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https://issues.apache.org/jira/browse/SPARK-29038?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16927243#comment-16927243
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angerszhu commented on SPARK-29038:
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I ma interested in the match about :
you create a MV table q1_mv with group by `l_returnflag, l_linestatus,
l_shipdate`,
your query group by `l_returnflag, l_linestatus` ,
This may be the most complex place need to be achieved.
I wanted to do this in my cache framework, but I couldn't find a good way to do
it.
Can i contact you with wechat.
> SPIP: Support Spark Materialized View
> -------------------------------------
>
> Key: SPARK-29038
> URL: https://issues.apache.org/jira/browse/SPARK-29038
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Lantao Jin
> Priority: Major
>
> Materialized view is an important approach in DBMS to cache data to
> accelerate queries. By creating a materialized view through SQL, the data
> that can be cached is very flexible, and needs to be configured arbitrarily
> according to specific usage scenarios. The Materialization Manager
> automatically updates the cache data according to changes in detail source
> tables, simplifying user work. When user submit query, Spark optimizer
> rewrites the execution plan based on the available materialized view to
> determine the optimal execution plan.
> Details in [design
> doc|https://docs.google.com/document/d/1q5pjSWoTNVc9zsAfbNzJ-guHyVwPsEroIEP8Cca179A/edit?usp=sharing]
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