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retest this please
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GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/8820
[SPARK-10699] [ML] Support checkpointInterval can be disabled
Currently use can set ```checkpointInterval``` to specify how often should
the cache be checkpointed. But we also need the function
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Github user srowen commented on the pull request:
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LGTM
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Github user srowen commented on the pull request:
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I think this and SPARK-10571 are duplicates of SPARK-10531; let's at least
retag this, or close the PR, as that's already resolved.
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Github user viirya commented on the pull request:
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@yhuai Thanks for commenting this.
You are correct that there will be high storing cost if we store all null
values. But I am not sure how to just write null
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https://github.com/apache/spark/pull/8818
[SPARK-10692][Streaming]Report the batch error to
StreamingListener.onBatchCompleted
Added an `errorMessage` field and set it when a Streaming job is failed.
I have not yet updated the
Github user zsxwing commented on the pull request:
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@tdas, what do you think?
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GitHub user zsxwing reopened a pull request:
https://github.com/apache/spark/pull/8357
[SPARK-10155][SQL]Change SqlParser to object to avoid memory leak
Since `scala.util.parsing.combinator.Parsers` is thread-safe since Scala
2.10 (See
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Github user KaiXinXiaoLei closed the pull request at:
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Github user zsxwing commented on the pull request:
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@marmbrus since SQLContext is thread-safe, I suppose SQLParser is
thread-safe too. So I reopened it. Could you take a look at this one?
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https://github.com/apache/spark/pull/8819
Fixed links to the API
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Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-141462484
That is exactly what I was afraid of. Would the patch make more sense to
*only* check precision for a zero value? Does it ever make sense to have a
precision of
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Github user yhuai commented on the pull request:
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@viirya We may try to store the schema to a metadata file for the table.
With this way, we can avoid of introducing hacks for writing out null values.
But, we need to
Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/8819#issuecomment-141505941
@aseigneurin Please send the patch to master branch instead of a release
branch unless it is a bug fix in particular to that branch. You can close this
PR and open
Github user yhuai commented on the pull request:
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@zsxwing How serious is the leak? Under what condition(s) will we see a
significant amount of memory occupied by leaked stuff?
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Github user tedyu commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
@@ -96,7 +96,7 @@ class SparkContext(config: SparkConf) extends Logging
with
Github user mengxr commented on the pull request:
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LGTM. Merged into master. Thanks!
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LGTM. Merged into master. Thanks!
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LGTM. Once jenkins is good, I will merge it to master and branch 1.5.
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Github user yhuai commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
@@ -96,7 +96,7 @@ class SparkContext(config: SparkConf) extends Logging
with
Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/8822#issuecomment-141519890
This is a duplicate. Let's move convo to
https://github.com/apache/spark/pull/8749 Yes, definitely not OK to expose the
mutable object.
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--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/stat/test/StreamingTest.scala ---
@@ -0,0 +1,145 @@
+/*
+ * Licensed to the Apache
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--- Diff: python/pyspark/sql/functions.py ---
@@ -189,6 +190,14 @@ def approxCountDistinct(col, rsd=None):
return Column(jc)
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test this please
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Github user JoshRosen commented on the pull request:
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@rxin, should this also go into 1.5.1.?
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Github user ash211 commented on the pull request:
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Jenkins, test this please.
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Thanks! Merging to master.
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[WIP] [SPARK-9392] [SQL] Dataframe drop should work on unresolved columns
Dataframe drop should work on unresolved columns
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thanks for the merge :)
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Jenkins, retest this please.
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I'm closing this one. Probably not necessary to backport this one to
branch-1.5.
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/7971#issuecomment-141513624
Merged build finished. Test PASSed.
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Github user squito commented on the pull request:
https://github.com/apache/spark/pull/8438#issuecomment-141514207
Hi @mccheah , on the mima tests -- those check for binary compatabilities
across spark versions. If you click through to the link for the test build,
you'll see this in
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