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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-23442) Reading from partitioned and bucketed table uses only bucketSpec.numBuckets partitions in all cases
Date Wed, 30 May 2018 07:28:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-23442?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-23442:
------------------------------------

    Assignee: Apache Spark

> Reading from partitioned and bucketed table uses only bucketSpec.numBuckets partitions
in all cases
> ---------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-23442
>                 URL: https://issues.apache.org/jira/browse/SPARK-23442
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core, SQL
>    Affects Versions: 2.2.1
>            Reporter: Pranav Rao
>            Assignee: Apache Spark
>            Priority: Major
>
> Through the DataFrameWriter[T] interface I have created a external HIVE table with 5000
(horizontal) partitions and 50 buckets in each partition. Overall the dataset is 600GB and
the provider is Parquet.
> Now this works great when joining with a similarly bucketed dataset - it's able to avoid
a shuffle. 
> But any action on this Dataframe(from _spark.table("tablename")_), works with only 50
RDD partitions. This is happening because of [createBucketedReadRDD|https://github.com/apachttps:/github.com/apache/spark/blob/branch-2.3/sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.she/spark/blob/branch-2.3/sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.sc].
So the 600GB dataset is only read through 50 tasks, which makes this partitioning + bucketing
scheme not useful.
> I cannot expose the base directory of the parquet folder for reading the dataset, because
the partition locations don't follow a (basePath + partSpec) format.
> Meanwhile, are there workarounds to use higher parallelism while reading such a table?

>  Let me know if I can help in any way.



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