Copilot commented on code in PR #68974:
URL: https://github.com/apache/airflow/pull/68974#discussion_r3473214464
##########
providers/databricks/src/airflow/providers/databricks/operators/databricks.py:
##########
@@ -876,6 +909,39 @@ def
_inject_openlineage_properties_into_databricks_job(self, json: dict, context
)
return json
+ def submit_job(self, context: Context) -> int:
+ normalised = self._prepare_submit_json(context)
+ # Set run_id the instant the run exists so on_kill can cancel it even
if the worker dies
+ # before polling begins.
+ self.run_id = self._hook.submit_run(normalised)
+ self.log.info("Run submitted with run_id: %s", self.run_id)
+ return self.run_id
+
+ def get_job_status(self, external_id: int, context: Context) -> str:
+ # Databricks splits run state across life_cycle_state and
result_state; the mixin's status
+ # interface is a single string, so encode both as "LIFE_CYCLE:RESULT"
and decode them in
+ # is_job_active / is_job_succeeded.
+ run_info = self._hook.get_run(external_id)
+ state = RunState(**run_info["state"])
+ return f"{state.life_cycle_state}:{state.result_state}"
+
+ def is_job_active(self, status: str) -> bool:
+ life_cycle_state = status.split(":", 1)[0]
+ return life_cycle_state not in ("TERMINATED", "SKIPPED",
"INTERNAL_ERROR")
+
+ def is_job_succeeded(self, status: str) -> bool:
+ return status == "TERMINATED:SUCCESS"
+
+ def poll_until_complete(self, external_id: int, context: Context) -> None:
+ self.run_id = external_id
+ # The run already exists here (fresh submit logged in submit_job, or
reconnect logged by the
+ # mixin), so the poll helper must not announce a submission.
+ _handle_databricks_operator_execution(self, self._hook, self.log,
context, announce_submission=False)
+
+ def get_job_result(self, external_id: int, context: Context) -> None:
+ self.run_id = external_id
+ return None
Review Comment:
In the durable "already succeeded" retry path,
`ResumableJobMixin.execute_resumable()` calls `get_job_result()` directly and
skips `poll_until_complete()`. Since XCom push of `run_id` / `run_page_url`
currently only happens in `_handle_databricks_operator_execution()` (called
from `poll_until_complete()`), retries that short-circuit as already-succeeded
will not push these XCom keys even when `do_xcom_push=True`.
That’s a behavior change vs the normal synchronous path and can break
downstream tasks that rely on `run_id` / `run_page_url` being present. Consider
pushing these XCom values from `get_job_result()` as well (it’s the hook point
the mixin uses for the already-succeeded case).
##########
providers/databricks/tests/unit/databricks/operators/test_databricks.py:
##########
@@ -1651,6 +1668,161 @@ def
test_inject_parent_job_info_preserves_existing_config(self, db_mock_class, m
assert
submitted["new_cluster"]["spark_conf"]["spark.openlineage.parentJobNamespace"]
== "ns"
[email protected](
+ not AIRFLOW_V_3_3_PLUS, reason="task_state_store (durable execution)
requires Airflow 3.3+"
+)
+class TestDatabricksSubmitRunOperatorDurable:
+ @staticmethod
+ def _context(task_store=None):
+ ctx: dict = {"ti": MagicMock(autospec=True)}
+ if task_store is not None:
+ ctx["task_state_store"] = task_store
+ return ctx
+
+ @staticmethod
+ def _state(lifecycle: str, result: str = ""):
+ return {"state": {"life_cycle_state": lifecycle, "result_state":
result, "state_message": ""}}
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_persists_run_id_to_task_state_store_on_fresh_submit(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.submit_run.return_value = RUN_ID
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
+ task_store.get.return_value = None
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_called_once()
+ task_store.set.assert_called_once_with("databricks_run_id", RUN_ID)
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_reconnects_to_active_run_without_resubmitting(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ # status check sees the stored run still RUNNING, the poll then sees
it finish.
+ db_mock.get_run.side_effect = [self._state("RUNNING"),
self._state("TERMINATED", "SUCCESS")]
+ task_store = MagicMock()
+ task_store.get.return_value = RUN_ID
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_not_called()
+ task_store.set.assert_not_called()
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_skips_polling_when_stored_run_already_succeeded(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
+ task_store.get.return_value = RUN_ID
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_not_called()
+ db_mock.get_run_page_url.assert_not_called()
+ assert op.run_id == RUN_ID
Review Comment:
If the durable retry short-circuits because the stored run already
succeeded, the operator should still behave like a successful execution from
the caller’s perspective (notably: push `run_id` / `run_page_url` XComs when
`do_xcom_push=True`). This test currently asserts `get_run_page_url` is *not*
called, which would codify the missing-XCom behavior.
After adjusting the operator to push XComs from `get_job_result()` (for the
already-succeeded path), update this test to assert the URL is fetched and the
XCom pushes happen.
##########
providers/databricks/tests/unit/databricks/operators/test_databricks.py:
##########
@@ -1651,6 +1668,161 @@ def
test_inject_parent_job_info_preserves_existing_config(self, db_mock_class, m
assert
submitted["new_cluster"]["spark_conf"]["spark.openlineage.parentJobNamespace"]
== "ns"
[email protected](
+ not AIRFLOW_V_3_3_PLUS, reason="task_state_store (durable execution)
requires Airflow 3.3+"
+)
+class TestDatabricksSubmitRunOperatorDurable:
+ @staticmethod
+ def _context(task_store=None):
+ ctx: dict = {"ti": MagicMock(autospec=True)}
+ if task_store is not None:
+ ctx["task_state_store"] = task_store
+ return ctx
Review Comment:
`MagicMock(autospec=True)` here does not actually apply autospeccing
("autospec" is a `mock.patch` feature, not a `MagicMock` ctor arg), so this
ends up as an unspecced mock with an unused attribute. Prefer mocks with an
explicit `spec`/`spec_set` so the test will fail if the production code calls a
non-existent method.
Also, `ResumableJobMixin` reads `ti.stats_tags`; initializing it to `{}`
avoids accidental truthy `MagicMock` values affecting metric tag selection.
##########
providers/databricks/tests/unit/databricks/operators/test_databricks.py:
##########
@@ -1651,6 +1668,161 @@ def
test_inject_parent_job_info_preserves_existing_config(self, db_mock_class, m
assert
submitted["new_cluster"]["spark_conf"]["spark.openlineage.parentJobNamespace"]
== "ns"
[email protected](
+ not AIRFLOW_V_3_3_PLUS, reason="task_state_store (durable execution)
requires Airflow 3.3+"
+)
+class TestDatabricksSubmitRunOperatorDurable:
+ @staticmethod
+ def _context(task_store=None):
+ ctx: dict = {"ti": MagicMock(autospec=True)}
+ if task_store is not None:
+ ctx["task_state_store"] = task_store
+ return ctx
+
+ @staticmethod
+ def _state(lifecycle: str, result: str = ""):
+ return {"state": {"life_cycle_state": lifecycle, "result_state":
result, "state_message": ""}}
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_persists_run_id_to_task_state_store_on_fresh_submit(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.submit_run.return_value = RUN_ID
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
+ task_store.get.return_value = None
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_called_once()
+ task_store.set.assert_called_once_with("databricks_run_id", RUN_ID)
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_reconnects_to_active_run_without_resubmitting(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ # status check sees the stored run still RUNNING, the poll then sees
it finish.
+ db_mock.get_run.side_effect = [self._state("RUNNING"),
self._state("TERMINATED", "SUCCESS")]
+ task_store = MagicMock()
+ task_store.get.return_value = RUN_ID
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_not_called()
+ task_store.set.assert_not_called()
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_skips_polling_when_stored_run_already_succeeded(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
+ task_store.get.return_value = RUN_ID
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_not_called()
+ db_mock.get_run_page_url.assert_not_called()
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_resubmits_when_stored_run_in_terminal_failure(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.submit_run.return_value = RUN_ID
+ # stored run failed, after fresh resubmit the poll sees success.
+ db_mock.get_run.side_effect = [
+ self._state("TERMINATED", "FAILED"),
+ self._state("TERMINATED", "SUCCESS"),
+ ]
+ task_store = MagicMock()
Review Comment:
`task_store = MagicMock()` is unspecced; using `spec_set` makes this test
more robust against accidental API drift/typos.
##########
providers/databricks/tests/unit/databricks/operators/test_databricks.py:
##########
@@ -1651,6 +1668,161 @@ def
test_inject_parent_job_info_preserves_existing_config(self, db_mock_class, m
assert
submitted["new_cluster"]["spark_conf"]["spark.openlineage.parentJobNamespace"]
== "ns"
[email protected](
+ not AIRFLOW_V_3_3_PLUS, reason="task_state_store (durable execution)
requires Airflow 3.3+"
+)
+class TestDatabricksSubmitRunOperatorDurable:
+ @staticmethod
+ def _context(task_store=None):
+ ctx: dict = {"ti": MagicMock(autospec=True)}
+ if task_store is not None:
+ ctx["task_state_store"] = task_store
+ return ctx
+
+ @staticmethod
+ def _state(lifecycle: str, result: str = ""):
+ return {"state": {"life_cycle_state": lifecycle, "result_state":
result, "state_message": ""}}
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_persists_run_id_to_task_state_store_on_fresh_submit(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.submit_run.return_value = RUN_ID
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
+ task_store.get.return_value = None
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_called_once()
+ task_store.set.assert_called_once_with("databricks_run_id", RUN_ID)
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_reconnects_to_active_run_without_resubmitting(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ # status check sees the stored run still RUNNING, the poll then sees
it finish.
+ db_mock.get_run.side_effect = [self._state("RUNNING"),
self._state("TERMINATED", "SUCCESS")]
+ task_store = MagicMock()
+ task_store.get.return_value = RUN_ID
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_not_called()
+ task_store.set.assert_not_called()
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_skips_polling_when_stored_run_already_succeeded(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
+ task_store.get.return_value = RUN_ID
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_not_called()
+ db_mock.get_run_page_url.assert_not_called()
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_resubmits_when_stored_run_in_terminal_failure(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.submit_run.return_value = RUN_ID
+ # stored run failed, after fresh resubmit the poll sees success.
+ db_mock.get_run.side_effect = [
+ self._state("TERMINATED", "FAILED"),
+ self._state("TERMINATED", "SUCCESS"),
+ ]
+ task_store = MagicMock()
+ task_store.get.return_value = 999
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_called_once()
+ task_store.set.assert_called_once_with("databricks_run_id", RUN_ID)
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_durable_false_never_touches_task_state_store(self, db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}, durable=False
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.submit_run.return_value = RUN_ID
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
Review Comment:
This `task_store` mock is unspecced; `spec_set=["get", "set"]` helps catch
accidental typos and keeps tests aligned with the task state store API.
##########
providers/databricks/tests/unit/databricks/operators/test_databricks.py:
##########
@@ -1651,6 +1668,161 @@ def
test_inject_parent_job_info_preserves_existing_config(self, db_mock_class, m
assert
submitted["new_cluster"]["spark_conf"]["spark.openlineage.parentJobNamespace"]
== "ns"
[email protected](
+ not AIRFLOW_V_3_3_PLUS, reason="task_state_store (durable execution)
requires Airflow 3.3+"
+)
+class TestDatabricksSubmitRunOperatorDurable:
+ @staticmethod
+ def _context(task_store=None):
+ ctx: dict = {"ti": MagicMock(autospec=True)}
+ if task_store is not None:
+ ctx["task_state_store"] = task_store
+ return ctx
+
+ @staticmethod
+ def _state(lifecycle: str, result: str = ""):
+ return {"state": {"life_cycle_state": lifecycle, "result_state":
result, "state_message": ""}}
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_persists_run_id_to_task_state_store_on_fresh_submit(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.submit_run.return_value = RUN_ID
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
+ task_store.get.return_value = None
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_called_once()
+ task_store.set.assert_called_once_with("databricks_run_id", RUN_ID)
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_reconnects_to_active_run_without_resubmitting(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ # status check sees the stored run still RUNNING, the poll then sees
it finish.
+ db_mock.get_run.side_effect = [self._state("RUNNING"),
self._state("TERMINATED", "SUCCESS")]
+ task_store = MagicMock()
+ task_store.get.return_value = RUN_ID
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_not_called()
+ task_store.set.assert_not_called()
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_skips_polling_when_stored_run_already_succeeded(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
Review Comment:
`task_store` is created as a bare `MagicMock()` here. Consider
`spec_set=["get", "set"]` so the test enforces the expected task state store
API surface.
##########
providers/databricks/tests/unit/databricks/operators/test_databricks.py:
##########
@@ -1651,6 +1668,161 @@ def
test_inject_parent_job_info_preserves_existing_config(self, db_mock_class, m
assert
submitted["new_cluster"]["spark_conf"]["spark.openlineage.parentJobNamespace"]
== "ns"
[email protected](
+ not AIRFLOW_V_3_3_PLUS, reason="task_state_store (durable execution)
requires Airflow 3.3+"
+)
+class TestDatabricksSubmitRunOperatorDurable:
+ @staticmethod
+ def _context(task_store=None):
+ ctx: dict = {"ti": MagicMock(autospec=True)}
+ if task_store is not None:
+ ctx["task_state_store"] = task_store
+ return ctx
+
+ @staticmethod
+ def _state(lifecycle: str, result: str = ""):
+ return {"state": {"life_cycle_state": lifecycle, "result_state":
result, "state_message": ""}}
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_persists_run_id_to_task_state_store_on_fresh_submit(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.submit_run.return_value = RUN_ID
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
Review Comment:
`task_store` is a `MagicMock()` without a `spec`/`spec_set`, which can hide
typos in the code under test (e.g. calling `tas_store.get`). Prefer a specced
mock for the task state store interface.
##########
providers/databricks/tests/unit/databricks/operators/test_databricks.py:
##########
@@ -1651,6 +1668,161 @@ def
test_inject_parent_job_info_preserves_existing_config(self, db_mock_class, m
assert
submitted["new_cluster"]["spark_conf"]["spark.openlineage.parentJobNamespace"]
== "ns"
[email protected](
+ not AIRFLOW_V_3_3_PLUS, reason="task_state_store (durable execution)
requires Airflow 3.3+"
+)
+class TestDatabricksSubmitRunOperatorDurable:
+ @staticmethod
+ def _context(task_store=None):
+ ctx: dict = {"ti": MagicMock(autospec=True)}
+ if task_store is not None:
+ ctx["task_state_store"] = task_store
+ return ctx
+
+ @staticmethod
+ def _state(lifecycle: str, result: str = ""):
+ return {"state": {"life_cycle_state": lifecycle, "result_state":
result, "state_message": ""}}
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_persists_run_id_to_task_state_store_on_fresh_submit(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ db_mock.submit_run.return_value = RUN_ID
+ db_mock.get_run = make_run_with_state_mock("TERMINATED", "SUCCESS")
+ task_store = MagicMock()
+ task_store.get.return_value = None
+
+ op.execute(self._context(task_store))
+
+ db_mock.submit_run.assert_called_once()
+ task_store.set.assert_called_once_with("databricks_run_id", RUN_ID)
+ assert op.run_id == RUN_ID
+
+
@mock.patch("airflow.providers.databricks.operators.databricks.DatabricksHook")
+ def test_reconnects_to_active_run_without_resubmitting(self,
db_mock_class):
+ op = DatabricksSubmitRunOperator(
+ task_id=TASK_ID, json={"new_cluster": NEW_CLUSTER,
"notebook_task": NOTEBOOK_TASK}
+ )
+ db_mock = db_mock_class.return_value
+ # status check sees the stored run still RUNNING, the poll then sees
it finish.
+ db_mock.get_run.side_effect = [self._state("RUNNING"),
self._state("TERMINATED", "SUCCESS")]
+ task_store = MagicMock()
Review Comment:
`task_store` is an unspecced `MagicMock()`. Using `spec_set` helps ensure
the test fails if the production code calls an unexpected method on the task
state store.
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