def test_counter():
@traced
async def foo():
pass
@traced
async def bar():
pass
async def call_foo(num):
await asyncio.gather(*[foo() for _ in range(num)])
async def call_bar(num):
await asyncio.gather(*[bar() for _ in range(num)])
async def run():
await call_foo(10)
await call_foo(10)
await call_bar(10)
traced_counter.set(Counter())
loop = asyncio.get_event_loop()
loop.run_until_complete(run())
counter = traced_counter.get()
assert isinstance(counter, Counter)
counts = counter.counts()
assert counts["foo"] == 20
assert counts["bar"] == 10
def test_asset_batching():
with instance_for_test() as instance:
repo = get_asset_repo()
foo_job = repo.get_job("foo_job")
for _ in range(3):
foo_job.execute_in_process(instance=instance)
with define_out_of_process_context(__file__, "asset_repo",
instance) as context:
traced_counter.set(Counter())
result = execute_dagster_graphql(
context,
ASSET_RUNS_QUERY,
variables={"assetKey": {
"path": ["foo"]
}})
assert result.data
assert "assetOrError" in result.data
assert "assetMaterializations" in result.data["assetOrError"]
materializations = result.data["assetOrError"][
"assetMaterializations"]
assert len(materializations) == 3
counter = traced_counter.get()
counts = counter.counts()
assert counts
assert counts.get("DagsterInstance.get_run_records") == 1
def test_repository_batching(graphql_context):
instance = graphql_context.instance
if not instance.supports_batch_tick_queries or not instance.supports_bucket_queries:
pytest.skip("storage cannot batch fetch")
traced_counter.set(Counter())
selector = infer_repository_selector(graphql_context)
result = execute_dagster_graphql(
graphql_context,
REPOSITORY_SENSORS_QUERY,
variables={"repositorySelector": selector},
)
assert result.data
assert "repositoryOrError" in result.data
assert "sensors" in result.data["repositoryOrError"]
counter = traced_counter.get()
counts = counter.counts()
assert counts
assert len(counts) == 3
# We should have a single batch call to fetch run records (to fetch sensor runs) and a single
# batch call to fetch instigator state, instead of separate calls for each sensor (~5 distinct
# sensors in the repo)
# 1) `get_run_records` is fetched to instantiate GrapheneRun
# 2) `all_instigator_state` is fetched to instantiate GrapheneSensor
assert counts.get("DagsterInstance.get_run_records") == 1
assert counts.get("DagsterInstance.all_instigator_state") == 1
assert counts.get("DagsterInstance.get_batch_ticks") == 1
def test_repository_batching():
with instance_for_test() as instance:
repo = get_repo_at_time_1()
foo_pipeline = repo.get_pipeline("foo_pipeline")
evolving_pipeline = repo.get_pipeline("evolving_pipeline")
foo_run_ids = [execute_pipeline(foo_pipeline, instance=instance).run_id for i in range(3)]
evolving_run_ids = [
execute_pipeline(evolving_pipeline, instance=instance).run_id for i in range(2)
]
with define_out_of_process_context(__file__, "get_repo_at_time_1", instance) as context:
traced_counter.set(Counter())
result = execute_dagster_graphql(
context,
REPOSITORY_RUNS_QUERY,
variables={"repositorySelector": infer_repository_selector(context)},
)
assert result.data
assert "repositoryOrError" in result.data
assert "pipelines" in result.data["repositoryOrError"]
pipelines = result.data["repositoryOrError"]["pipelines"]
assert len(pipelines) == 2
pipeline_runs = {pipeline["name"]: pipeline["runs"] for pipeline in pipelines}
assert len(pipeline_runs["foo_pipeline"]) == 3
assert len(pipeline_runs["evolving_pipeline"]) == 2
assert set(foo_run_ids) == set(run["runId"] for run in pipeline_runs["foo_pipeline"])
assert set(evolving_run_ids) == set(
run["runId"] for run in pipeline_runs["evolving_pipeline"]
)
counter = traced_counter.get()
counts = counter.counts()
assert counts
assert len(counts) == 1
# We should have a single batch call to fetch run records, instead of 3 separate calls
# to fetch run records (which is fetched to instantiate GrapheneRun)
assert counts.get("DagsterInstance.get_run_records") == 1
def send_wrapper(message: Message):
if message["type"] == "http.response.start":
counter = traced_counter.get()
if counter and isinstance(counter, Counter):
headers = MutableHeaders(scope=message)
headers.append("x-dagster-call-counts", json.dumps(counter.counts()))
return send(message)
def test_repository_batching(graphql_context):
traced_counter.set(Counter())
selector = infer_repository_selector(graphql_context)
result = execute_dagster_graphql(
graphql_context,
REPOSITORY_SCHEDULES_QUERY,
variables={"repositorySelector": selector},
)
assert result.data
assert "repositoryOrError" in result.data
assert "schedules" in result.data["repositoryOrError"]
counter = traced_counter.get()
counts = counter.counts()
assert counts
assert len(counts) == 2
# We should have a single batch call to fetch run records (to fetch schedule runs) and a single
# batch call to fetch instigator state, instead of separate calls for each schedule (~18
# distinct schedules in the repo)
# 1) `get_run_records` is fetched to instantiate GrapheneRun
# 2) `all_instigator_state` is fetched to instantiate GrapheneSchedule
assert counts.get("DagsterInstance.get_run_records") == 1
assert counts.get("DagsterInstance.all_instigator_state") == 1
def return_counts(response):
counter = traced_counter.get()
if counter and isinstance(counter, Counter):
response.headers["x-dagster-call-counts"] = json.dumps(
counter.counts())
return response