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Github user michaelmior commented on the issue:
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@jerryshao I agree that the history server itself doesn't provide useful
information but for detailed analysis I've found it helpful to persist the logs
and write my own scripts to analyze
Github user jerryshao commented on the issue:
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Yes, I understand your scenario, but my concern is that your proposal is
quite scenario specific, it may well serve your scenario, but somehow it breaks
the design purpose of KafkaRDD. From my
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Github user cloud-fan commented on the issue:
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a late LGTM :)
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--- Diff:
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@@ -186,8 +186,7 @@ case class
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Github user mgaido91 commented on the issue:
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@yanboliang may you please take a look at this when you have time? Thanks.
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--- Diff: python/pyspark/sql/readwriter.py ---
@@ -420,7 +425,22 @@ def csv(self, path, schema=None, sep=None,
encoding=None, quote=None, escape=Non
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Github user mpjlu commented on the issue:
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Ok, thanks. we don't need to change the code here.
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--- Diff: core/src/main/scala/org/apache/spark/deploy/master/Master.scala
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@@ -265,6 +265,9 @@ private[deploy] class Master(
val app =
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Github user WeichenXu123 commented on the issue:
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`require` is better i think
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Can one of the admins verify this patch?
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GitHub user guoxiaolongzte opened a pull request:
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[SPARK-22127][CORE]The Master Register Application Function requires an
warn log to increase the waiting status
## What changes were proposed in this pull request?
The Master
Github user squito commented on the issue:
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whoops, sorry I wrote [CORE] out of habit!
> Spark SQL might not be deployed in the HDFS system. Conceptually, this
HDFS-specific codes should not be part of our HiveExternalCatalog .
Github user mpjlu commented on the issue:
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Sorry, I got wrong.
So you think assert is better here? now we use require.
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Why not possible ? `meanGammaChange` is always positive. The loop will
become `while (true) {...}`
and should use `require` instead of `assert`
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I will update this PR after #19350 get merged. We need to address another
issue first. Thanks!
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Because epsilon is Double, negative value should not cause the code run
into dead loop. All other setting in LDA using require for check or no check.
Should we use assert only for this change?
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OK, I will change it to assert.
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Github user lonelytrooper commented on the issue:
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lonelytrooper... : Pwill more executors be used in RDD#mapPartitions
way ? I'll try that later to see if it works. I think if Spark provides a
convenient way for this , it would help
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retest this please.
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Github user caneGuy commented on the issue:
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@cloud-fan Sorry for bothering you.Could you help review this?Thanks
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OK. But I'm afraid accidently negative value cause the code run into dead
loop. Maybe adding `assert` is better.
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Not check is also ok, user should know epsilon > 0
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[SPARK-22126][ML] Fix model-specific optimization support for ML tuning
## What changes were proposed in this pull request?
Push down fitting parallelization code from
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Hi @michaelmalak , history server only shows the last state of application
before finished, and cached blocks can be evicted/unpersisted during the middle
of application. So you probably cannot
Github user jerryshao commented on the issue:
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Hi @loneknightpy , think a bit on your PR, I think this can also be done in
the user side. User could create several threads in one task
(RDD#mapPartitions) to consume the records concurrently,
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--- Diff:
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@@ -328,6 +331,22 @@ class
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@@ -671,8 +671,9 @@ private[spark] class TaskSetManager(
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--- Diff: core/src/main/scala/org/apache/spark/scheduler/TaskInfo.scala ---
@@ -74,6 +81,10 @@ class TaskInfo(
gettingResultTime = time
}
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--- Diff: core/src/main/scala/org/apache/spark/scheduler/TaskInfo.scala ---
@@ -66,6 +66,13 @@ class TaskInfo(
*/
var finishTime: Long = 0
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Added.
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I'd add
https://github.com/apache/spark/pull/19236
https://github.com/apache/spark/pull/19244
https://github.com/apache/spark/pull/19300
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retest this please
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LGTM, merging to master!
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retest this please
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