[jira] [Assigned] (HIVE-15933) Improve plans for correlated subquery with join and predicate

["Vineet Garg (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HIVE-15933?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Vineet Garg reassigned HIVE-15933:
----------------------------------


> Improve plans for correlated subquery with join and predicate
> -------------------------------------------------------------
>
>                 Key: HIVE-15933
>                 URL: https://issues.apache.org/jira/browse/HIVE-15933
>             Project: Hive
>          Issue Type: Sub-task
>          Components: Query Planning
>            Reporter: Vineet Garg
>            Assignee: Vineet Garg
>
> This is a continuation of HIVE-15905
> for queries such as:
> {code:SQL}
> explain select  
>   cd_gender,
>   cd_marital_status,
>   cd_education_status,
>   count(*) cnt1,
>   cd_purchase_estimate,
>   count(*) cnt2,
>   cd_credit_rating,
>   count(*) cnt3,
>   cd_dep_count,
>   count(*) cnt4,
>   cd_dep_employed_count,
>   count(*) cnt5,
>   cd_dep_college_count,
>   count(*) cnt6
>  from
>   customer c,customer_address ca,customer_demographics
>  where
>   c.c_current_addr_sk = ca.ca_address_sk and
>   ca_county in ('Walker County','Richland County','Gaines County','Douglas County','Dona Ana County') and
>   cd_demo_sk = c.c_current_cdemo_sk and 
>   exists (select *
>           from store_sales,date_dim
>           where c.c_customer_sk = ss_customer_sk and
>                 ss_sold_date_sk = d_date_sk and
>                 d_year = 2002 and
>                 d_moy between 4 and 4+3)
>  group by cd_gender,
>           cd_marital_status,
>           cd_education_status,
>           cd_purchase_estimate,
>           cd_credit_rating,
>           cd_dep_count,
>           cd_dep_employed_count,
>           cd_dep_college_count
>  order by cd_gender,
>           cd_marital_status,
>           cd_education_status,
>           cd_purchase_estimate,
>           cd_credit_rating,
>           cd_dep_count,
>           cd_dep_employed_count,
>           cd_dep_college_count
> limit 100;
> {code}
> HIVE generates un-necessary joins to produce value for correlated columns.



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