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Github user shaneknapp commented on the issue:
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i've been having trouble getting this build to pass, and i'm testing a few
other modules on top of yours. if i have problems, i'll revert the extraneous
changes and build yours.
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ugh hang on. lemme fix that crap. (this is on a testing branch in my
personal spark form)
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Is this really necessary? It will always be "1", since client-mode apps are
not re-tried (the YARN AM might be, but the driver is not). That makes it not
really useful.
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def stop(): Unit
Github user icexelloss commented on the issue:
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Tests pass now. This comment
https://github.com/apache/spark/pull/22104/files#r210414941 requires some
attention. @cloud-fan Do you think this is the right way to handle
GenericInternalRow
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Github user BryanCutler commented on the issue:
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@shaneknapp would you mind kicking off a test on one of the workers with
python 3.5 and pyarrow 0.10.0 to verify this PR is passing under that env?
Sorry for the special request, this should be
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How do users manually migrate and keep compatibility?That is the
problem I have, I am all for reverting, if we have an easy way for users to
migrate to the internal one.
Note that
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@gatorsmile Thank you for your reply. Could you elaborate on your
suggestion?
>A general suggestion. To avoid introducing the regressions, how about
implementing a new one without changing the
Github user gengliangwang commented on the issue:
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But it seems that creating a configuration makes everyone happy...
I will wait for another day to get more thoughts.
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@tgravescs I saw your comments. Just feel that we can make it simpler by
reverting it.
For hive tables that used Databricks spark-avro, the tables can still using
the Databricks
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"This usually
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the added tests are good. This is pretty nit-picky, but looking at the
whole test suite, are there any tests that check for anything other than the
first byte (or array length)? Seems the longer
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> I would propose we fix the things that are using the round robin type
partitioning (repartition) but then unordered things like zip/MapPartitions
(via user code) we document or perhaps give the
Github user shaneknapp commented on the issue:
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oh wow, nice find @HyukjinKwon! code archaeology ftw! :)
anyways: that PR went through about a week after i started here @ the
amplab and i don't think i even had access to the build
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@HyukjinKwon I am worrying about the design of a mixture of representation
s"" and code""? When the design is not good, it is hard to maintain it and add
new code based on this. Let @cloud-fan
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[SPARK-25134][SQL] Csv column pruning with checking of headers throws
incorrect error
## What changes were proposed in this pull request?
When column pruning is turned on the
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Are they all instances to fix?
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[SPARK-24665][PySpark][FollowUp] Use SQLConf in PySpark to manage all sql
configs
## What changes were proposed in this pull request?
Follow up for SPARK-24665, find some others hard
Github user squito commented on the issue:
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restest this please
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lgtm, just a small reword in one of the msgs suggested by maxgekk.
@hvanhovell @gatorsmile would you like to review this as well?
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@Victsm @vanzin i want to get this going, is it better if I have a PR up
with the requested changes and concerns?
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can you please close this pr @deshanxiao ?
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retest this please
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[SPARK-25133][SQL][Doc]AVRO data source guide
## What changes were proposed in this pull request?
Create documentation for AVRO data source.
The new page will be linked in
Github user tgravescs commented on the issue:
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Personally I don't want to talk about implementation until we decide what
we want our semantics to be around the unordered operations because that
affects any implementation.
If we are
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Thanks! merging to master.
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@holdenk somehow, Jenkins didn't execute the tests.
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