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https://issues.apache.org/jira/browse/CARBONDATA-48?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15368978#comment-15368978
 ] 

ASF GitHub Bot commented on CARBONDATA-48:
------------------------------------------

GitHub user ravipesala opened a pull request:

    https://github.com/apache/incubator-carbondata/pull/33

    [CARBONDATA-48] Supported spark sql cli in carbon.

    For more details https://issues.apache.org/jira/browse/CARBONDATA-48

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/ravipesala/incubator-carbondata sqlcli

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/incubator-carbondata/pull/33.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #33
    
----
commit 47bc3ce2b01974f7e2e82785521ada1dc223e8ab
Author: ravipesala <[email protected]>
Date:   2016-07-09T06:46:21Z

    Added spark sql cli in carbon.

----


> Support Carbon sql cli to enhance user experiance
> -------------------------------------------------
>
>                 Key: CARBONDATA-48
>                 URL: https://issues.apache.org/jira/browse/CARBONDATA-48
>             Project: CarbonData
>          Issue Type: New Feature
>            Reporter: Ravindra Pesala
>
> Support SQL cli to enhance user experience.  User can directly run the 
> carbon-spark-sql and input the sql queries. These queries will run on 
> CarbonContext and shows the output.
> Example:
> {code}
> carbondata/bin$ ./carbon-spark-sql
> spark-sql> CREATE TABLE test_table (country String, name String, phonetype 
> String, serialname String, salary Int) STORED BY 
> 'org.apache.carbondata.format';
> INFO  09-07 12:27:31,388 - Time taken: 1.729 seconds
> spark-sql> LOAD DATA INPATH 
> '/home/root1/carbon/carbondata/examples/src/main/resources/data.csv' into 
> table test_table;
> INFO  09-07 12:29:01,598 - Time taken: 1.951 seconds
> spark-sql> select count(*) from test_table;
> 1000
> INFO  09-07 12:29:56,313 - Time taken: 0.82 seconds, Fetched 1 row(s)
> {code}



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