cloud-fan opened a new pull request, #57747:
URL: https://github.com/apache/spark/pull/57747
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### What changes were proposed in this pull request?
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Spark Connect's protocol includes an operation ID for identifying an
`ExecutePlan` request, but
clients currently leave it unset unless callers explicitly provide one. This
PR makes operation
IDs available throughout the request lifecycle:
* Python and Scala clients generate an operation ID before sending every
`ExecutePlan` request.
* Python exposes it through `ExecutionInfo.operation_id` after successful
execution and
`SparkConnectException.operation_id` after failure.
* Scala clients continue exposing it in `ExecutePlanResponse` and can
retrieve it from failures
through `SparkConnectClient.getOperationId`.
* Python session hooks preserve the client-generated operation ID.
* The server publishes the ID through
`SparkContext.SPARK_CONNECT_OPERATION_ID_PROPERTY`.
No protocol change is required, and callers that explicitly provide an
operation ID retain the
existing behavior.
### Why are the changes needed?
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Successful requests can sometimes be correlated using the operation ID
returned by the server.
That is insufficient for failures before the first response, because the
caller never learns a
server-generated identifier.
Generating the identifier client-side provides a stable correlation key
before the RPC begins.
The server propagates the same ID using Spark's existing local-property
mechanism, making it
available to driver-side listeners and executor tasks. Applications and
observability integrations
can therefore correlate client failures, server logs, Spark jobs, and tasks
without depending on a
specific event system.
### Does this PR introduce _any_ user-facing change?
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Yes. Spark Connect clients now generate operation IDs by default. Python
users can access the ID
through execution information and exceptions; Scala users can access it
through responses and
exceptions. Server-side integrations can access it through the public Spark
local-property key.
### How was this patch tested?
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Added tests for generated operation IDs, Python session-hook preservation,
successful execution
metadata, exceptions, and server-side local-property propagation.
Ran:
* `build/sbt 'connect-client-jvm/testOnly
org.apache.spark.sql.connect.client.SparkConnectClientSuite'`
* `build/sbt 'connect/testOnly
org.apache.spark.sql.connect.service.SparkConnectServiceE2ESuite'`
The focused Python test command was also invoked, but the configured local
interpreter skipped the
Connect tests because pandas 2.2 or newer was unavailable.
### Was this patch authored or co-authored using generative AI tooling?
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Generated-by: OpenAI Codex (GPT-5)
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