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https://issues.apache.org/jira/browse/DRILL-8555?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18124870#comment-18124870
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ASF GitHub Bot commented on DRILL-8555:
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letian-jiang commented on PR #3086:
URL: https://github.com/apache/drill/pull/3086#issuecomment-6054786514

   Hi @cgivre, thanks again for your review! I’ve pushed updates addressing 
your feedback on parameterized planning and BIGINT literal round trips. When 
you have a chance, could you take another look? Please let me know if there’s 
anything else you’d like me to address. Thanks!




> Physical plan cache for parameterized SQL queries
> -------------------------------------------------
>
>                 Key: DRILL-8555
>                 URL: https://issues.apache.org/jira/browse/DRILL-8555
>             Project: Apache Drill
>          Issue Type: New Feature
>          Components: Query Planning & Optimization
>            Reporter: Letian Jiang
>            Priority: Major
>
> h2. Motivation
> Repeated queries that differ only in literals are a common workload, yet each 
> query currently requires full planning. This adds unnecessary latency and 
> wastes CPU time.
> h2. Brief Design
> Add a per-Drillbit, in-memory plan cache. Drill automatically parameterizes 
> eligible SQL queries and reuses a cached physical plan with the current 
> literal values, without changes to client queries.
> h2. Plan reuse safety
>  * *Engine:* matches the SQL template and checks relevant option changes, 
> plugin configuration changes, and whether base table versions still match.
>  * *Storage plugin:* explicitly opts in, provides a plan-compatible table 
> version, and is responsible for rebuilding its predicate-dependent scan work 
> from the rebound expressions.
> h2. Expected benefit
> Short, frequently executed queries such as HBase reads can benefit 
> substantially. Analytical queries with significant planning cost can benefit 
> as well.
> h2. Implementation status
> A working implementation is available, including HBase, Paimon and Iceberg 
> integrations. A pull request will follow.



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