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https://issues.apache.org/jira/browse/SPARK-29038?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16927229#comment-16927229
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Lantao Jin commented on SPARK-29038:
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[~angerszhuuu] By default, we use Parquet to storage the data of materialized
view, but it supports all storage formats Spark supported. We have implemented
most matching logic about filter, join and aggregate. But it cannot cover all
scenarios, like JoinBack, since Spark current doesn't support PK or dimensions
like other DBMS (oracle).
> 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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