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docs(bigquery): schema resolver strategy #15164

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7 changes: 7 additions & 0 deletions metadata-ingestion/src/datahub/ingestion/source/bigquery_v2/bigquery.py
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Original file line number Diff line number Diff line change
Expand Up @@ -219,6 +219,13 @@ def test_connection(config_dict: dict) -> TestConnectionReport:
return BigQueryTestConnection.test_connection(config_dict)

def _init_schema_resolver(self) -> SchemaResolver:
"""
The ininitialization of SchemaResolver prefetches all existing urns and schemas in the env/platform/instance.
Because of that, it's important all classes requiring a SchemaResolver use this instance, as it has an already pre-populated cache.
An alternative strategy would be to do an on-demand resolution of the urns/schemas.

TODO: prove pre-fetch is better strategy than on-demand resolution or make this behaviour configurable.
"""
schema_resolution_required = (
self.config.use_queries_v2 or self.config.lineage_use_sql_parser
)
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5 changes: 4 additions & 1 deletion metadata-ingestion/src/datahub/sql_parsing/schema_resolver.py
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Expand Up @@ -168,7 +168,10 @@ def resolve_table(self, table: _TableName) -> Tuple[str, Optional[SchemaInfo]]:
self._track_cache_hit()
return urn_mixed, schema_info

# Track cache miss for the final attempt
logger.debug(
f"Schema resolution failed for table {table}. Tried URNs: "
f"primary={urn}, lower={urn_lower}, mixed={urn_mixed}"
)
self._track_cache_miss()

if self._prefers_urn_lower():
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