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Posted to issues@spark.apache.org by "Marco Gaido (Jira)" <ji...@apache.org> on 2019/09/10 13:41:00 UTC
[jira] [Comment Edited] (SPARK-29038) SPIP: Support Spark
Materialized View
[ https://issues.apache.org/jira/browse/SPARK-29038?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16926650#comment-16926650 ]
Marco Gaido edited comment on SPARK-29038 at 9/10/19 1:40 PM:
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[~cltlfcjin] currently spark has a something similar, which is query caching, where the user can also select the level of caching performed. My understanding is that your proposal is to do something very similar, just with a different syntax, more DB oriented. Is my understanding correct?
was (Author: mgaido):
[~cltlfcjin] currently spark has a something similar, which is query caching, where the user can also select the level of caching performed. My undersatanding is that your proposal is to do something very similar, just with a different syntax, more DB oriented. Is my understanding correct?
> 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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