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| author | Liang-Chi Hsieh <viirya@appier.com> | 2015-09-24 12:52:11 -0700 |
|---|---|---|
| committer | Yin Huai <yhuai@databricks.com> | 2015-09-24 12:52:11 -0700 |
| commit | b3862d3c59746ffb5f089aea4ff9e6f033a2c658 (patch) | |
| tree | a8d508b2dfb065dce4c0b166aead5de02d77a24e /sbin | |
| parent | 341b13f8f5eb118f1fb4d4f84418715ac4750a4d (diff) | |
| download | spark-b3862d3c59746ffb5f089aea4ff9e6f033a2c658.tar.gz spark-b3862d3c59746ffb5f089aea4ff9e6f033a2c658.tar.bz2 spark-b3862d3c59746ffb5f089aea4ff9e6f033a2c658.zip | |
[SPARK-10705] [SQL] Avoid using external rows in DataFrame.toJSON
JIRA: https://issues.apache.org/jira/browse/SPARK-10705
As described in the JIRA ticket, `DataFrame.toJSON` uses `DataFrame.mapPartitions`, which converts internal rows to external rows. We should use `queryExecution.toRdd.mapPartitions` that directly uses internal rows for better performance.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes #8865 from viirya/df-tojson-internalrow.
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