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| author | Jeff Zhang <zjffdu@apache.org> | 2015-08-06 21:03:47 -0700 |
|---|---|---|
| committer | Reynold Xin <rxin@databricks.com> | 2015-08-06 21:03:47 -0700 |
| commit | fe12277b40082585e40e1bdf6aa2ebcfe80ed83f (patch) | |
| tree | 10b70490618a275e65711d5d7b20e3433bca36e9 /docs/tuning.md | |
| parent | 17284db314f52bdb2065482b8a49656f7683d30a (diff) | |
| download | spark-fe12277b40082585e40e1bdf6aa2ebcfe80ed83f.tar.gz spark-fe12277b40082585e40e1bdf6aa2ebcfe80ed83f.tar.bz2 spark-fe12277b40082585e40e1bdf6aa2ebcfe80ed83f.zip | |
Fix doc typo
Straightforward fix on doc typo
Author: Jeff Zhang <zjffdu@apache.org>
Closes #8019 from zjffdu/master and squashes the following commits:
aed6e64 [Jeff Zhang] Fix doc typo
Diffstat (limited to 'docs/tuning.md')
| -rw-r--r-- | docs/tuning.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/tuning.md b/docs/tuning.md index 572c7270e4..6936912a6b 100644 --- a/docs/tuning.md +++ b/docs/tuning.md @@ -240,7 +240,7 @@ worth optimizing. ## Data Locality Data locality can have a major impact on the performance of Spark jobs. If data and the code that -operates on it are together than computation tends to be fast. But if code and data are separated, +operates on it are together then computation tends to be fast. But if code and data are separated, one must move to the other. Typically it is faster to ship serialized code from place to place than a chunk of data because code size is much smaller than data. Spark builds its scheduling around this general principle of data locality. |