http://apache-carbondata-dev-mailing-list-archive.168.s1.nabble.com/Re-carbondata-test-join-question-tp4447p4459.html
yes. suggest to move to the first or second.
the basic principle is, should from left to right with cardinality increasing,
at the same time, if it is a commonly used filter field, u should make it dimension and put left .
> hi, geda
> can u share ur create ddl?
> some suggestion: for that filter field (like id), u can try to put in
> left column and use dictionary_include or exclude to make it dimension. if
> cardinality more than 100 thousand, u can try to make it no dictionary.
> as for ur question, if all the dimensions make no dictionary, there will
> be no decode part.
>
>
> thanks
> Jay
>
>
>
>
>
> ------------------ Original ------------------
> From: "geda";<[hidden email]
> <
http:///user/SendEmail.jtp?type=node&node=4442&i=0>>;
> Date: Wed, Dec 14, 2016 11:10 PM
> To: "dev"<[hidden email]
> <
http:///user/SendEmail.jtp?type=node&node=4442&i=1>>;
>
> Subject: carbondata test join question
>
>
>
> hello
> i want to test orc ,carbon , which is faster
> test on yarn with 8 executors, each executor 4G,each 2 core
> spark1.6 ,carbon2.0
> sql : join 3 table
> A :300W row,5GB
> B:13W row,30MB
> C:7W row,10MB
> like this:
> select b.id ,b.d_name ,a.v_no,count(*) o_count from a left join b on
> a.d_id=b.id left join c on c.v_no=a.v_no where
> date(a.create_time)>=
> '2016-07-01' and date(a.create_time)<= '2016-09-02' group by b.id ,
> b.d_name, a.v_no having o_count> 30 order by b.id desc
> use context
> cc.sql($SQL).show() : carbondata :run 5times avg time :7.3s
> hiveContext.sql($SQL).show() : ORC : run 5times avg time:5.3s
> i find from DAG ,carbon has a more job ,do carbon decode ,finish this job
> cause 2-3s spend
> if strip this job ,carbon and orc use time more or less the same
> i want to know how to strip the last stage or how to tune sql like this
> .Thanks
> <
http://apache-carbondata-mailing-list-archive.1130556.
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