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https://issues.apache.org/jira/browse/SPARK-60964?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-60964.
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Resolution: Fixed
Issue resolved by pull request 201
[https://github.com/apache/spark-connect-rust/pull/201]
> Retry each reattach, and release executions that fail at once, in Spark
> Connect Rust as PySpark does
> ----------------------------------------------------------------------------------------------------
>
> Key: SPARK-60964
> URL: https://issues.apache.org/jira/browse/SPARK-60964
> Project: Spark
> Issue Type: Bug
> Components: Connect
> Affects Versions: connect-rust-4.3.0
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Priority: Major
> Labels: pull-request-available
> Fix For: connect-rust-4.3.0
>
>
> PySpark Connect retries each reattach of an execution with a retry policy of
> its own ({{_has_next()}} makes a new {{Retrying}}), and releases an execution
> whose first {{ExecutePlan}} call fails. The Rust client differs:
> * It keeps one retry state for the whole stream: its attempts are never reset
> and its elapsed-time limit counts from the start of the stream. A query, a
> statement or the streaming listener that runs longer than the limit cannot
> retry a transient {{UNAVAILABLE}} of a later reattach, so the call fails and
> the execution is released.
> * An error of the first {{ExecutePlan}} call, as an analysis or parse error
> is, returns before the reattachable stream exists, so no {{ReleaseExecute}}
> is sent, and the server keeps the execution until its detached timeout.
> Retry each reattach, and release an execution that fails at once, as PySpark
> does.
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