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--- Diff:
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@@ -1255,6 +1255,97 @@ class TaskSetManagerSuite extends
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--- Diff: docs/sql-programming-guide.md ---
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--- Diff: docs/sql-programming-guide.md ---
@@ -968,6 +968,13 @@ Configuration of Parquet can be done using the
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+/*
+ *
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@@ -52,4 +55,13 @@ public abstract void
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@@ -117,6 +118,12 @@ public void
Github user squito commented on the issue:
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I'm not sure I totally follow the sequence of events, but I get the feeling
this should be handled in yarn, not spark.
Also, I agree with Jerry, it seems like your `completedContainerIdSet`
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Have a look at http://spark.apache.org/contributing.html -- maybe prefix
the title with `[MINOR][DOCS]` for completeness?
Are there other instances of this same issue in the Pyspark docs?
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--- Diff:
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@@ -998,6 +1047,172 @@ class LinearRegressionSuite
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@@ -0,0 +1,142 @@
+/*
+ * Licensed to the Apache
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Update quickstart python dataset example
The python spark datasets example for the mapreduce was returning error,
when using .select().as() function.
Replaces the error to use the
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[SPARK-22066][BUILD] Update checkstyle to 8.2, enable it, fix violations
## What changes were proposed in this pull request?
Update plugins, including scala-maven-plugin, to latest
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--- Diff: core/src/main/scala/org/apache/spark/executor/Executor.scala ---
@@ -115,6 +115,7 @@ private[spark] class Executor(
if (!isLocal) {
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package
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I don't really have a readily available cluster that can easily put that
much pressure on the listener bus; I tried with the one I have and monitored
the listener bus metrics, and found pretty much
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retest this please
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Github user susanxhuynh commented on a diff in the pull request:
https://github.com/apache/spark/pull/19272#discussion_r139772286
--- Diff:
resource-managers/mesos/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosCredentialRenewer.scala
---
@@ -0,0 +1,150 @@
+/*
Github user susanxhuynh commented on a diff in the pull request:
https://github.com/apache/spark/pull/19272#discussion_r139726573
--- Diff:
resource-managers/mesos/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosCredentialRenewer.scala
---
@@ -0,0 +1,150 @@
+/*
Github user susanxhuynh commented on a diff in the pull request:
https://github.com/apache/spark/pull/19272#discussion_r139779444
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
---
@@ -159,6 +159,13 @@ class
Github user squito commented on the issue:
https://github.com/apache/spark/pull/19211
lgtm
do you know how much better this makes it? Eg., if we had an existing case
where things go haywire in dynamic allocation because of this -- we could see
if after this change, the only
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/18659
**[Test build #81945 has
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/81945/testReport)**
for PR 18659 at commit
Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/19211#discussion_r139787945
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/AsyncEventQueue.scala ---
@@ -0,0 +1,196 @@
+/*
+ * Licensed to the Apache Software
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/19281
Can one of the admins verify this patch?
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Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/19218
You just need to fix `InsertIntoHiveTable `. It is not related to
`Insertintohadoopfsrelationcommand.scala`. In your test cases, you just need to
set `spark.sql.hive.convertMetastoreParquet` to
GitHub user maryannxue opened a pull request:
https://github.com/apache/spark/pull/19281
[SPARK-21998][SQL] SortMergeJoinExec did not calculate its outputOrdering
correctly during physical planning
## What changes were proposed in this pull request?
Right now the
Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/19218
Table-level metadata has the highest priority. In the table-level metadata,
`compression` has a higher priority than `parquet.compression`. If the is not
specified, we need to check the
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