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Subject [1/2] incubator-carbondata git commit: Add website link in readme
Date Mon, 26 Dec 2016 13:23:36 GMT
Repository: incubator-carbondata
Updated Branches:
  refs/heads/master 37dc0fb6d -> 28190eb71

Add website link in readme

Add website link:


Branch: refs/heads/master
Commit: 9e17448437fbd69c9eb91e07af515fda7983b049
Parents: 37dc0fb
Author: Liang Chen <>
Authored: Mon Dec 26 21:13:06 2016 +0800
Committer: GitHub <>
Committed: Mon Dec 26 21:13:06 2016 +0800

---------------------------------------------------------------------- | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)
diff --git a/ b/
index f3e5e8a..3db6fdf 100644
--- a/
+++ b/
@@ -24,13 +24,15 @@ interactive query using advanced columnar storage, index, compression
 and encoding techniques to improve computing efficiency, in turn it will 
 help speedup queries an order of magnitude faster over PetaBytes of data. 
-You can find the latest CarbonData document and learn more at [CarbonData cwiki](
+You can find the latest CarbonData document and learn more at:
+[CarbonData cwiki](
 ### Features
 CarbonData file format is a columnar store in HDFS, it has many features that a modern columnar
format has, such as splittable, compression schema ,complex data type etc, and CarbonData
has following unique features:
 * Stores data along with index: it can significantly accelerate query performance and reduces
the I/O scans and CPU resources, where there are filters in the query.  CarbonData index consists
of multiple level of indices, a processing framework can leverage this index to reduce the
task it needs to schedule and process, and it can also do skip scan in more finer grain unit
(called blocklet) in task side scanning instead of scanning the whole file. 
 * Operable encoded data :Through supporting efficient compression and global encoding schemes,
can query on compressed/encoded data, the data can be converted just before returning the
results to the users, which is "late materialized". 
-* Column group: Allow multiple columns to form a column group that would be stored as row
format. This reduces the row reconstruction cost at query time.
 * Supports for various use cases with one single Data format : like interactive OLAP-style
query, Sequential Access (big scan), Random Access (narrow scan). 
 ### Building CarbonData,using development tools and cluster deployment guide

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