Repository: spark Updated Branches: refs/heads/master 17284db31 -> fe12277b4
Fix doc typo Straightforward fix on doc typo Author: Jeff Zhang <[email protected]> Closes #8019 from zjffdu/master and squashes the following commits: aed6e64 [Jeff Zhang] Fix doc typo Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/fe12277b Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/fe12277b Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/fe12277b Branch: refs/heads/master Commit: fe12277b40082585e40e1bdf6aa2ebcfe80ed83f Parents: 17284db Author: Jeff Zhang <[email protected]> Authored: Thu Aug 6 21:03:47 2015 -0700 Committer: Reynold Xin <[email protected]> Committed: Thu Aug 6 21:03:47 2015 -0700 ---------------------------------------------------------------------- docs/tuning.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/fe12277b/docs/tuning.md ---------------------------------------------------------------------- diff --git a/docs/tuning.md b/docs/tuning.md index 572c727..6936912 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. --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
