GitHub user yhuai opened a pull request:
https://github.com/apache/spark/pull/8515
[SPARK-10339] [SPARK-10334] [SQL]Partitioned table scan
This fixes the problem that scanning partitioned table causes driver have a
high memory pressure and takes down the cluster. Also, with this fix, we will
be able to correctly show the query plan of a query consuming partitioned
tables.
https://issues.apache.org/jira/browse/SPARK-10339
https://issues.apache.org/jira/browse/SPARK-10334
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/yhuai/spark partitionedTableScan
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/8515.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 #8515
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commit 2390b066f56eb9e43beb68db749bc5db1366c95a
Author: Yin Huai <[email protected]>
Date: 2015-08-28T22:46:43Z
Only create a single Filter/Project for partitioned table scan instead of
create one Filter/Project for every partition.
commit f6303ba01afdd049d1aa69e65dea570b81678a5d
Author: Yin Huai <[email protected]>
Date: 2015-08-28T22:51:18Z
Throw an exception if parquet file's schema has different number of fields
with the table schema.
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