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https://issues.apache.org/jira/browse/IGNITE-8732?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Vladimir Ozerov updated IGNITE-8732:
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    Issue Type: Improvement  (was: Bug)

> SQL: REPLICATED cache cannot be left-joined to PARTITIONED
> ----------------------------------------------------------
>
>                 Key: IGNITE-8732
>                 URL: https://issues.apache.org/jira/browse/IGNITE-8732
>             Project: Ignite
>          Issue Type: Improvement
>          Components: sql
>    Affects Versions: 2.5
>            Reporter: Vladimir Ozerov
>            Priority: Major
>              Labels: sql-engine
>
> *Steps to reproduce*
> # Run 
> {{org.apache.ignite.sqltests.ReplicatedSqlTest#testLeftJoinReplicatedPartitioned}}
> # Observe that we have 2x results on 2-node cluster
> *Root Cause*
> {{left LEFT JOIN right ON cond}} operation assumes full scan of of a left 
> expression. Currently we perform this scan on every node and then simply 
> merge results on reducer. Two nodes, two scans of {{REPLICATED}} cache, 2x 
> results.
> *Potential Solutions*
> We may consider several solutions. Deeper analysis is required to understand 
> which is the right one.
> # Perform deduplication on reducer - this most prospective and general 
> technique, described in more details below
> # Treat {{REPLICATED}} cache as {{PARTITIONED}}. Essentially, we just need to 
> pass proper backup filter. But what if {{REPLICATED}} cache spans more nodes 
> than {{PARTITIONED}}? We cannot rely on primary/backup in this case
> # Implement additional execution phase as follows: 
> {code}
> SELECT left.cols, right.cols FROM left INNER JOIN right ON cond;              
>             // Get "inner join" part
> UNION
> UNICAST SELECT left.cols, [NULL].cols FROM left WHERE left.id NOT IN ([ids 
> from the first phase]) // Get "outer join" part
> {code}
> *Reducer Deduplication*
> The idea is to get all data locally and then perform final deduplication. 
> This may incur high network overhead, because of lot of duplicated left parts 
> would be transferred. However, this could be optimized greatly with the 
> following techniques applied one after another
> # Semi-jions: {{left}} is {{joined}} on mapper node, but instead of sending 
> {{(left, right)}} relation, we send {{(left) + (right)}}
> # In case {{left}} part is known to be idempotent (i.e. it produces the same 
> result set on all nodes), only one node will send {{(left) + (right)}}, other 
> nodes will send {{(right)}} only
> # Merge {{left}} results with if needed (i.e. if idempotence-related opto was 
> not applicable)
> # Join {{left}} and {{right}} parts on reducer



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