[GitHub] [hudi] danny0405 commented on a diff in pull request #5392: [HUDI-3942] [RFC-50] Improve Timeline Server

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danny0405 commented on code in PR #5392:
URL: https://github.com/apache/hudi/pull/5392#discussion_r875426679


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rfc/rfc-50/rfc-50.md:
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+
+# RFC-50: Improve Timeline Server
+
+## Proposers
+- @yuzhaojing
+
+## Approvers
+ - @xushiyan
+ - @danny0405
+
+## Abstract
+
+Support client to obtain timeline from timeline server.
+
+## Background
+
+The core of HUDI is to maintain all the operations performed by the timeline on the table at different times. Every time you write and read, you need to obtain the information of the HUDI table through the timeline.
+At present, there are two ways to obtain the timeline of HUDI :
+- Create a MetaClient and get the complete timeline through MetaClient #getActiveTimeline, which will directly scan the HDFS directory of metadata
+- Get the timeline through FileSystemView#getTimeline. This timeline is the cache timeline obtained by requesting the Embedded timeline service. There is no need to repeatedly scan the HDFS directory of metadata, but this timeline only contains completed instants
+
+### Problem description
+
+- HUDI designs the Timeline service for processing and caching when accessing metadata , but currently does not converge all access to metadata to the Timeline service, such as the acquisition of a complete timeline.
+- When the number of tasks written increases, a large number of repeated access to metadata will lead to high HDFS NameNode requests, causing greater pressure and not easy to expand.
+
+### Spark and Flink write flow comparison diagram
+
+Since Hudi is designed based on the Spark micro-batch model, in the Spark write process, all operations on the timeline are completed on the driver side, and then distributed to the executor side to start the write operation.
+
+But for Flink , Write tasks are resident services due to their pure streaming model. There is also no highly reliable communication mechanism between the user-side JM and the TM in Flink, so the TM needs to obtain the latest instant by polling the timeline for writing.
+
+![](ComparisonDiagram.png)
+
+### Current
+
+![](CurrentDesign.png)
+
+The current design implementation has two main problems with the convergence timeline
+- Since the timeline of the task is pulled from the Embedded timeline service, the refresh mechanism of the Embedded timeline service itself will doesn't work
+- MetaClient and HoodieTable are decoupled. Obtain the timeline in MetaClient and then request the Embedded timeline service to obtain file-related information through the FileSystemViewManager in HoodieTable combined with the timeline. There are circular dependencies and problems in the case of using MetaClient alone without creating HoodieTable
+

Review Comment:
   > We can record the last instant of the last request in fs view, and sync if there is a change
   
   Actually the current code already cache a local timeline for each fs view instance, we can just use that timeline hash toe compare with the timeline hash from the client to decide whether the fs view is behind (the code already does so, see `RequestHandler#syncIfLocalViewBehind`)



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