def metadata_scan(
catalog: Catalog,
detectors: List[MetadataDetector],
work_generator: Generator[Tuple[CatSchema, CatTable, CatColumn], None,
None],
generator: Generator[Tuple[CatSchema, CatTable, CatColumn], None, None],
):
total_columns = len([c for s, t, c in work_generator])
counter = 0
set_number = 0
for schema, table, column in tqdm(generator,
total=total_columns,
desc="columns",
unit="columns"):
counter += 1
LOGGER.debug("Scanning column name %s", column.fqdn)
for detector in detectors:
type = detector.detect(column)
if type is not None:
set_number += 1
catalog.set_column_pii_type(column=column,
pii_type=type,
pii_plugin=detector.name)
break
LOGGER.info("Columns Scanned: %d, Columns Labeled: %d", counter,
set_number)
def extract_lineage(
catalog: Catalog,
visited_query: DmlVisitor,
source: CatSource,
parsed: Parsed,
start_time,
end_time,
) -> JobExecution:
job = catalog.add_job(name=parsed.name,
source=source,
context={"query": parsed.query})
job_execution = catalog.add_job_execution(
job=job,
started_at=start_time,
ended_at=end_time,
status=JobExecutionStatus.SUCCESS,
)
for source, target in zip(visited_query.source_columns,
visited_query.target_columns):
for column in source.columns:
edge = catalog.add_column_lineage(column, target, job_execution.id,
{})
logging.debug("Added {}".format(edge))
return job_execution
def _bind_target(self, catalog: Catalog, source: CatSource):
target_table_visitor = RangeVarVisitor()
target_table_visitor(self._insert_table)
if target_table_visitor.is_qualified:
schema = catalog.get_schema(
source_name=source.name,
schema_name=target_table_visitor.schema_name)
elif source.default_schema is not None:
schema = source.default_schema.schema
else:
raise SemanticError("No default schema set for source {}".format(
source.fqdn))
self._target_table = catalog.add_table(
table_name=target_table_visitor.name, schema=schema)
sort_order = 1
for col in self._insert_columns:
self._target_columns.append(
catalog.add_column(
column_name=col,
data_type="varchar",
sort_order=sort_order,
table=self._target_table,
))
def scan_sources(
catalog: Catalog,
source_names: Optional[List[str]] = None,
include_schema_regex: Optional[List[str]] = None,
exclude_schema_regex: Optional[List[str]] = None,
include_table_regex: Optional[List[str]] = None,
exclude_table_regex: Optional[List[str]] = None,
):
with catalog.managed_session:
if source_names is not None and len(source_names) > 0:
sources: List[CatSource] = []
for source_name in source_names:
try:
sources.append(catalog.get_source(source_name))
except NoResultFound:
LOGGER.error("Source '%s' not found", source_name)
else:
sources = catalog.get_sources()
LOGGER.info("%d sources will be scanned", len(sources))
for source in sources:
scanner = DbScanner(
catalog,
source,
include_schema_regex_str=include_schema_regex,
exclude_schema_regex_str=exclude_schema_regex,
include_table_regex_str=include_table_regex,
exclude_table_regex_str=exclude_table_regex,
)
LOGGER.info("Scanning {}".format(scanner.name))
try:
scanner.scan()
except StopIteration:
raise NoMatchesError
def data_scan(
catalog: Catalog,
detectors: List[DatumDetector],
work_generator: Generator[Tuple[CatSchema, CatTable, CatColumn], None,
None],
generator: Generator[Tuple[CatSchema, CatTable, CatColumn, str], None,
None],
sample_size: int = SMALL_TABLE_MAX,
):
total_columns = _filter_text_columns([c for s, t, c in work_generator])
total_work = len(total_columns) * sample_size
counter = 0
set_number = 0
for schema, table, column, val in tqdm(generator,
total=total_work,
desc="datum",
unit="datum"):
counter += 1
LOGGER.debug("Scanning column name %s", column.fqdn)
if val is not None:
for detector in detectors:
type = detector.detect(column=column, datum=val)
if type is not None:
set_number += 1
catalog.set_column_pii_type(column=column,
pii_type=type,
pii_plugin=detector.name)
LOGGER.debug("{} has {}".format(column.fqdn, type))
scan_logger.info("deep_scan",
extra={
"column": column.fqdn,
"pii_types": type
})
data_logger.info(
"deep_scan",
extra={
"column": column.fqdn,
"data": val,
"pii_types": type
},
)
break
LOGGER.info("Columns Scanned: %d, Columns Labeled: %d", counter,
set_number)
def column_generator(
catalog: Catalog,
source: CatSource,
last_run: Optional[datetime.datetime] = None,
include_schema_regex_str: List[str] = None,
exclude_schema_regex_str: List[str] = None,
include_table_regex_str: List[str] = None,
exclude_table_regex_str: List[str] = None,
) -> Generator[Tuple[CatSchema, CatTable, CatColumn], None, None]:
try:
for schema, table in table_generator(
catalog=catalog,
source=source,
include_schema_regex_str=include_schema_regex_str,
exclude_schema_regex_str=exclude_schema_regex_str,
include_table_regex_str=include_table_regex_str,
exclude_table_regex_str=exclude_table_regex_str,
):
for column in catalog.get_columns_for_table(table=table,
newer_than=last_run):
LOGGER.debug(
f"Scanning {schema.name}.{table.name}.{column.name}")
yield schema, table, column
except StopIteration:
raise NoMatchesError
def create_graph(catalog: Catalog,
visited_queries: List[DmlVisitor]) -> DbGraph:
logger = LogMixin()
job_ids = set()
for query in visited_queries:
job = catalog.add_job(query.name, {})
job_execution = catalog.add_job_execution(job, datetime.now(),
datetime.now(),
JobExecutionStatus.SUCCESS)
for source, target in zip(query.source_columns, query.target_columns):
edge = catalog.add_column_lineage(source, target, job_execution.id,
{})
job_ids.add(job.id)
logger.logger.debug("Added {}".format(edge))
graph = DbGraph(catalog, job_ids)
graph.load()
return graph
def _bind_target(self, catalog: Catalog, source: CatSource):
target_table_visitor = RangeVarVisitor()
target_table_visitor(self._insert_table)
logging.debug("Searching for: {}".format(
target_table_visitor.search_string))
try:
self._target_table = catalog.search_table(
source_like=source.name, **target_table_visitor.search_string)
except RuntimeError as error:
logging.debug(str(error))
raise TableNotFound(
'"{schema_like}"."{table_like}" is not found'.format(
**target_table_visitor.search_string))
logging.debug("Bound target table: {}".format(self._target_table))
if len(self._insert_columns) == 0:
self._target_columns = catalog.get_columns_for_table(
self._target_table)
logging.debug("Bound all columns in {}".format(self._target_table))
else:
bound_cols = catalog.get_columns_for_table(
self._target_table, column_names=self._insert_columns)
# Handle error case
if len(bound_cols) != len(self._insert_columns):
for column in self._insert_columns:
found = False
for bound in bound_cols:
if column == bound.name:
found = True
break
if not found:
raise ColumnNotFound(
'"{}" not found in the following tables: {}'.
format(
column,
json.dumps([self._target_table],
cls=CatTableEncoder),
))
self._target_columns = bound_cols
logging.debug("Bound {} target columns".format(len(bound_cols)))
def runserver(obj, port):
logger = LogMixin()
with open(obj, "r") as file:
config = yaml.load(file, Loader=yaml.FullLoader)
logger.logger.debug("Load config file: {}".format(obj))
logger.logger.debug(config)
catalog = Catalog(**config["catalog"])
# elif config.snowflake is not None:
# source = Snowflake(config.file)
server = Server(port, catalog)
server.run_server()
def table_generator(
catalog: Catalog,
source: CatSource,
include_schema_regex_str: List[str] = None,
exclude_schema_regex_str: List[str] = None,
include_table_regex_str: List[str] = None,
exclude_table_regex_str: List[str] = None,
) -> Generator[Tuple[CatSchema, CatTable], None, None]:
schemata = filter_objects(
include_schema_regex_str,
exclude_schema_regex_str,
[
CatalogObject(s.name, s.id)
for s in catalog.search_schema(source_like=source.name,
schema_like="%")
],
)
for schema_object in schemata:
schema = catalog.get_schema_by_id(schema_object.id)
LOGGER.info("Generating schema %s", schema.name)
table_objects = filter_objects(
include_table_regex_str,
exclude_table_regex_str,
[
CatalogObject(t.name, t.id)
for t in catalog.search_tables(source_like=source.name,
schema_like=schema.name,
table_like="%")
],
)
for table_object in table_objects:
table = catalog.get_table_by_id(table_object.id)
LOGGER.info("Generating table %s", table.name)
yield schema, table
def add_athena_source(
catalog: Catalog,
name: str,
region_name: str,
s3_staging_dir: str,
aws_access_key_id: Optional[str] = None,
aws_secret_access_key: Optional[str] = None,
) -> CatSource:
with catalog.commit_context:
return catalog.add_source(
name=name,
aws_access_key_id=aws_access_key_id,
aws_secret_access_key=aws_secret_access_key,
region_name=region_name,
s3_staging_dir=s3_staging_dir,
source_type="athena",
)
def add_redshift_source(
catalog: Catalog,
name: str,
username: str,
password: str,
database: str,
uri: str,
port: Optional[int] = None,
) -> CatSource:
with catalog.commit_context:
return catalog.add_source(
name=name,
username=username,
password=password,
database=database,
uri=uri,
port=port,
source_type="redshift",
)
def add_snowflake_source(
catalog: Catalog,
name: str,
account: str,
username: str,
password: str,
database: str,
warehouse: str,
role: str,
) -> CatSource:
with catalog.commit_context:
return catalog.add_source(
name=name,
username=username,
password=password,
database=database,
account=account,
warehouse=warehouse,
role=role,
source_type="snowflake",
)
def data_generator(
catalog: Catalog,
source: CatSource,
last_run: Optional[datetime.datetime] = None,
include_schema_regex_str: List[str] = None,
exclude_schema_regex_str: List[str] = None,
include_table_regex_str: List[str] = None,
exclude_table_regex_str: List[str] = None,
sample_size=SMALL_TABLE_MAX,
) -> Generator[Tuple[CatSchema, CatTable, CatColumn, str], None, None]:
for schema, table in table_generator(
catalog=catalog,
source=source,
include_schema_regex_str=include_schema_regex_str,
exclude_schema_regex_str=exclude_schema_regex_str,
include_table_regex_str=include_table_regex_str,
exclude_table_regex_str=exclude_table_regex_str,
):
try:
columns = _filter_text_columns(
catalog.get_columns_for_table(table=table,
newer_than=last_run))
if len(columns) > 0:
for row in _row_generator(
column_list=columns,
schema=schema,
table=table,
source=source,
sample_size=sample_size,
):
for col, val in zip(columns, row):
yield schema, table, col, val
except StopIteration:
raise NoMatchesError
except exc.SQLAlchemyError as e:
LOGGER.warning(
f"Exception when getting data for {schema.name}.{table.name}. Code: {e.code}"
)
def add_sqlite_source(
catalog: Catalog, name: str, path: Path,
):
with catalog.managed_session:
catalog.add_source(name=name, uri=str(path), source_type="sqlite")
def scan_database(
catalog: Catalog,
source: CatSource,
scan_type: ScanTypeEnum = ScanTypeEnum.metadata,
incremental: bool = True,
output_format: OutputFormat = OutputFormat.tabular,
list_all: bool = False,
include_schema_regex: List[str] = None,
exclude_schema_regex: List[str] = None,
include_table_regex: List[str] = None,
exclude_table_regex: List[str] = None,
sample_size: int = SMALL_TABLE_MAX,
) -> Union[List[Any], Dict[Any, Any]]:
message = "Source: {source_name}, scan_type: {scan_type}, include_schema: {include_schema}, \
exclude_schema: {exclude_schema}, include_table: {include_table}, exclude_schema: {exclude_table}".format(
source_name=source.name,
scan_type=str(scan_type),
include_schema=",".join(include_schema_regex)
if include_schema_regex is not None else "None",
exclude_schema=",".join(exclude_schema_regex)
if exclude_schema_regex is not None else "None",
include_table=",".join(include_table_regex)
if include_table_regex is not None else "None",
exclude_table=",".join(exclude_table_regex)
if exclude_table_regex is not None else "None",
)
status_message = "Success"
exit_code = 0
with catalog.managed_session:
scan_sources(
catalog=catalog,
source_names=[source.name],
include_schema_regex=include_schema_regex,
exclude_schema_regex=exclude_schema_regex,
include_table_regex=include_table_regex,
exclude_table_regex=exclude_table_regex,
)
last_run: Optional[datetime.datetime] = None
if incremental:
last_task = catalog.get_latest_task("piicatcher.{}".format(
source.name))
last_run = last_task.updated_at if last_task is not None else None
if last_run is not None:
LOGGER.debug("Last Run at {}", last_run)
else:
LOGGER.debug("No last run found")
try:
scan_sources(
catalog=catalog,
source_names=[source.name],
include_schema_regex=include_schema_regex,
exclude_schema_regex=exclude_schema_regex,
include_table_regex=include_table_regex,
exclude_table_regex=exclude_table_regex,
)
if scan_type == ScanTypeEnum.metadata:
detector_list = [
detector() for detector in
detectors.detector_registry.get_all().values()
if issubclass(detector, MetadataDetector)
]
metadata_scan(
catalog=catalog,
detectors=detector_list,
work_generator=column_generator(
catalog=catalog,
source=source,
last_run=last_run,
exclude_schema_regex_str=exclude_schema_regex,
include_schema_regex_str=include_schema_regex,
exclude_table_regex_str=exclude_table_regex,
include_table_regex_str=include_table_regex,
),
generator=column_generator(
catalog=catalog,
source=source,
last_run=last_run,
exclude_schema_regex_str=exclude_schema_regex,
include_schema_regex_str=include_schema_regex,
exclude_table_regex_str=exclude_table_regex,
include_table_regex_str=include_table_regex,
),
)
else:
detector_list = [
detector() for detector in
detectors.detector_registry.get_all().values()
if issubclass(detector, DatumDetector)
]
data_scan(
catalog=catalog,
detectors=detector_list,
work_generator=column_generator(
catalog=catalog,
source=source,
last_run=last_run,
exclude_schema_regex_str=exclude_schema_regex,
include_schema_regex_str=include_schema_regex,
exclude_table_regex_str=exclude_table_regex,
include_table_regex_str=include_table_regex,
),
generator=data_generator(
catalog=catalog,
source=source,
last_run=last_run,
exclude_schema_regex_str=exclude_schema_regex,
include_schema_regex_str=include_schema_regex,
exclude_table_regex_str=exclude_table_regex,
include_table_regex_str=include_table_regex,
sample_size=sample_size,
),
sample_size=sample_size,
)
if output_format == OutputFormat.tabular:
return output_tabular(catalog=catalog,
source=source,
list_all=list_all,
last_run=last_run)
else:
return output_dict(catalog=catalog,
source=source,
list_all=list_all,
last_run=last_run)
except Exception as e:
status_message = str(e)
exit_code = 1
raise e
finally:
catalog.add_task(
"piicatcher.{}".format(source.name),
exit_code,
"{}.{}".format(message, status_message),
)
def bind(self, catalog: Catalog):
target_table_visitor = RangeVarVisitor()
target_table_visitor.visit(self._target_table)
self.logger.debug(
"Searching for: {}".format(target_table_visitor.search_string)
)
self._target_table = catalog.search_table(**target_table_visitor.search_string)
self.logger.debug("Bound target table: {}".format(self._target_table))
if len(self._target_columns) == 0:
self._target_columns = catalog.get_columns_for_table(self._target_table)
self.logger.debug("Bound all columns in {}".format(self._target_table))
else:
bound_cols = catalog.get_columns_for_table(
self._target_table, column_names=self._target_columns
)
# Handle error case
if len(bound_cols) != len(self._target_columns):
for column in self._target_columns:
found = False
for bound in bound_cols:
if column == bound.name:
found = True
break
if not found:
raise RuntimeError("'{}' column is not found".format(column))
self._target_columns = bound_cols
self.logger.debug("Bound {} target columns".format(len(bound_cols)))
alias_map = {}
bound_tables = []
for table in self._source_tables:
visitor = RangeVarVisitor()
visitor.visit(table)
if visitor.alias is not None:
alias_map[visitor.alias] = visitor.search_string
self.logger.debug("Searching for: {}".format(visitor.search_string))
candidate_table = catalog.search_table(**visitor.search_string)
self.logger.debug("Bound source table: {}".format(candidate_table))
bound_tables.append(candidate_table)
self._source_tables = bound_tables
bound_cols = []
for column in self._source_columns:
column_ref_visitor = ColumnRefVisitor()
column_ref_visitor.visit(column)
if column_ref_visitor.name[0] in alias_map:
table_name = alias_map[column_ref_visitor.name[0]]
else:
table_name = {"table_like": column_ref_visitor.name[0]}
self.logger.debug("Searching for: {}".format(table_name))
candidate_table = catalog.search_table(**table_name)
bound = catalog.get_columns_for_table(
table=candidate_table, column_names=[column_ref_visitor.name[1]]
)
if len(bound) == 0:
raise RuntimeError("{} not found in table".format(column))
elif len(bound) > 1:
raise RuntimeError("Ambiguous column name. Multiple matches found")
self.logger.debug("Bound source column: {}".format(bound[0]))
bound_cols.append(bound[0])
self._source_columns = bound_cols
