JDarDagran commented on code in PR #39614:
URL: https://github.com/apache/airflow/pull/39614#discussion_r1600010667
##########
airflow/providers/google/cloud/utils/openlineage.py:
##########
@@ -79,3 +92,265 @@ def get_identity_column_lineage_facet(
}
)
return column_lineage_facet
+
+
+@define
+class BigQueryJobRunFacet(BaseFacet):
+ """Facet that represents relevant statistics of bigquery run.
+
+ This facet is used to provide statistics about bigquery run.
+
+ :param cached: BigQuery caches query results. Rest of the statistics will
not be provided for cached queries.
+ :param billedBytes: How many bytes BigQuery bills for.
+ :param properties: Full property tree of BigQUery run.
+ """
+
+ cached: bool
+ billedBytes: int | None = field(default=None)
+ properties: str | None = field(default=None)
+
+
+def get_from_nullable_chain(source: Any, chain: list[str]) -> Any | None:
+ """Get object from nested structure of objects, where it's not guaranteed
that all keys in the nested structure exist.
+
+ Intended to replace chain of `dict.get()` statements.
+
+ Example usage:
+
+ .. code-block:: python
+
+ if (
+ not job._properties.get("statistics")
+ or not job._properties.get("statistics").get("query")
+ or not
job._properties.get("statistics").get("query").get("referencedTables")
+ ):
+ return None
+ result =
job._properties.get("statistics").get("query").get("referencedTables")
+
+ becomes:
+
+ .. code-block:: python
+
+ result = get_from_nullable_chain(properties, ["statistics", "query",
"queryPlan"])
+ if not result:
+ return None
+ """
+ chain.reverse()
+ try:
+ while chain:
+ next_key = chain.pop()
+ if isinstance(source, dict):
+ source = source.get(next_key)
+ else:
+ source = getattr(source, next_key)
+ return source
+ except AttributeError:
+ return None
+
+
+class _BigQueryOpenLineageMixin:
+ def get_openlineage_facets_on_complete(self, _):
+ """
+ Retrieve OpenLineage data for a COMPLETE BigQuery job.
+
+ This method retrieves statistics for the specified job_ids using the
BigQueryDatasetsProvider.
+ It calls BigQuery API, retrieving input and output dataset info from
it, as well as run-level
+ usage statistics.
+
+ Run facets should contain:
+ - ExternalQueryRunFacet
+ - BigQueryJobRunFacet
+
+ Job facets should contain:
+ - SqlJobFacet if operator has self.sql
+
+ Input datasets should contain facets:
+ - DataSourceDatasetFacet
+ - SchemaDatasetFacet
+
+ Output datasets should contain facets:
+ - DataSourceDatasetFacet
+ - SchemaDatasetFacet
+ - OutputStatisticsOutputDatasetFacet
+ """
+ from openlineage.client.facet import ExternalQueryRunFacet, SqlJobFacet
+
+ from airflow.providers.openlineage.extractors import OperatorLineage
+ from airflow.providers.openlineage.sqlparser import SQLParser
+
+ if not self.job_id:
+ return OperatorLineage()
+
+ run_facets: dict[str, BaseFacet] = {
+ "externalQuery":
ExternalQueryRunFacet(externalQueryId=self.job_id, source="bigquery")
+ }
+
+ job_facets = {"sql":
SqlJobFacet(query=SQLParser.normalize_sql(self.sql))}
+
+ self.client = self.hook.get_client(project_id=self.hook.project_id)
+ job_ids = self.job_id
+ if isinstance(self.job_id, str):
+ job_ids = [self.job_id]
+ inputs, outputs = [], []
+ for job_id in job_ids:
+ inner_inputs, inner_outputs, inner_run_facets =
self.get_facets(job_id=job_id)
+ inputs.extend(inner_inputs)
+ outputs.extend(inner_outputs)
+ run_facets.update(inner_run_facets)
+
+ return OperatorLineage(
+ inputs=inputs,
+ outputs=outputs,
+ run_facets=run_facets,
+ job_facets=job_facets,
+ )
+
+ def get_facets(self, job_id: str):
+ inputs = []
+ outputs = []
+ run_facets: dict[str, BaseFacet] = {}
+ if hasattr(self, "log"):
+ self.log.debug("Extracting data from bigquery job: `%s`", job_id)
+ try:
+ job = self.client.get_job(job_id=job_id) # type: ignore
+ props = job._properties
+
+ if get_from_nullable_chain(props, ["status", "state"]) != "DONE":
+ raise ValueError(f"Trying to extract data from running
bigquery job: `{job_id}`")
+
+ run_facets["bigQuery_job"] =
self._get_bigquery_job_run_facet(props)
Review Comment:
I agree, it's more of matter how to deal with the changes/deprecations.
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