# Copyright 2021 Collate # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ Helper module to handle data sampling for the profiler """ from typing import Union, cast from sqlalchemy import Column, inspect, text from sqlalchemy.orm import DeclarativeMeta, Query, Session, aliased from sqlalchemy.orm.util import AliasedClass from sqlalchemy.sql.sqltypes import Enum from metadata.generated.schema.entity.data.table import ( PartitionIntervalType, PartitionProfilerConfig, ProfileSampleType, TableData, ) from metadata.profiler.api.models import ProfileSampleConfig from metadata.profiler.orm.functions.modulo import ModuloFn from metadata.profiler.orm.functions.random_num import RandomNumFn from metadata.profiler.orm.registry import Dialects from metadata.profiler.processor.handle_partition import partition_filter_handler from metadata.profiler.processor.sampler.sampler_interface import SamplerInterface from metadata.utils.sqa_utils import ( build_query_filter, dispatch_to_date_or_datetime, get_integer_range_filter, get_partition_col_type, get_value_filter, ) RANDOM_LABEL = "random" def _object_value_for_elem(self, elem): """ we have mapped DataType.ENUM: sqlalchemy.Enum if map by default return None, we will always get None because there is no enum map to lookup, so what we are doing here is basically trusting the database, that it will be storing the correct map key and showing directly that on the UI, and in this approach we will be only able to display what database has stored (i.e the key) and not the actual value of the same! """ return self._object_lookup.get(elem, elem) # pylint: disable=protected-access Enum._object_value_for_elem = _object_value_for_elem # pylint: disable=protected-access class SQASampler(SamplerInterface): """ Generates a sample of the data to not run the query in the whole table. """ @partition_filter_handler(build_sample=True) def get_sample_query(self) -> Query: """get query for sample data""" if self.profile_sample_type == ProfileSampleType.PERCENTAGE: return ( self.client.query( self.table, (ModuloFn(RandomNumFn(), 100)).label(RANDOM_LABEL), ) .suffix_with( f"SAMPLE BERNOULLI ({self.profile_sample or 100})", dialect=Dialects.Snowflake, ) .suffix_with( f"TABLESAMPLE SYSTEM ({self.profile_sample or 100} PERCENT)", dialect=Dialects.BigQuery, ) .cte(f"{self.table.__tablename__}_rnd") ) table_query = self.client.query(self.table) return ( self.client.query( self.table, (ModuloFn(RandomNumFn(), table_query.count())).label(RANDOM_LABEL), ) .order_by(RANDOM_LABEL) .limit(self.profile_sample) .cte(f"{self.table.__tablename__}_rnd") ) def random_sample(self) -> Union[DeclarativeMeta, AliasedClass]: """ Either return a sampled CTE of table, or the full table if no sampling is required. """ if self._profile_sample_query: return self._rdn_sample_from_user_query() if not self.profile_sample: if self._partition_details: return self._partitioned_table() return self.table # Add new RandomNumFn column rnd = self.get_sample_query() session_query = self.client.query(rnd) # Prepare sampled CTE sampled = session_query.where(rnd.c.random <= self.profile_sample).cte( f"{self.table.__tablename__}_sample" ) # Assign as an alias return aliased(self.table, sampled) def fetch_sample_data(self) -> TableData: """ Use the sampler to retrieve sample data rows as per limit given by user :return: TableData to be added to the Table Entity """ if self._profile_sample_query: return self._fetch_sample_data_from_user_query() # Add new RandomNumFn column rnd = self.get_sample_query() sqa_columns = [col for col in inspect(rnd).c if col.name != RANDOM_LABEL] sqa_sample = ( self.client.query(*sqa_columns) .select_from(rnd) .limit(self.sample_limit) .all() ) return TableData( columns=[column.name for column in sqa_columns], rows=[list(row) for row in sqa_sample], ) def _fetch_sample_data_from_user_query(self) -> TableData: """Returns a table data object using results from query execution""" rnd = self.client.execute(f"{self._profile_sample_query}") try: columns = [col.name for col in rnd.cursor.description] except AttributeError: columns = list(rnd.keys()) return TableData( columns=columns, rows=[list(row) for row in rnd.fetchmany(100)], ) def _rdn_sample_from_user_query(self) -> Query: """Returns sql alchemy object to use when running profiling""" return self.client.query(self.table).from_statement( text(f"{self._profile_sample_query}") ) def _partitioned_table(self) -> Query: """Return the Query object for partitioned tables""" self._partition_details = cast( PartitionProfilerConfig, self._partition_details ) # satisfying type checker partition_field = self._partition_details.partitionColumnName type_ = get_partition_col_type( partition_field, self.table.__table__.c, ) if ( self._partition_details.partitionIntervalType == PartitionIntervalType.COLUMN_VALUE ): return aliased( self.table, ( self.client.query(self.table) .filter( get_value_filter( Column(partition_field), self._partition_details.partitionValues, ) ) .subquery() ), ) if ( self._partition_details.partitionIntervalType == PartitionIntervalType.INTEGER_RANGE ): return aliased( self.table, ( self.client.query(self.table) .filter( get_integer_range_filter( Column(partition_field), self._partition_details.partitionIntegerRangeStart, self._partition_details.partitionIntegerRangeEnd, ) ) .subquery() ), ) return aliased( self.table, ( self.client.query(self.table) .filter( build_query_filter( [ ( Column(partition_field), "ge", dispatch_to_date_or_datetime( self._partition_details.partitionInterval, text( self._partition_details.partitionIntervalUnit.value ), type_, ), ) ], False, ) ) .subquery() ), )