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Only preload interactive algorithms for reader studies with budget #4741

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11 changes: 10 additions & 1 deletion app/grandchallenge/components/tasks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1307,9 +1307,17 @@ def delete_stale_provisioned_concurrency_configs(self):
@acks_late_micro_short_task
@transaction.atomic
def preload_interactive_algorithms():
from grandchallenge.reader_studies.models import Question
from grandchallenge.reader_studies.models import Question, ReaderStudy
from grandchallenge.workstations.models import Session

reader_studies_out_of_budget = [
rs.pk
for rs in ReaderStudy.objects.exclude(max_credits__isnull=True).only(
"pk", "max_credits"
)
if not rs.has_budget
]

Comment on lines +1313 to +1320
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@amickan amickan May 28, 2026

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This query has an N+1 problem (due to expensive queries in credits_consumed). It's an asynchronous task, but still. Currently looking at annotating credits_consumed in the DB to make this more efficient.

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@amickan amickan May 28, 2026

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Struggling with turning credits_consumed into an annotation. It involves nested aggregates, and gets quite complex. Maybe prefetching the related objects is good enough here? In general, I would like to know how bad the performance is before I continue trying to optimize this.

@jmsmkn could you compare timings for the following 2 queries:

import time
from grand_challenge.reader_studies.models import ReaderStudy


def query_without_prefetch():
    return [
        rs.pk
        for rs in ReaderStudy.objects.exclude(max_credits__isnull=True).only(
            "pk", "max_credits"
        )
        if not rs.has_budget
    ]


def query_with_prefetch():
    return [
        rs.pk
        for rs in ReaderStudy.objects.exclude(max_credits__isnull=True)
        .prefetch_related(
            "session_utilizations__reader_studies",
            "endpoint_utilizations__reader_studies",
        )
        .only("pk", "max_credits")
        if not rs.has_budget
    ]


def benchmark(label, func):
    start = time.perf_counter()
    result = func()
    end = time.perf_counter()

    return {
        "label": label,
        "time_seconds": end - start,
    }


def main():
    results = [
        benchmark("without_prefetch", query_without_prefetch),
        benchmark("with_prefetch", query_with_prefetch),
    ]

    for r in results:
        print(f"{r['label']}:")
        print(f"  time: {r['time_seconds']:.6f}s")


if __name__ == "__main__":
    main()

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@jmsmkn jmsmkn May 29, 2026

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without_prefetch:
  time: 0.294184s
with_prefetch:
  time: 0.203041s

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@amickan amickan May 29, 2026

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Thanks. Those timings seem fine to me for an asynchronous task and not worth the added complexity of moving the consumed credits into a DB annotation.

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@jmsmkn jmsmkn May 29, 2026

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Would still be worth including the prefetching if those objects are going to be used.

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@amickan amickan May 29, 2026

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Very true, I had that as a local commit, but forgot to push!

active_interactive_algorithms = (
Question.objects.filter(
reader_study__workstation_sessions__status__in=[
Expand All @@ -1318,6 +1326,7 @@ def preload_interactive_algorithms():
Session.RUNNING,
],
)
.exclude(reader_study__pk__in=reader_studies_out_of_budget)
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@jmsmkn jmsmkn May 29, 2026

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Is there a reason to use the negative here? Filtering is going to be more efficient than excluding.

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@amickan amickan May 29, 2026

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No. This seemed easier to read to me and I didn't know that filtering is more efficient than excluding. I'll change it to filter().

.exclude(interactive_algorithm="")
.values_list("interactive_algorithm", flat=True)
.distinct()
Expand Down
53 changes: 53 additions & 0 deletions app/tests/components_tests/test_tasks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -109,6 +109,7 @@
UserUploadFactory,
create_upload_from_file,
)
from tests.utilization_tests.factories import SessionUtilizationFactory


@pytest.mark.django_db
Expand Down Expand Up @@ -1322,6 +1323,58 @@ def test_preload_interactive_algorithms(settings):
assert mock_instance.consolidate.call_count == 1


@pytest.mark.django_db
def test_preload_interactive_algorithms_excludes_reader_studies_without_budget(
settings,
):
arn = f"arn:aws:lambda:eu-central-1:1234567890:function:org-proj-e-uls23-baseline-{uuid.uuid4()}"

settings.INTERACTIVE_ALGORITHMS_LAMBDA_FUNCTIONS = {
"io_bucket_name": "org-proj-e-some-bucket",
"lambda_functions": [
{
# Add a uuid to avoid cache key clashes in testing
"arn": arn,
"internal_name": "uls23-baseline",
"minimum_duration": 1,
"timeout": 60,
"version": "1",
}
],
}

rs_with_exhausted_credit = ReaderStudyFactory(max_credits=100)
session_utilization = SessionUtilizationFactory(
duration=timedelta(hours=1)
)
session_utilization.reader_studies.add(rs_with_exhausted_credit)

QuestionFactory(
reader_study=rs_with_exhausted_credit,
interactive_algorithm=InteractiveAlgorithmLambdaChoices.ULS23_BASELINE,
)

assert not rs_with_exhausted_credit.has_budget

with patch(
"grandchallenge.components.tasks.InteractiveAlgorithmLambda"
) as mock_interactive_algorithm:
mock_instance = mock_interactive_algorithm.return_value
mock_instance.consolidate.return_value = "mocked_consolidation_result"

assert preload_interactive_algorithms() == {
"uls23-baseline": "mocked_consolidation_result"
}

mock_interactive_algorithm.assert_any_call(
arn=arn,
qualifier="1",
should_be_active=False,
)

assert mock_instance.consolidate.call_count == 1


@pytest.mark.django_db
@pytest.mark.parametrize(
"image_factory, job_model_factory, image_attribute_name",
Expand Down
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