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Posted to commits@kylin.apache.org by sh...@apache.org on 2017/04/17 03:13:43 UTC
kylin git commit: miss a change
Repository: kylin
Updated Branches:
refs/heads/document c4bab4e47 -> 6cf24dd71
miss a change
Project: http://git-wip-us.apache.org/repos/asf/kylin/repo
Commit: http://git-wip-us.apache.org/repos/asf/kylin/commit/6cf24dd7
Tree: http://git-wip-us.apache.org/repos/asf/kylin/tree/6cf24dd7
Diff: http://git-wip-us.apache.org/repos/asf/kylin/diff/6cf24dd7
Branch: refs/heads/document
Commit: 6cf24dd718b12738982e647c97c13b5e05f2ff40
Parents: c4bab4e
Author: shaofengshi <sh...@apache.org>
Authored: Mon Apr 17 11:13:39 2017 +0800
Committer: shaofengshi <sh...@apache.org>
Committed: Mon Apr 17 11:13:39 2017 +0800
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website/community/poweredby.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
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http://git-wip-us.apache.org/repos/asf/kylin/blob/6cf24dd7/website/community/poweredby.md
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diff --git a/website/community/poweredby.md b/website/community/poweredby.md
index d9ed2a5..d857de5 100644
--- a/website/community/poweredby.md
+++ b/website/community/poweredby.md
@@ -42,4 +42,4 @@ __Companies & Organizations__
* [LeEco](http://www.leeco.com/)
* Apache Kylin has been used as a part of OLAP engine and data query engine for big data platform at LeEco, which is powering various big data business, such as stream media data and cloud data.
* [Toutiao](https://www.toutiao.com/)
- * As the most popular mobile news app in China, Toutiao has over 78 million daily active users, we need OLAP capability on **Trillion** level data, and only Kylin can fulfill. Take an example, the Cube for the videos analysis has more than 2.4 trillion source records, taking 4+ TB storage (source file more than 100 TB); Most of the queries can be finished in less than 1 second (same query need couple hours in Hive). From another perspective, Kylin reduces the pressure of our Hadoop cluster. This is what called "build once, use many".
+ * As the most popular mobile news app in China, Toutiao has over 78 million daily active users (collected on Feb 2017), we need OLAP capability on **Trillion** level data, and only Kylin can fulfill. Take an example, the Cube for the videos analysis has more than 2.4 trillion source records, taking 4+ TB storage (source file more than 100 TB); Most of the queries can be finished in less than 1 second (same query need couple hours in Hive). From another perspective, Kylin reduces the pressure of our Hadoop cluster. This is what called "build once, use many".