[jira] [Updated] (PIG-5029) Optimize sort case when data is skewed

["liyunzhang_intel (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/PIG-5029?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

liyunzhang_intel updated PIG-5029:
----------------------------------
    Attachment: PIG-5029_3.patch

> Optimize sort case when data is skewed
> --------------------------------------
>
>                 Key: PIG-5029
>                 URL: https://issues.apache.org/jira/browse/PIG-5029
>             Project: Pig
>          Issue Type: Sub-task
>          Components: spark
>            Reporter: liyunzhang_intel
>            Assignee: liyunzhang_intel
>             Fix For: spark-branch
>
>         Attachments: PIG-5029.patch, PIG-5029_2.patch, PIG-5029_3.patch, SkewedData_L9.docx
>
>
> In PigMix L9.pig
> {code}
> register $PIGMIX_JAR
> A = load '$HDFS_ROOT/page_views' using org.apache.pig.test.pigmix.udf.PigPerformanceLoader()
>     as (user, action, timespent, query_term, ip_addr, timestamp,
>         estimated_revenue, page_info, page_links);
> B = order A by query_term parallel $PARALLEL;
> store B into '$PIGMIX_OUTPUT/L9out';
> {code}
> The pig physical plan will be changed to spark plan and to spark lineage:
> {code}
> [main] 2016-09-08 01:49:09,844 DEBUG converter.StoreConverter (StoreConverter.java:convert(110)) - RDD lineage: (23) MapPartitionsRDD[8] at map at StoreConverter.java:80 []
>  |   MapPartitionsRDD[7] at mapPartitions at SortConverter.java:58 []
>  |   ShuffledRDD[6] at sortByKey at SortConverter.java:56 []
>  +-(23) MapPartitionsRDD[3] at map at SortConverter.java:49 []
>     |   MapPartitionsRDD[2] at mapPartitions at ForEachConverter.java:64 []
>     |   MapPartitionsRDD[1] at map at LoadConverter.java:127 []
>     |   NewHadoopRDD[0] at newAPIHadoopRDD at LoadConverter.java:102 []
> {code}
> We use [sortByKey|https://github.com/apache/pig/blob/spark/src/org/apache/pig/backend/hadoop/executionengine/spark/converter/SortConverter.java#L56] to implement the sort feature. Although [RangePartitioner|https://github.com/apache/spark/blob/d6dc12ef0146ae409834c78737c116050961f350/core/src/main/scala/org/apache/spark/Partitioner.scala#L106] is used by RDD.sortByKey and RangePartitiner will sample data and ranges the key roughly into equal range, the test result(attached  document) shows that one partition will load most keys and take long time to finish.



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