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https://issues.apache.org/jira/browse/SPARK-59135?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ruifeng Zheng resolved SPARK-59135.
-----------------------------------
    Fix Version/s: 4.4.0
       Resolution: Fixed

Issue resolved by pull request 58435
[https://github.com/apache/spark/pull/58435]

> Spark Connect command streams fail on valid non-dictionary ExecutePlan 
> responses
> --------------------------------------------------------------------------------
>
>                 Key: SPARK-59135
>                 URL: https://issues.apache.org/jira/browse/SPARK-59135
>             Project: Spark
>          Issue Type: Bug
>          Components: Connect, PySpark
>    Affects Versions: 4.2.0
>            Reporter: Haoyan Geng
>            Assignee: Haoyan Geng
>            Priority: Major
>              Labels: pull-request-available
>             Fix For: 4.4.0
>
>
> ### Problem
> `SparkConnectClient.execute_command_as_iterator` assumes every decoded 
> `ExecutePlanResponse` item is a dictionary. However, the response decoder 
> legitimately produces other values, including `PlanMetrics`, 
> `PlanObservedMetrics`, schemas, Arrow batches, and protobuf extensions.
> Python Data Source workers currently register profiler accumulators even when 
> `spark.sql.pyspark.dataSource.profiler` is unset. Their empty accumulator 
> updates can therefore be returned as observed metrics alongside command 
> results. When this happens, `execute_command_as_iterator` raises 
> `UNKNOWN_RESPONSE` and terminates the command stream.
> ### Impact
> This affects PySpark Spark Connect clients. Known affected consumers are the 
> streaming-query listener bus and Declarative Pipelines event stream, so the 
> problem is not limited to streaming queries. Accumulators are currently 
> registered unconditionally.
> ### Expected behavior
> The low-level command iterator should preserve every valid decoded response. 
> Command-specific consumers should ignore recognized execution metadata while 
> continuing to reject malformed or unrelated responses. Python Data Source 
> workers should only create profiler accumulators when performance or memory 
> profiling is enabled. Ordinary accumulator updates must remain unaffected.
> ### Proposed change
> - Make `execute_command_as_iterator` yield every decoded response item.
> - Let streaming-listener and pipeline consumers ignore `PlanMetrics` and 
> `ObservedMetrics`.
> - Continue raising errors for unexpected command-specific responses.
> - Register Python Data Source profiler accumulators only for `perf` and 
> `memory` profiling modes.



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