Github user HyukjinKwon commented on the issue:
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Yup, it will still fail but it fixes everything else to make it working
with Hadoop 3 within Spark. I think the current change is minimised as the
current status as is and I meant to target
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[SPARK-24613][SQL] Cache with UDF could not be matched with subsequent
dependent caches
## What changes were proposed in this pull request?
Wrap the logical plan with a
Github user vanzin commented on the issue:
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I'm talking about the `VersionsSuite` stuff. I think it needs to be a more
conscious decision about what happens.
If, when build with Hadoop 3, Spark will not support older versions of
Github user HyukjinKwon commented on the issue:
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@vanzin, which tests do you mean? Two types of tests are skipped. One is by
external Hive's limit which we can't control and the other one (two tests)
looks by a JDK bug which I think we
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@ueshin @kiszk Thanks for your comments. I fixed the problems.
I am not sure if I should use ```$i++ ``` or ```$i ++``` in the for loop.
It seems other people use ```$i ++```, so I also used
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Github user skonto commented on the issue:
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@foxish gentle ping.
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Github user tgravescs commented on the issue:
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the code here lgtm, I was trying to make one more pass through all the
scenarios but got stuck in meetings, will try to do it later tonight or
tomorrow morning but we can always have another
Github user tgravescs commented on the issue:
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ping @rdblue ^ . If I don't hear tomorrow, will file separate jira.
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Github user mgaido91 commented on the issue:
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@cloud-fan @gatorsmile the main issue which is causing the UT failures,
now, is that since before we were allowing overflows, in aggregations we could
have an overflow eventually fixed by another
Github user zsxwing commented on the issue:
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Thanks! Merging to master and 2.3.
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Github user vanzin commented on the issue:
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Which is, btw, a way of saying you should run `dev/run-tests` locally, at
least, when changing a dependency.
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Github user vanzin commented on the issue:
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I agree we should upgrade, but just changing the pom version will not work.
I have an internal patch for this and I needed small changes in a few other
places...
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@HyukjinKwon @hvanhovell Thanks for reviewing and merging!
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+/*
+ *
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GitHub user dhruve opened a pull request:
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[SPARK-24610] fix reading small files via wholeTextFiles
## What changes were proposed in this pull request?
The `WholeTextFileInputFormat` determines the `maxSplitSize` for the file/s
being
Github user maryannxue commented on the issue:
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@TomaszGaweda @viirya Nice suggestion about the doc. I'll update it.
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Github user Fokko commented on the issue:
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This was more than a year ago, we should eventually upgrade..
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Github user steveloughran commented on the issue:
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If jenkins is happy, this is good.
* Be interesting to see what happens in a build with the
hadoop-cloud-storage module, if it adds new dependencies
* regarding commons-config, know
Github user Fokko commented on the issue:
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@HyukjinKwon Ok, some Apache projects are really strict with the Jira
tickets.
@maropu I've updated the commit
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Github user MaxGekk commented on the issue:
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> I think the JIRA and this PR claim the current behaviour is righter?
@HyukjinKwon Yes but changing current behavior can potentially break
existing user's applications. I am not sure we can do
Github user vanzin commented on the issue:
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I pushed the change for that in:
https://github.com/vanzin/spark/commit/e6a862ecb83c64a0ea2f5bd469bc0febe25e15ba
In case anyone wants to take a look.
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--- Diff:
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@@ -1314,6 +1314,13 @@ object SQLConf {
"Other column
Github user vanzin commented on the issue:
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I filed SPARK-24611 to track some enhancements to this part of the code
that have been discussed here. Of those, I'd consider the "use task IDs instead
of TaskIdentifier" as something we could
Github user MaxGekk commented on a diff in the pull request:
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@@ -1314,6 +1314,13 @@ object SQLConf {
"Other column
Github user vanzin commented on the issue:
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Sounds good to me (although I'm trying the change locally and unit tests
are so far happy).
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> Ah, right, d'oh. I just checked about whether stages register with the
coordinator, and saw the duplicate registration for the resubmitted map stage.
Yeah I noticed that to but I think
Github user HyukjinKwon commented on the issue:
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re: https://github.com/apache/spark/pull/21598#issuecomment-398737499 I
missed the default value. Shall we set it to `false`? I think the JIRA and this
PR claim the current behaviour is
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Github user mridulm commented on the issue:
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> * t2 finishes before that kill message arrives, is allowed to commit.
> If that can happen it would generate a duplicate map output; but my guess
(hope?) is that the map output tracker would
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> if its a map stage then I don't expect it to be asking to commit.
Ah, right, d'oh. I just checked about whether stages register with the
coordinator, and saw the duplicate registration for
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> The test I added can sort of illustrate that if you look at what happens.
There are two stages (map stage 2, result stage 3), and the fetch failure
causes a retry of stage 3 plus a resubmission
Github user vanzin commented on the issue:
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I was referring to a race caused by asynchronously killing speculative
tasks. Granted it's incredibly unlikely to occur in real life:
- in s1a1 1, t1 and t2 are started for the same
Github user ueshin commented on the issue:
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LGTM pending tests.
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for PR 21581 at commit
Github user ueshin commented on the issue:
https://github.com/apache/spark/pull/21581
Jenkins, retest this please.
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