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This pr is a follow-up of
https://github.com/apache/spark/pull/21288#event-1697426905
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[SPARK-24206][SQL][FOLLOW-UP] Update DataSourceReadBenchmark benchmark
results
## What changes were proposed in this pull request?
This pr corrected the default configuration
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Sure
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--- Diff:
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@@ -0,0 +1,88 @@
+/*
+ * Licensed to the
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cc @maryannxue Please take a look at this?
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+/*
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Github user maropu commented on the issue:
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IMHO we need to have clear decision rules for these kinds of behaviour
changes in the contribution guide. In the past migration guide descriptions, it
seems we've already accept some behaviour
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+/*
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--- Diff: python/pyspark/sql/column.py ---
@@ -514,6 +514,16 @@ def isin(self, *cols):
desc_nulls_first =
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@markhamstra, Spark sometimes has some behaviour changes for some bug fixes
or in few other cases so far. At least, see the similar configurations added in
the migration guide. It sounded we
Github user maropu commented on the issue:
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Thanks for the check! btw, `DataSourceReadBenchmark` has the same issue
(`spark.master` setup), so is it ok to fix this as follow-up?
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LGTM
Thanks! Merged to master.
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LGTM
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@gatorsmile Thanks a lot. I will process your comments and get back.
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@HyukjinKwon this is not new policy. It is what Apache Spark has guaranteed
in its version numbering and public API since 1.0.0. It is not a matter of
"from now on", but rather of whether
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Whether Memory Structured streaming sink is idempotent and provides
end-to-end exactly-once semantics?
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--- Diff: docs/sql-programming-guide.md ---
@@ -1302,9 +1302,20 @@ the following case-insensitive options:
dbtable
-
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dbtable
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dbtable
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dbtable
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Github user HyukjinKwon commented on the issue:
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> is it basically true that Hadoop 3 will work with only minor patches to
the Hive fork in Spark?
Up to my knowledge so far, yes, it basically works. At least, the
regression tests we
Github user HyukjinKwon commented on the issue:
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I am good to have the configuration as that's basically what I suggested
too. Removing the behaviour in 3.0.0 is fine. My only question left is the
default value.
> We should change
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@@ -75,28 +75,47 @@ trait
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I created a JIRA https://issues.apache.org/jira/browse/SPARK-24640. We
should change the behavior in 3.0. Before 3.0 release, we introduce a conf and
make it configurable. The default is to keep
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OK if you want to pare down the PR to fixes we had discussed here and on
the thread, I can get it in. I will need to just reevaluate the whole LICENSE
and NOTICE anyway as it's clear it's at least a
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If there is some codepath not updating shuffle write metrics (introduced
for sql), that would be a bug.
On Sat, Jun 23, 2018 at 7:27 AM Liang-Chi Hsieh
wrote:
> *@viirya*
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retest this, please
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Also weighing in here to ask: is it basically true that Hadoop 3 will work
with only minor patches to the Hive fork in Spark? then that seems worth the
hacking. Is the blocker that we can't get a
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@@ -145,10 +145,12 @@ public void write(Iterator> records)
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/16677#discussion_r197613004
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala ---
@@ -204,6 +204,13 @@ object SQLConf {
.intConf
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/21619
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/21619
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