import warnings
from typing import Callable, Dict, Iterable, List, Optional, Tuple
from feast import type_map
from feast.data_source import DataSource
from feast.errors import DataSourceNotFoundException
from feast.protos.feast.core.DataSource_pb2 import DataSource as DataSourceProto
from feast.protos.feast.core.SavedDataset_pb2 import (
SavedDatasetStorage as SavedDatasetStorageProto,
)
from feast.repo_config import RepoConfig
from feast.saved_dataset import SavedDatasetStorage
from feast.value_type import ValueType
[docs]class BigQuerySource(DataSource):
def __init__(
self,
*,
event_timestamp_column: Optional[str] = "",
table: Optional[str] = None,
created_timestamp_column: Optional[str] = "",
field_mapping: Optional[Dict[str, str]] = None,
date_partition_column: Optional[str] = None,
query: Optional[str] = None,
name: Optional[str] = None,
description: Optional[str] = "",
tags: Optional[Dict[str, str]] = None,
owner: Optional[str] = "",
timestamp_field: Optional[str] = None,
):
"""Create a BigQuerySource from an existing table or query.
Args:
table (optional): The BigQuery table where features can be found.
event_timestamp_column: (Deprecated) Event timestamp column used for point in time joins of feature values.
created_timestamp_column (optional): Timestamp column when row was created, used for deduplicating rows.
field_mapping: A dictionary mapping of column names in this data source to feature names in a feature table
or view. Only used for feature columns, not entities or timestamp columns.
date_partition_column (deprecated): Timestamp column used for partitioning.
query (optional): SQL query to execute to generate data for this data source.
name (optional): Name for the source. Defaults to the table if not specified.
description (optional): A human-readable description.
tags (optional): A dictionary of key-value pairs to store arbitrary metadata.
owner (optional): The owner of the bigquery source, typically the email of the primary
maintainer.
timestamp_field (optional): Event timestamp field used for point in time
joins of feature values.
Example:
>>> from feast import BigQuerySource
>>> my_bigquery_source = BigQuerySource(table="gcp_project:bq_dataset.bq_table")
"""
if table is None and query is None:
raise ValueError('No "table" or "query" argument provided.')
self.bigquery_options = BigQueryOptions(table=table, query=query)
if date_partition_column:
warnings.warn(
(
"The argument 'date_partition_column' is not supported for BigQuery sources. "
"It will be removed in Feast 0.21+"
),
DeprecationWarning,
)
# If no name, use the table as the default name
_name = name
if not _name:
if table:
_name = table
else:
warnings.warn(
(
f"Starting in Feast 0.21, Feast will require either a name for a data source (if using query) or `table`: {self.query}"
),
DeprecationWarning,
)
super().__init__(
name=_name if _name else "",
event_timestamp_column=event_timestamp_column,
created_timestamp_column=created_timestamp_column,
field_mapping=field_mapping,
description=description,
tags=tags,
owner=owner,
timestamp_field=timestamp_field,
)
# Note: Python requires redefining hash in child classes that override __eq__
def __hash__(self):
return super().__hash__()
def __eq__(self, other):
if not isinstance(other, BigQuerySource):
raise TypeError(
"Comparisons should only involve BigQuerySource class objects."
)
return (
super().__eq__(other)
and self.table == other.table
and self.query == other.query
)
@property
def table(self):
return self.bigquery_options.table
@property
def query(self):
return self.bigquery_options.query
[docs] @staticmethod
def from_proto(data_source: DataSourceProto):
assert data_source.HasField("bigquery_options")
return BigQuerySource(
name=data_source.name,
field_mapping=dict(data_source.field_mapping),
table=data_source.bigquery_options.table,
timestamp_field=data_source.timestamp_field,
created_timestamp_column=data_source.created_timestamp_column,
query=data_source.bigquery_options.query,
description=data_source.description,
tags=dict(data_source.tags),
owner=data_source.owner,
)
[docs] def to_proto(self) -> DataSourceProto:
data_source_proto = DataSourceProto(
name=self.name,
type=DataSourceProto.BATCH_BIGQUERY,
field_mapping=self.field_mapping,
bigquery_options=self.bigquery_options.to_proto(),
description=self.description,
tags=self.tags,
owner=self.owner,
timestamp_field=self.timestamp_field,
created_timestamp_column=self.created_timestamp_column,
)
return data_source_proto
[docs] def validate(self, config: RepoConfig):
if not self.query:
from google.api_core.exceptions import NotFound
from google.cloud import bigquery
client = bigquery.Client()
try:
client.get_table(self.table)
except NotFound:
raise DataSourceNotFoundException(self.table)
[docs] def get_table_query_string(self) -> str:
"""Returns a string that can directly be used to reference this table in SQL"""
if self.table:
return f"`{self.table}`"
else:
return f"({self.query})"
[docs] @staticmethod
def source_datatype_to_feast_value_type() -> Callable[[str], ValueType]:
return type_map.bq_to_feast_value_type
[docs] def get_table_column_names_and_types(
self, config: RepoConfig
) -> Iterable[Tuple[str, str]]:
from google.cloud import bigquery
client = bigquery.Client()
if self.table:
schema = client.get_table(self.table).schema
if not isinstance(schema[0], bigquery.schema.SchemaField):
raise TypeError("Could not parse BigQuery table schema.")
else:
bq_columns_query = f"SELECT * FROM ({self.query}) LIMIT 1"
queryRes = client.query(bq_columns_query).result()
schema = queryRes.schema
name_type_pairs: List[Tuple[str, str]] = []
for field in schema:
bq_type_as_str = field.field_type
if field.mode == "REPEATED":
bq_type_as_str = "ARRAY<" + bq_type_as_str + ">"
name_type_pairs.append((field.name, bq_type_as_str))
return name_type_pairs
[docs]class BigQueryOptions:
"""
Configuration options for a BigQuery data source.
"""
def __init__(
self, table: Optional[str], query: Optional[str],
):
self.table = table or ""
self.query = query or ""
[docs] @classmethod
def from_proto(cls, bigquery_options_proto: DataSourceProto.BigQueryOptions):
"""
Creates a BigQueryOptions from a protobuf representation of a BigQuery option
Args:
bigquery_options_proto: A protobuf representation of a DataSource
Returns:
Returns a BigQueryOptions object based on the bigquery_options protobuf
"""
bigquery_options = cls(
table=bigquery_options_proto.table, query=bigquery_options_proto.query,
)
return bigquery_options
[docs] def to_proto(self) -> DataSourceProto.BigQueryOptions:
"""
Converts an BigQueryOptionsProto object to its protobuf representation.
Returns:
BigQueryOptionsProto protobuf
"""
bigquery_options_proto = DataSourceProto.BigQueryOptions(
table=self.table, query=self.query,
)
return bigquery_options_proto
[docs]class SavedDatasetBigQueryStorage(SavedDatasetStorage):
_proto_attr_name = "bigquery_storage"
bigquery_options: BigQueryOptions
def __init__(self, table: str):
self.bigquery_options = BigQueryOptions(table=table, query=None)
[docs] @staticmethod
def from_proto(storage_proto: SavedDatasetStorageProto) -> SavedDatasetStorage:
return SavedDatasetBigQueryStorage(
table=BigQueryOptions.from_proto(storage_proto.bigquery_storage).table
)
[docs] def to_proto(self) -> SavedDatasetStorageProto:
return SavedDatasetStorageProto(
bigquery_storage=self.bigquery_options.to_proto()
)
[docs] def to_data_source(self) -> DataSource:
return BigQuerySource(table=self.bigquery_options.table)