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https://issues.apache.org/jira/browse/HIVE-5945?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Navis updated HIVE-5945:
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Attachment: HIVE-5945.4.patch.txt
> ql.plan.ConditionalResolverCommonJoin.resolveMapJoinTask also sums those
> tables which are not used in the child of this conditional task.
> -----------------------------------------------------------------------------------------------------------------------------------------
>
> Key: HIVE-5945
> URL: https://issues.apache.org/jira/browse/HIVE-5945
> Project: Hive
> Issue Type: Bug
> Components: Query Processor
> Affects Versions: 0.8.0, 0.9.0, 0.10.0, 0.11.0, 0.12.0, 0.13.0
> Reporter: Yin Huai
> Assignee: Navis
> Priority: Critical
> Attachments: HIVE-5945.1.patch.txt, HIVE-5945.2.patch.txt,
> HIVE-5945.3.patch.txt, HIVE-5945.4.patch.txt
>
>
> Here is an example
> {code}
> select
> i_item_id,
> s_state,
> avg(ss_quantity) agg1,
> avg(ss_list_price) agg2,
> avg(ss_coupon_amt) agg3,
> avg(ss_sales_price) agg4
> FROM store_sales
> JOIN date_dim on (store_sales.ss_sold_date_sk = date_dim.d_date_sk)
> JOIN item on (store_sales.ss_item_sk = item.i_item_sk)
> JOIN customer_demographics on (store_sales.ss_cdemo_sk =
> customer_demographics.cd_demo_sk)
> JOIN store on (store_sales.ss_store_sk = store.s_store_sk)
> where
> cd_gender = 'F' and
> cd_marital_status = 'U' and
> cd_education_status = 'Primary' and
> d_year = 2002 and
> s_state in ('GA','PA', 'LA', 'SC', 'MI', 'AL')
> group by
> i_item_id,
> s_state
> order by
> i_item_id,
> s_state
> limit 100;
> {\code}
> I turned off noconditionaltask. So, I expected that there will be 4 Map-only
> jobs for this query. However, I got 1 Map-only job (joining strore_sales and
> date_dim) and 3 MR job (for reduce joins.)
> So, I checked the conditional task determining the plan of the join involving
> item. In ql.plan.ConditionalResolverCommonJoin.resolveMapJoinTask,
> aliasToFileSizeMap contains all input tables used in this query and the
> intermediate table generated by joining store_sales and date_dim. So, when we
> sum the size of all small tables, the size of store_sales (which is around
> 45GB in my test) will be also counted.
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