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Posted to commits@kylin.apache.org by sh...@apache.org on 2018/01/02 06:40:32 UTC
kylin git commit: Add Grow Force to powerby
Repository: kylin
Updated Branches:
refs/heads/document 18c0fa975 -> af6c05328
Add Grow Force to powerby
Project: http://git-wip-us.apache.org/repos/asf/kylin/repo
Commit: http://git-wip-us.apache.org/repos/asf/kylin/commit/af6c0532
Tree: http://git-wip-us.apache.org/repos/asf/kylin/tree/af6c0532
Diff: http://git-wip-us.apache.org/repos/asf/kylin/diff/af6c0532
Branch: refs/heads/document
Commit: af6c053281346387a92d48492f1d60befceab738
Parents: 18c0fa9
Author: shaofengshi <sh...@apache.org>
Authored: Tue Jan 2 14:40:24 2018 +0800
Committer: shaofengshi <sh...@apache.org>
Committed: Tue Jan 2 14:40:24 2018 +0800
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website/community/poweredby.md | 4 +++-
1 file changed, 3 insertions(+), 1 deletion(-)
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http://git-wip-us.apache.org/repos/asf/kylin/blob/af6c0532/website/community/poweredby.md
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diff --git a/website/community/poweredby.md b/website/community/poweredby.md
index e0e67ee..7c83ff1 100644
--- a/website/community/poweredby.md
+++ b/website/community/poweredby.md
@@ -54,4 +54,6 @@ __Companies & Organizations__
* [4399.com](http://www.4399.com/)
* Apache Kylin is used at 4399.com for Big Data Analytics on Hadoop, which let us query massive data set at sub-second latency.
* [ZTE 中兴](http://www.zte.com.cn/)
- * Apache Kylin is one of the foundational components of ZTE's Big Data Platform. ZTE uses Apache Kylin to provide OLAP capabilities to customers in the telecom, government, banking, finance and other industries.
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+ * Apache Kylin is one of the foundational components of ZTE's Big Data Platform. ZTE uses Apache Kylin to provide OLAP capabilities to customers in the telecom, government, banking, finance and other industries.
+* [Grow Force](http://www.300.cn/)
+ * Kyin in Grow Force are mainly in the new data warehouse system and the data computing of BI reports. On one hand, it increases our development efficiency and eliminates the need for the developer to manually write HQL/SQL statement to query dimension data; on the other hand, it decouples the existing system design. The data computing layer thus mainly includes the real-time calculation of Spark and the offline calculation of HQL. After Kylin being introduced, the whole offline calculation can be moved to Kylin, which improves the flexibility greatly.
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