GitHub user zzcclp opened a pull request:
https://github.com/apache/carbondata/pull/1245
[CARBONDATA-1366]Change rdd storage level to 'MEMORY_AND_DISK_SER' to
improve loading performance when sort_scope=global_sort
My testing env and configs are as followings:
**Env:**
6 executors, 9G mem + 6 cores per executor
**Configs:**
SINGLE_PASS=true
SORT_SCOPE=GLOBAL_SORT
spark.memory.fraction=0.5
if using 'convertRDD.persist(StorageLevel.MEMORY_AND_DISK_SER)' in method
'org.apache.carbondata.spark.load.DataLoadProcessBuilderOnSpark.loadDataUsingGlobalSort',
it takes about **7.2** min to load 144136697 lines (10.9 G parquet files), and
if using 'convertRDD.persist(StorageLevel.MEMORY_AND_DISK)', it takes about
**9.5** min to load 144136697 lines.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/zzcclp/carbondata CARBONDATA-1366
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/carbondata/pull/1245.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 #1245
----
commit b50a3bb590d53e7749665e2f20b6a78ca963561f
Author: Zhang Zhichao <441586...@qq.com>
Date: 2017-08-08T09:42:40Z
[CARBONDATA-1366]Change rdd storage level to 'MEMORY_AND_DISK_SER' to
improve loading performance when sort_scope=global_sort
Change rdd storage level to 'MEMORY_AND_DISK_SER' to improve loading
performance when sort_scope=global_sort
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