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cc @cloud-fan
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@@ -64,6 +64,12 @@ private[spark] class EventLoggingListener(
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Hey, would definitely like to see this included in Spark. We are having
issues with OOM errors training pretty small RFs. It could have something to do
with the cross validation
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Thank YOU, always! :)
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@dongjoon-hyun my apologies, thanks for bringing this to my attention. I
had to hang merge and didn't realize the mismatch. Opened a new PR to fix that.
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[SPARK-19399][SPARKR] fix tests broken by merge
## What changes were proposed in this pull request?
fix test
## How was this patch tested?
manual
You can merge this
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/16949
[SPARK-16122][CORE] Add rest api for job environment
## What changes were proposed in this pull request?
add rest api for job environment.
## How was this patch tested?
Github user viirya commented on a diff in the pull request:
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--- Diff:
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@@ -340,3 +341,91 @@ object CaseKeyWhen {
Github user jisookim0513 commented on a diff in the pull request:
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@@ -64,6 +64,12 @@ private[spark] class EventLoggingListener(
Github user JasonMWhite commented on the issue:
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Modified as suggested. Don't think this has been through CI at all yet.
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Github user budde commented on the issue:
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Looks like I missed a Catalyst test. Updating the PR.
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--- Diff:
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@@ -742,7 +742,7 @@ public boolean append(Object kbase, long koff, int
Github user viirya commented on the issue:
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retest this please.
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cool. It has been merged.
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@@ -195,17 +198,39 @@ class BlockManagerMasterEndpoint(
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@@ -1131,14 +1131,47 @@ private[spark] class BlockManager(
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Yes, refined : )
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@erikerlandson Are you still working on this PR? Thanks! Miao
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I also keep considering other ways to fix this...
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ok to test
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[SPARK-19618][SQL] Inconsistency wrt max. buckets allowed from Dataframe
API vs SQL
## What changes were proposed in this pull request?
Jira:
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Let me try to review further at my best once it is decided.
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cc @cloud-fan, could I ask if you think matching it seems reasonable? I
wrote some details below for you to track this issue.
Currently, JSON produces
```scala
Seq("""{"a":
Github user uncleGen commented on the issue:
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@srowen
> Does it really not work if not enough receivers can schedule?
That's not what I want to express. What I mean is the stream output can not
operate.
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GitHub user zsxwing opened a pull request:
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[SPARK-19617][SS]Don't interrupt 'mkdirs' to workaround HADOOP-14084
## What changes were proposed in this pull request?
This PR adds a workaround for
Github user erenavsarogullari commented on the issue:
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Hi All,
All comments are addressed and this is ready for re-review.
@markhamstra, if it is suitable, i plan to address _removing
SchedulingMode.NONE_ via separated PR. In the
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cc @felixcheung
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+1 @sethah
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BTW, in the future I'd prefer to separate the examples and they Python API.
I'm not sure if we ever fully decided on a normal protocol for this, but it
certainly would make the review easier :)
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