Source code for airflow.providers.amazon.aws.utils.openlineage
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from __future__ import annotations
from typing import TYPE_CHECKING, Any
from airflow.providers.amazon.aws.hooks.redshift_sql import RedshiftSQLHook
from airflow.providers.common.compat.openlineage.facet import (
ColumnLineageDatasetFacet,
DocumentationDatasetFacet,
Fields,
InputField,
SchemaDatasetFacet,
SchemaDatasetFacetFields,
)
if TYPE_CHECKING:
from airflow.providers.amazon.aws.hooks.redshift_data import RedshiftDataHook
[docs]def get_facets_from_redshift_table(
redshift_hook: RedshiftDataHook | RedshiftSQLHook,
table: str,
redshift_data_api_kwargs: dict,
schema: str = "public",
) -> dict[Any, Any]:
"""
Query redshift for table metadata.
SchemaDatasetFacet and DocumentationDatasetFacet (if table has description) will be created.
"""
sql = f"""
SELECT
cols.column_name,
cols.data_type,
col_des.description as column_description,
tbl_des.description as table_description
FROM
information_schema.columns cols
LEFT JOIN
pg_catalog.pg_description col_des
ON
cols.ordinal_position = col_des.objsubid
AND col_des.objoid = (SELECT oid FROM pg_class WHERE relnamespace =
(SELECT oid FROM pg_namespace WHERE nspname = cols.table_schema) AND relname = cols.table_name)
LEFT JOIN
pg_catalog.pg_class tbl
ON
tbl.relname = cols.table_name
AND tbl.relnamespace = (SELECT oid FROM pg_namespace WHERE nspname = cols.table_schema)
LEFT JOIN
pg_catalog.pg_description tbl_des
ON
tbl.oid = tbl_des.objoid
AND tbl_des.objsubid = 0
WHERE
cols.table_name = '{table}'
AND cols.table_schema = '{schema}';
"""
if isinstance(redshift_hook, RedshiftSQLHook):
records = redshift_hook.get_records(sql)
if records:
table_description = records[0][-1] # Assuming the table description is the same for all rows
else:
table_description = None
documentation = DocumentationDatasetFacet(description=table_description or "")
table_schema = SchemaDatasetFacet(
fields=[
SchemaDatasetFacetFields(name=field[0], type=field[1], description=field[2])
for field in records
]
)
else:
statement_id = redshift_hook.execute_query(
sql=sql, poll_interval=1, **redshift_data_api_kwargs
).statement_id
response = redshift_hook.conn.get_statement_result(Id=statement_id)
table_schema = SchemaDatasetFacet(
fields=[
SchemaDatasetFacetFields(
name=field[0]["stringValue"],
type=field[1]["stringValue"],
description=field[2].get("stringValue"),
)
for field in response["Records"]
]
)
# Table description will be the same for all fields, so we retrieve it from first field.
documentation = DocumentationDatasetFacet(
description=response["Records"][0][3].get("stringValue") or ""
)
return {"schema": table_schema, "documentation": documentation}
[docs]def get_identity_column_lineage_facet(
field_names,
input_datasets,
) -> ColumnLineageDatasetFacet:
"""
Get column lineage facet.
Simple lineage will be created, where each source column corresponds to single destination column
in each input dataset and there are no transformations made.
"""
if field_names and not input_datasets:
raise ValueError("When providing `field_names` You must provide at least one `input_dataset`.")
column_lineage_facet = ColumnLineageDatasetFacet(
fields={
field: Fields(
inputFields=[
InputField(namespace=dataset.namespace, name=dataset.name, field=field)
for dataset in input_datasets
],
transformationType="IDENTITY",
transformationDescription="identical",
)
for field in field_names
}
)
return column_lineage_facet