Re: carbon data performance doubts

Posted by Swapnil Shinde on Jul 21, 2017; 10:09pm
URL: http://apache-carbondata-dev-mailing-list-archive.168.s1.nabble.com/carbon-data-performance-doubts-tp18438p18659.html

Thank you Jacky! Above encoding property makes sense. How would you handle
an INT column with high cardinality? as per my understanding, this column
will be considered as measure and only way to make it dimension is to
specify "dictionary_include" for that column.
Any reason why a column being a dimension or measure is tied with
dictionary encoding? Does it make sense to have column as dimension with no
encoding so indexes can be used for filter?

Thanks
Swapnil


On Fri, Jul 21, 2017 at 12:30 PM, Jacky Li <[hidden email]> wrote:

> Hi Swapnil,
>
> Dictionary is beneficial for aggregation query (carbon will leverage late
> decode optimization in sql optimizer), so you can use it for columns on
> which you frequently do group by. While it can improve query performance,
> but it also requires more memory and CPU while loading. Normally, you
> should consider to use dictionary only on low cardinality columns.
>
> In current apache master branch (and all history release before 1.2),
> carbon data’s default encoding strategy favor query performance over
> loading performance. By default,  all string data type by default is
> encoded as dictionary. But it creates some problems sometimes, for example,
> if there are high cardinality column in the table, loading may fail due to
> not enough memory in JVM. To avoid this, we have added DICTIONARY_EXCLUDE
> option so that user can disable this default behavior manually. So,
> DICTIONARY_EXCLUDE property is designed for String column only.
>
> And, if you have low cardinality integer column ( like some ID field), you
> can choose to encode it as dictionary by specifying DICTIONARY_INCLUDE, so
> group by on this integer column will be faster.
>
> All these are current behavior, and there was discussion to change this
> behavior and give more control to the user, in the coming release (1.2)
> The new proposed target behavior will be:
> 1. There will be a default encoding strategy for each data type. If user
> does not specify any encoding related property in CREATE TABLE, carbon will
> use the default encoding strategy for each column.
> 2. And there will be a ENCODING property through which user can override
> the system default strategy. For example, user can create table by:
>
> CREATE TABLE t1 (city_name STRING, city_id INT, population INT, area
> DOUBLE)
> TBLPROPERTIES (‘ENCODING’ = ‘city_name: dictionary, city_id: {dictionary,
> RLE}, population: delta’)
>
> This SQL means city_name is encoded using dictionary, city_id is encoded
> using dictionary then apply RLE encoding (for numeric value), population is
> encoded using delta encoding, and area is encoded using system default
> encoding for double data type.
>
> This change is still going on (CARBONDATA-1014, https://issues.apache.org/
> jira/browse/CARBONDATA-1014 <https://issues.apache.org/
> jira/browse/CARBONDATA-1014>), on apache/encoding_override branch. Once
> it is done and stable it will be merged into master.
>
> Please advise if you have any suggestions.
>
> Regards,
> Jacky
>
>
> > 在 2017年7月21日，上午12:12，Swapnil Shinde <[hidden email]> 写道：
> >
> > Ok. Just curious - Any reason not to support numeric columns with
> > dictionary_exclude? Wouldn't it be useful for numeric unique column which
> > should be dimension but avoid creating dictionary  (as it may not be
> > beneficial).
> >
> > Thanks
> > Swapnil
> >
> >
> > On Thu, Jul 20, 2017 at 4:20 AM, manishgupta88 <
> [hidden email]>
> > wrote:
> >
> >> No Dictionary_Exclude is supported only for String data type columns.
> >>
> >> Regards
> >> Manish Gupta
> >>
> >>
> >>
> >> --
> >> View this message in context: http://apache-carbondata-dev-
> >> mailing-list-archive.1130556.n5.nabble.com/carbon-data-
> performance-doubts-
> >> tp18438p18559.html
> >> Sent from the Apache CarbonData Dev Mailing List archive mailing list
> >> archive at Nabble.com.
> >>
>
>