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cc @dongjoon-hyun @gatorsmile @viirya
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Github user squito commented on the issue:
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btw I may have made the pull-based approach sound more complex than I meant
to, I'm happy to take that approach if you think its better. The fact the
replication is synchronous doesn't really
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Can one of the admins verify this patch?
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[Web UI] Do not skip cells in Tasks table on Stage page when accumulators
are not available
[Web UI] Do not skip cells in Tasks table on Stage page when accumulators
are not available.
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retest this please.
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As I've mentioned elsewhere, stages are currently submitted sequentially.
That is, for a stage X, all the stage dependencies of X are completed before
the tasks within X start. This change
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thanks, merging to master!
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@@ -0,0 +1,139 @@
+/*
+ * Licensed to the Apache
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thanks, merging to 2.3!
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--- Diff: core/src/main/scala/org/apache/spark/SparkEnv.scala ---
@@ -140,6 +140,7 @@ object SparkEnv extends Logging {
private[spark] val
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--- Diff: core/src/main/scala/org/apache/spark/MapOutputTracker.scala ---
@@ -213,6 +213,12 @@ private[spark] sealed trait MapOutputTrackerMessage
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--- Diff: core/src/main/scala/org/apache/spark/Dependency.scala ---
@@ -88,14 +96,53 @@ class ShuffleDependency[K: ClassTag, V: ClassTag, C:
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[SPARK-24036][SS] Scheduler changes for continuous processing shuffle
support
## What changes were proposed in this pull request?
This is the last part of the preview PRs, the mainly
Github user cloud-fan commented on the issue:
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I understand the default value of `enforceSchema` must be true to keep
backward compatibility, but shall we suggest users to set it to false to avoid
incorrect result in the document?
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--- Diff: python/pyspark/sql/tests.py ---
@@ -3040,6 +3040,24 @@ def test_csv_sampling_ratio(self):
.csv(rdd, samplingRatio=0.5).schema
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It seems good to use the array option for the hexadecimal sequence, if we
have the array option feature. But I don't think we should block this PR just
because the array option is not ready.
Github user xuanyuanking commented on the issue:
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> As discussed in the other PR, I'm not sure about how we're integrating
with the scheduler here, so I can't really give a more detailed review at this
point.
My bad, I'm preparing
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--- Diff: python/pyspark/sql/tests.py ---
@@ -3040,6 +3040,24 @@ def test_csv_sampling_ratio(self):
.csv(rdd, samplingRatio=0.5).schema
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LGTM apart from a nit
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Github user DylanGuedes commented on a diff in the pull request:
https://github.com/apache/spark/pull/21045#discussion_r188947896
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
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@@ -90,6 +90,132 @@ case class
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/21193#discussion_r18894
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/javaCode.scala
---
@@ -114,6 +114,113 @@ object JavaCode {
}
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/21193
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Github user skonto commented on the issue:
https://github.com/apache/spark/pull/21317
Jenkins, retest this please
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/21342
How about we create a special Exception class to wrap OOM and
InterupttedException, and say it's only used to work around the scala bug?
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Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/21028
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/21329
Merged build finished. Test FAILed.
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