Serve exact published runs as datasets

This commit is contained in:
2026-08-04 12:48:37 +02:00
parent 314e7c3edf
commit c888d98b79
4 changed files with 296 additions and 2 deletions
@@ -11,6 +11,11 @@ from govoplan_core.core.dataflows import (
DataflowRunConflictError,
DataflowRunUnavailableError,
)
from govoplan_core.core.datasources import (
DatasourceError,
DatasourceReadRequest,
datasource_catalogue,
)
from govoplan_core.security.time import utc_now
from govoplan_dataflow.backend.backends.base import ExecutionBudget
from govoplan_dataflow.backend.executor import PipelineExecutionError
@@ -20,6 +25,7 @@ from govoplan_dataflow.backend.service import (
_execute_pipeline_preview,
get_pipeline,
get_pipeline_revision,
get_pipeline_run,
list_pipelines,
)
from govoplan_dataflow.backend.subflows import substitute_parameters
@@ -110,6 +116,17 @@ class SqlDataflowDatasetOutputProvider:
raise DataflowRunConflictError(
"The pinned Dataflow definition hash no longer matches the requested revision."
)
if request.run_ref:
return _read_published_run_output(
typed_session,
typed_principal,
registry=self.registry,
request=request,
pipeline=pipeline,
revision=revision,
policy_decision=decision.to_dict(),
row_limit=row_limit,
)
graph = PipelineGraph.model_validate(
substitute_parameters(revision.graph, dict(request.parameters))
)
@@ -179,6 +196,143 @@ def dataset_output_provider(context: object | None = None):
return SqlDataflowDatasetOutputProvider(getattr(context, "registry", None))
def _read_published_run_output(
session,
principal: ApiPrincipal,
*,
registry: object | None,
request: DataflowDatasetRequest,
pipeline,
revision,
policy_decision: dict[str, object],
row_limit: int,
) -> DataflowDatasetResult:
if request.parameters:
raise DataflowRunConflictError(
"An immutable published run cannot be evaluated with new parameters."
)
run = get_pipeline_run(
session,
tenant_id=principal.tenant_id,
run_ref=request.run_ref or "",
)
if run.pipeline_id != pipeline.id or run.pipeline_revision_id != revision.id:
raise DataflowRunConflictError(
"The published run does not belong to the pinned Dataflow revision."
)
if run.definition_hash != revision.content_hash:
raise DataflowRunConflictError(
"The published run definition evidence does not match the pinned revision."
)
if run.status != "succeeded":
raise DataflowRunUnavailableError(
"Only a successful Dataflow run can be used as an immutable dataset."
)
if not run.output_datasource_ref or not run.output_materialization_ref:
raise DataflowRunUnavailableError(
"The successful Dataflow run has no immutable Datasource publication."
)
provider = datasource_catalogue(registry)
if provider is None:
raise DataflowRunUnavailableError(
"The Datasource catalogue required by this published run is not enabled."
)
rows: list[dict[str, object]] = []
materialization = None
total_rows = 0
try:
while len(rows) < row_limit:
remaining = row_limit - len(rows)
page = provider.read_datasource(
session,
principal,
request=DatasourceReadRequest(
datasource_ref=run.output_datasource_ref,
materialization_ref=run.output_materialization_ref,
limit=min(500, remaining),
offset=len(rows),
expected_fingerprint=(
materialization.fingerprint
if materialization is not None
else None
),
),
)
if (
page.materialization is None
or page.materialization.ref != run.output_materialization_ref
):
raise DataflowRunConflictError(
"The Datasource provider returned a different output materialization."
)
if len(page.rows) > remaining:
raise DataflowRunConflictError(
"The Datasource provider exceeded the requested output window."
)
materialization = page.materialization
total_rows = page.total_rows
rows.extend(dict(item) for item in page.rows)
if not page.truncated:
break
if not page.rows:
raise DataflowRunUnavailableError(
"The Datasource provider made no progress while reading the published output."
)
except DatasourceError as exc:
raise DataflowRunUnavailableError(
"The immutable Datasource output is unavailable to the current principal."
) from exc
source_fingerprints = tuple(dict(item) for item in run.source_fingerprints)
if request.expected_source_fingerprints and not _fingerprints_match(
request.expected_source_fingerprints,
source_fingerprints,
):
raise DataflowRunConflictError(
"Dataflow source fingerprints differ from the pinned run evidence."
)
output_hash = hashlib.sha256(
json.dumps(
rows,
sort_keys=True,
separators=(",", ":"),
ensure_ascii=True,
default=str,
).encode("utf-8")
).hexdigest()
if materialization is None:
raise DataflowRunUnavailableError(
"The Datasource provider returned no materialization evidence."
)
return DataflowDatasetResult(
pipeline_ref=pipeline.id,
revision=revision.revision,
definition_hash=revision.content_hash,
rows=tuple(rows),
total_rows=total_rows,
truncated=len(rows) < total_rows,
output_hash=output_hash,
executor_version=run.executor_version,
run_ref=f"dataflow-run:{run.id}",
source_fingerprints=source_fingerprints,
diagnostics=tuple(dict(item) for item in run.diagnostics),
generated_at=run.finished_at or materialization.created_at,
provenance={
"module": "dataflow",
"scope_type": pipeline.scope_type,
"scope_id": pipeline.scope_id,
"policy_decision": policy_decision,
"immutable_run": True,
"publication_ref": run.output_publication_ref,
"datasource_ref": run.output_datasource_ref,
"materialization_ref": run.output_materialization_ref,
"materialization_fingerprint": materialization.fingerprint,
"governance": materialization.governance.to_dict(),
},
)
def _fingerprints_match(expected, actual) -> bool:
def normalized(values):
return sorted(
@@ -270,6 +270,7 @@ DOCUMENTATION = (
"states whether work stopped, completed, failed, or requires operator reconciliation. Scheduled, event, "
"and queued execution is partitioned by tenant module entitlement before a run is claimed. Disabling "
"Dataflow stops new admission and leaves accepted runs available for an explicit operator decision."
" Reporting may pin a successful published run; Dataflow then rechecks run authority and Datasource access and reads only the exact recorded materialization without reparameterizing or re-executing it."
),
layer="available",
documentation_types=("admin", "user"),