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@dongjoon-hyun merged, thank you, did not know how to skip lint rule there.
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This is a regression introduced in 2.3; unfortunately we did not notice it
until now.
On Tue, Oct 2, 2018 at 4:56 AM Shahid wrote:
> Hi @mridulm
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@cloud-fan could you please help me with this PR and take it one step
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Thanks a lot @dongjoon-hyun
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>> So is there no behavior change if your master specifies only one master?
If user specifies only 1 master then there is no behavioral change.
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Thank you, @shahidki31 .
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Thanks, @HyukjinKwon !
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Hi @mridulm , Can't we limit the task information by setting
'spark.ui.retainedTasks' lesser, to avoid OOM? correct me if I am wrong.
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I will close this and open the actual Pr shortly. Thank you everyone for
the great reviews.
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Previously I opened a WIP PR
[here](https://github.com/apache/spark/pull/21916) and
[here](https://github.com/rezasafi/spark/pull/1). I have applied all the
comments that I received there to this
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@gengliangwang is right; there are still things that need to be done when
the UI is disabled; job, stage and executor info are all still exposed even if
the UI is disabled, and the task even
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@dongjoon-hyun Could you help me fix the website?
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[SPARK-25583][DOC][BRANCH-2.3]Add history-server related configuration in
the documentation.
## What changes were proposed in this pull request?
This is a follow up PR for the PR,
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Thanks! Merged to master.
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Thanks for looking into this @viirya ! I agree that there are lots of
cases where casting to another type is intentional and works fine, so this
isn't a bug. The only other idea I have is to
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Great, @gatorsmile ! Could you update Spark website properly, too?
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`spark.history.fs.endEventReparseChunkSize` and
`spark.history.fs.inProgressOptimization.enabled` exist since `branch-2.4`. So,
this PR lands at master/2.4. If you want to fix some in
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For a query similar to the one in the PR description:
`a.join(b, a("id") === b("id"), "inner").join(c, a("id") === b("id"),
"inner"`
It is interpreted as a cartesian products now.
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@squito
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Merging to master.
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BTW, I chose the most official one, `Sam Davarnia `.
But, it seems that your GitHub is not happy with that. Next time, you had
better be consistent in your commit message.
```
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Thanks will do!
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Thanks @viirya, your analysis is correct.
Unfortunately an attribute doesn't have a reference to its dataset so I
don't think this scenario can be solved easily. I believe the good
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--- Diff: python/pyspark/worker.py ---
@@ -84,13 +84,36 @@ def wrap_scalar_pandas_udf(f, return_type):
arrow_return_type =
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LGTM
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Since it's merged into `branch-2.2`, could you close this PR? GitHub only
closes the PRs against `master` branch. :)
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Rebased to `master` due to https://github.com/apache/spark/pull/22599.
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[SPARK-24958] Add executors' process tree total memory information to
heartbeat signals.
Spark executors' process tree total memory information can be really
useful. Currently such information
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@HyukjinKwon is this ready to be merged in, or is there more feedback to be
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Retest this please.
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You mean http://spark.apache.org/versioning-policy.html and the reference
to 2.4? I think that's still valid. When 2.4 is released, I'd propose to change
that to refer to 3.0 being released .. I
GitHub user kmanamcheri opened a pull request:
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HiveClient.getPartitionsByFilter should not throw an exception if HMS
retries directSql
## What changes were proposed in this pull request?
When using partition filter pushdown to
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@mallman @cloud-fan @ericl @rezasafi
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@vanzin any reason why liveStore is hardcoded to be in-memory ? Any
implications of making it disk backed ? That might be another option to unblock
- requires a config change to existing
Github user michalsenkyr commented on the issue:
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I restructured the code in this commit to allow easier addition of
array/list support in the future.
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Task events still might need to be processed - even for live applications
with the UI disabled. See the API that has been mentioned before
(`SparkStatusTracker`) for why. Processing task events is
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