TASK 13-14: pyflink users need geography schemas

[gkalashyan-akv]

What is the purpose of the change

(For example: This pull request makes task deployment go through the blob server, rather than through RPC. That way we avoid re-transferring them on each deployment (during recovery).)

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.

(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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Was generative AI tooling used to co-author this PR?

• Yes (please specify the tool below)

[talatuyarer]

I believe this PR is not working. It needs more careful work. There are four paths and also we can use the "everywhere BITMAP appears" as rule to add new type.

• from_elements (data in): Python pickles rows, then Java PythonTableUtils.converter() switches on the column's LogicalType to build a converter per field.
• collect() (data out): Java PythonBridgeUtils.getPickledBytesFromJavaObject() switches on the type to pickle each field. No Geography branch → the raw GeographyData object falls to the generic pickler, which can't handle it.
• UDFs: types cross to the Python worker via a proto enum (flink-fn-execution.proto TypeName) plus coders.py. zero GEOGRAPHY entries.
• pandas/Arrow: to_arrow_type in types.py and Java ArrowUtils — zero GEOGRAPHY entries.

[talatuyarer]

I believe this is not enough. adding a type to Flink means updating many parallel stacks what we did in Java. PyFlink has the same structure: types.py is only the declaration layer (Python class, Java↔Python DataType mapping). The data layers are separate: pickling between the Python driver and JVM, the UDF worker protocol, and Arrow for pandas.