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

• Yes: claude sonnet 4.6

Why

ResumableJobMixin had no standard on/off switch for crash recovery. When SparkSubmitOperator was
ported to resumability, I added a reconnect_on_retry parameter, but any future resumable operator
would need to invent their own name — making the flag inconsistent across operators and impossible to
measure uniformly.

What changed

• ResumableJobMixin now owns durable: bool = True in its own __init__, decorated with
  @BaseOperatorMeta._apply_defaults. Operators that inherit (ResumableJobMixin, BaseOperator) get
  the flag for free — no redeclaration needed, default_args injection and .partial() work
  automatically.
• When False, execute_resumable() skips all task_state_store interaction and runs a plain
  submit/poll/result cycle.
• SparkSubmitOperator.reconnect_on_retry is renamed to durable. The per-mode if/else branching in
  execute() is removed and all three tracking paths (standalone, K8s, YARN) now call
  execute_resumable(context) directly.
• reconnect_on_retry is kept as a deprecated alias for backcompat with 6.1.0 — passing it raises an
  AirflowProviderDeprecationWarning and maps to durable.

Impact on operators using resumability

No behavior change. durable defaults to True, so crash recovery is on by default exactly as before.

How to opt out

Set durable=False on the task:

SparkSubmitOperator(
    task_id="my_spark_job",
    application="my_app.jar",
    durable=False,
)

Or via default_args to disable for all tasks in a DAG:

with DAG("my_dag", default_args={"durable": False}):

Implementation note

ResumableJobMixin.__init__ is decorated directly with @BaseOperatorMeta._apply_defaults. When
super().__init__(**kwargs) reaches the mixin, apply_defaults fires, sees durable in the
signature, and injects it from default_args if not explicitly set. Operators just need
(ResumableJobMixin, BaseOperator) ordering and super().__init__(**kwargs).

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