kaori-seasons opened a new pull request, #25672:
URL: https://github.com/apache/flink/pull/25672

   ## What is the purpose of the change
   
   Hi, community. Currently, in the batch verification scenario of our 
algorithm data, we use pyflink and encounter low transmission efficiency caused 
by low performance of pickle4-based encoding. After research, we decided to 
adopt Apache fury, a serialization framework based on pickle5 encoding. The 
implementation of fury in python will define the transmission buffer size in 
the protocol for transmission to improve the performance of large data 
transmission.
   
   Related communications with fury community members can be found 
[here](https://github.com/apache/fury/issues/1919)
   
   ## Brief change log
   
   *(for example:)*
     - *The TaskInfo is stored in the blob store on job creation time as a 
persistent artifact*
     - *Deployments RPC transmits only the blob storage reference*
     - *TaskManagers retrieve the TaskInfo from the blob cache*
   
   
   ## Verifying this change
   
   Please make sure both new and modified tests in this PR follow [the 
conventions for tests defined in our code quality 
guide](https://flink.apache.org/how-to-contribute/code-style-and-quality-common/#7-testing).
   
   *(Please pick either of the following options)*
   
   This change is a trivial rework / code cleanup without any test coverage.
   
   *(or)*
   
   This change is already covered by existing tests, such as *(please describe 
tests)*.
   
   *(or)*
   
   This change added tests and can be verified as follows:
   
   *(example:)*
     - *Added integration tests for end-to-end deployment with large payloads 
(100MB)*
     - *Extended integration test for recovery after master (JobManager) 
failure*
     - *Added test that validates that TaskInfo is transferred only once across 
recoveries*
     - *Manually verified the change by running a 4 node cluster with 2 
JobManagers and 4 TaskManagers, a stateful streaming program, and killing one 
JobManager and two TaskManagers during the execution, verifying that recovery 
happens correctly.*
   
   ## Does this pull request potentially affect one of the following parts:
   
     - Dependencies (does it add or upgrade a dependency): (yes / no)
     - The public API, i.e., is any changed class annotated with 
`@Public(Evolving)`: (yes / no)
     - The serializers: (yes / no / don't know)
     - The runtime per-record code paths (performance sensitive): (yes / no / 
don't know)
     - Anything that affects deployment or recovery: JobManager (and its 
components), Checkpointing, Kubernetes/Yarn, ZooKeeper: (yes / no / don't know)
     - The S3 file system connector: (yes / no / don't know)
   
   ## Documentation
   
     - Does this pull request introduce a new feature? (yes / no)
     - If yes, how is the feature documented? (not applicable / docs / JavaDocs 
/ not documented)
   


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