task in result
stage
## What changes were proposed in this pull request?
As the doc says "For accumulator updates performed inside
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[WIP][ML][SPARK-11171] spark 11237 Add PMML export to Spark ML pipelines
## What changes were proposed in this pull request?
Adds PMML export support to Spark ML pipelines in the style of
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[SPARK-22473][FOLLOWUP][TEST] Remove deprecated Date functions
## What changes were proposed in this pull request?
#19696 replaced the deprecated usages for `Date` and `Waiter`, but a few
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Oh, will double check too for sure shortly.
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--- Diff: python/pyspark/sql/functions.py ---
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+clas
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Friendly ping -- I've fixed that @ueshin.
Is there anything else I should look at to get this to be merged?
/cc @HyukjinKwon
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@yaooqinn It is used for executors.
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Retest this please.
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@ueshin
[context.py#L191](https://github.com/yaooqinn/spark/blob/8ff5663fe9a32eae79c8ee6bc310409170a8da64/python/pyspark/context.py#L191)
set for both driver and executor?
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ok to test
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Thanks for your work! A late LGTM
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please review it again, thanks all.
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@ueshin i see.
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+/*
+ * Licens
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@yaooqinn I meant it is not used for `pythonExec`.
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I can `spark.executorEnv.PYSPARK_PYTHON` in `sparkConf` at executor side ,
because it is set at
[context.py#L156](https://github.com/yaooqinn/spark/blob/8ff5663fe9a32eae79c8ee6bc310409170a8da64/py
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.c
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LGTM
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Github user ueshin commented on the issue:
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@yaooqinn OK, I see the situation.
In client mode, I think we can't use `spark.yarn.appMasterEnv.XXX` which is
for cluster mode. So we should use environment variable `PYSPARK_PYTHON` or
`PY
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retest this please.
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/19869
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Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/19871#discussion_r154577760
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
---
@@ -568,8 +571,11 @@ object DataSource extends Logging
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