[GitHub] [hudi] yuzhaojing commented on a diff in pull request #4309: [HUDI-3016][RFC-43] Proposal to implement Compaction/Clustering Servi…

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yuzhaojing commented on code in PR #4309:
URL: https://github.com/apache/hudi/pull/4309#discussion_r859291367


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rfc/rfc-43/rfc-43.md:
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+
+# RFC-43: Implement Table Management Service for Hudi
+
+## Proposers
+
+- @yuzhaojing
+
+## Approvers
+
+- @vinothchandar
+- @Raymond
+
+## Status
+
+JIRA: [https://issues.apache.org/jira/browse/HUDI-3016](https://issues.apache.org/jira/browse/HUDI-3016)
+
+## Abstract
+
+Hudi table needs table management operations. Currently, schedule these job provides Three ways:
+
+- Inline, execute these job and writing job in the same application, perform the these job and writing job serially.
+
+- Async, execute these job and writing job in the same application, Async parallel execution of these job and write job.
+
+- Independent compaction/clustering job, execute an async compaction/clustering job of another application.
+
+With the increase in the number of HUDI tables, due to a lack of management capabilities, maintenance costs will become
+higher. This proposal is to implement an independent compaction/clustering Service to manage the Hudi
+compaction/clustering job.
+
+## Background
+
+In the current implementation, if the HUDI table needs do compact/cluster, it only has three ways:
+
+1. Use inline compaction/clustering, in this mode the job will be block writing job.
+
+2. Using Async compaction/clustering, in this mode the job execute async but also sharing the resource with HUDI to
+   write a job that may affect the stability of job writing, which is not what the user wants to see.
+
+3. Using independent compaction/clustering job is a better way to schedule the job, in this mode the job execute async
+   and do not sharing resources with writing job, but also has some questions:
+    1. Users have to enable lock service providers so that there is not data loss. Especially when compaction/clustering

Review Comment:
   Yes, because we prefer that the execution plan can be scheduled by the service later, but in phase1, the execution plan is still scheduled by the client to reduce the service pressure. After implementing multi-instance in phase2, the configuration will be provided to decide who schedules the execution plan.



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