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From "Josh Wills (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (CRUNCH-485) groupByKey on Spark incorrect if key is Avro record with defined sort order
Date Thu, 08 Jan 2015 20:53:37 GMT

     [ https://issues.apache.org/jira/browse/CRUNCH-485?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Josh Wills updated CRUNCH-485:
------------------------------
    Attachment: CRUNCH-485b.patch

Now with a test, this is likely to be the version I commit by tomorrow w/o any objections.

> groupByKey on Spark incorrect if key is Avro record with defined sort order
> ---------------------------------------------------------------------------
>
>                 Key: CRUNCH-485
>                 URL: https://issues.apache.org/jira/browse/CRUNCH-485
>             Project: Crunch
>          Issue Type: Bug
>          Components: Core
>    Affects Versions: 0.11.0
>            Reporter: Tycho Lamerigts
>            Assignee: Josh Wills
>         Attachments: CRUNCH-485.patch, CRUNCH-485b.patch
>
>
> GroupByKey on Spark is incorrect if the key type is an Avro record with defined sort
order (http://avro.apache.org/docs/1.7.7/spec.html#order).
> Instead, it serializes the entire avro record to a binary blob (byte array) and groups
identical blobs. This is wrong. By contrast, groupByKey on MapReduce works as expected, so
it does take Avro's sort order into account.
> The culprit is probably the following code from org.apache.crunch.impl.spark.collect.PGroupedTableImpl#getJavaRDDLikeInternal
> {code}
> groupedRDD = parentRDD.map(new PairMapFunction(ptype.getOutputMapFn(), runtime.getRuntimeContext()))
>           .mapToPair(new MapOutputFunction(keySerde, valueSerde))
>           .groupByKey(numPartitions);
> {code}
> where MapOutputFunction simply converts the entire key object to a binary blob, without
taking sort order into account.



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