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Posted to commits@spark.apache.org by rx...@apache.org on 2014/05/31 07:05:00 UTC
git commit: updated link to mailing list
Repository: spark
Updated Branches:
refs/heads/master 9c1f204d8 -> 23ae36630
updated link to mailing list
Author: nchammas <ni...@gmail.com>
Closes #923 from nchammas/patch-1 and squashes the following commits:
65c4d18 [nchammas] updated link to mailing list
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/23ae3663
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/23ae3663
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/23ae3663
Branch: refs/heads/master
Commit: 23ae36630aa5e6ca4a86e32912a99408129dff7b
Parents: 9c1f204
Author: nchammas <ni...@gmail.com>
Authored: Fri May 30 22:04:57 2014 -0700
Committer: Reynold Xin <rx...@apache.org>
Committed: Fri May 30 22:04:57 2014 -0700
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docs/tuning.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/23ae3663/docs/tuning.md
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diff --git a/docs/tuning.md b/docs/tuning.md
index c423041..4917c11 100644
--- a/docs/tuning.md
+++ b/docs/tuning.md
@@ -253,4 +253,4 @@ This has been a short guide to point out the main concerns you should know about
Spark application -- most importantly, data serialization and memory tuning. For most programs,
switching to Kryo serialization and persisting data in serialized form will solve most common
performance issues. Feel free to ask on the
-[Spark mailing list](http://groups.google.com/group/spark-users) about other tuning best practices.
+[Spark mailing list](https://spark.apache.org/community.html) about other tuning best practices.