[GitHub] [hudi] yuzhaojing commented on a diff in pull request #4309: [HUDI-3016][RFC-43] Proposal to implement Table Management Service

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yuzhaojing commented on code in PR #4309:
URL: https://github.com/apache/hudi/pull/4309#discussion_r964884802


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rfc/rfc-43/rfc-43.md:
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+
+# RFC-43: Implement Table Management ServiceTable 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
+       is getting scheduled, no other writes should proceed concurrently and hence a lock is required.
+    2. The user needs to manually start an async compaction/clustering application, which means that the user needs to
+       maintain two jobs.
+    3. With the increase in the number of HUDI jobs, there is no unified service to manage compaction/clustering jobs (
+       monitor, retry, history, etc...), which will make maintenance costs increase.
+
+With this effort, we want to provide an independent compaction/clustering Service, it will have these abilities:
+
+- Provides a pluggable execution interface that can adapt to multiple execution engines, such as Spark and Flink.
+
+- With the ability to failover, need to be persisted compaction/clustering message.
+
+- Perfect metrics and reuse HoodieMetric expose to the outside.
+
+- Provide automatic failure retry for compaction/clustering job.
+

Review Comment:
   This is expected to provide pluggable interfaces to support various scheduling strategies.



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