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`UDFRegistration.registerFunction` needs a minor update for the log
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> it also means the chained evaluation of expressions needs to be run at
every occurrence.
We can introduce some mechanism to save statement to local variables if
it's going to be re-comp
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@HyukjinKwon @srowen Kindly review now, if looks good do merge. Thanks
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[SPARK-22878] [CORE] Count totalDroppedEvents for LiveListenerBus
## What changes were proposed in this pull request?
Count total dropped events from all queues' numDroppedEvents for
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@gatorsmile I added the test, but I didn't get what needs to be updated in
`registerPython`. May you explain me please? Thanks.
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@gatorsmile I answered to your comments about DB2 in the e-mail.
@cloud-fan that would help, but not solve the problem. It would just make
the problem being generated by bigger numbers.
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retest this please
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peopleDF.show()
++---+
| age| name|
++---+
|null|Michael|
| 30| Andy|
| 19| Justin|
++---+
peopleDF
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[SPARK-22875][BUILD] Assembly build fails for a high user id
## What changes were proposed in this pull request?
Add tarLongFileMode=posix configuration for the assembly plugin
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We need test cases. Manual tests are not enough.
I will try to review this tomorrow. Thanks!
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@@ -0,0 +1,432 @@
+/*
+ * Licen
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/19943#discussion_r158447746
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcColumnarBatchReader.scala
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@@ -0,0 +1,432 @@
+/*
+ * Licen
GitHub user ueshin opened a pull request:
https://github.com/apache/spark/pull/20054
[SPARK-22874][PYSPARK][SQL] Modify checking pandas version to use
LooseVersion.
## What changes were proposed in this pull request?
Currently we check pandas version by capturing if `Import
Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/20029
cc @liufengdb
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Github user viirya commented on the issue:
https://github.com/apache/spark/pull/19813
> What about future? Will we need to output statement for some reason? like
reducing the usage of local variables?
I think that we won't have strong motivation to use output statement. The
r
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/19977
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Github user maropu commented on the issue:
https://github.com/apache/spark/pull/19977
retest this please.
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Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/19218
Could you also add another test scenario? For the existing Hive tables
(created by Hive), does our Spark respect it? Do we use the existing
compression configuration?
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Github user maropu commented on the issue:
https://github.com/apache/spark/pull/20024
ok, I'll brush up based on your suggestion.
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/20036
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Github user kiszk commented on the issue:
https://github.com/apache/spark/pull/20036
retest this please
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Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/19218#discussion_r158445027
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/SaveAsHiveFile.scala
---
@@ -68,6 +68,12 @@ private[hive] trait SaveAsHiveFile ext
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/19218#discussion_r158444388
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveOptions.scala
---
@@ -19,7 +19,16 @@ package org.apache.spark.sql.hive.executi
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