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Posted to reviews@spark.apache.org by ueshin <gi...@git.apache.org> on 2014/07/11 11:22:32 UTC

[GitHub] spark pull request: [SPARK-2446][SQL] Add BinaryType support to Pa...

GitHub user ueshin opened a pull request:

    https://github.com/apache/spark/pull/1373

    [SPARK-2446][SQL] Add BinaryType support to Parquet I/O.

    To support `BinaryType`, the following changes are needed:
    - Make `StringType` use `OriginalType.UTF8`
    - Add `BinaryType` using `PrimitiveTypeName.BINARY` without `OriginalType`

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/ueshin/apache-spark issues/SPARK-2446

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/spark/pull/1373.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #1373
    
----
commit 616e04a989edce9f5109a3b2ad11b78e1e0f1a77
Author: Takuya UESHIN <ue...@happy-camper.st>
Date:   2014-07-09T15:25:08Z

    Make StringType use OriginalType.UTF8.

commit ecacb925c4e1f2dbf863b604ad2600cc8c9663d8
Author: Takuya UESHIN <ue...@happy-camper.st>
Date:   2014-07-11T09:13:46Z

    Add BinaryType support to Parquet I/O.

----


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[GitHub] spark pull request: [SPARK-2446][SQL] Add BinaryType support to Pa...

Posted by marmbrus <gi...@git.apache.org>.
Github user marmbrus commented on the pull request:

    https://github.com/apache/spark/pull/1373#issuecomment-48760249
  
    Thanks for the patch!  One quick question: will this change the behavior when loading in string data that was saved with previous versions of Spark SQL?


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[GitHub] spark pull request: [SPARK-2446][SQL] Add BinaryType support to Pa...

Posted by ueshin <gi...@git.apache.org>.
Github user ueshin commented on the pull request:

    https://github.com/apache/spark/pull/1373#issuecomment-48781530
  
    @marmbrus Yes, I think so.
    But this new behavior is the same as Avro, Thrift and the next Hive (0.14).
    To load the string data saved with previous versions, `Cast` to `StringType` will be needed.


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[GitHub] spark pull request: [SPARK-2446][SQL] Add BinaryType support to Pa...

Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:

    https://github.com/apache/spark/pull/1373#issuecomment-48710936
  
    QA tests have started for PR 1373. This patch merges cleanly. <br>View progress: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/16565/consoleFull


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[GitHub] spark pull request: [SPARK-2446][SQL] Add BinaryType support to Pa...

Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:

    https://github.com/apache/spark/pull/1373#issuecomment-48718560
  
    QA results for PR 1373:<br>- This patch PASSES unit tests.<br>- This patch merges cleanly<br>- This patch adds no public classes<br><br>For more information see test ouptut:<br>https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/16565/consoleFull


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[GitHub] spark pull request: [SPARK-2446][SQL] Add BinaryType support to Pa...

Posted by marmbrus <gi...@git.apache.org>.
Github user marmbrus commented on the pull request:

    https://github.com/apache/spark/pull/1373#issuecomment-48970135
  
    Thanks for adding this.  I've merge this into master, but not branch-1.0 due to the change in semantics.  I also updated the commit message to include a disclaimer about the new semantics.


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[GitHub] spark pull request: [SPARK-2446][SQL] Add BinaryType support to Pa...

Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:

    https://github.com/apache/spark/pull/1373


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[GitHub] spark pull request: [SPARK-2446][SQL] Add BinaryType support to Pa...

Posted by marmbrus <gi...@git.apache.org>.
Github user marmbrus commented on the pull request:

    https://github.com/apache/spark/pull/1373#issuecomment-48969674
  
    Okay, I figured that was the case, but you are right that compatibility with other systems is the right thing to do here.


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