feast/sdk/python/feast/infra/online_stores/sqlite.py at podfv2 · feast-dev/feast

497 lines (432 loc) · 17.1 KB
# Copyright 2021 The Feast Authors
# 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
#     https://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.
import itertools
import logging
import sqlite3
import struct
from datetime import datetime
from pathlib import Path
from typing import Any, Callable, Dict, List, Literal, Optional, Sequence, Tuple, Union
from google.protobuf.internal.containers import RepeatedScalarFieldContainer
from pydantic import StrictStr
from feast import Entity
from feast.feature_view import FeatureView
from feast.infra.infra_object import SQLITE_INFRA_OBJECT_CLASS_TYPE, InfraObject
from feast.infra.key_encoding_utils import serialize_entity_key
from feast.infra.online_stores.online_store import OnlineStore
from feast.infra.online_stores.vector_store import VectorStoreConfig
from feast.protos.feast.core.InfraObject_pb2 import InfraObject as InfraObjectProto
from feast.protos.feast.core.Registry_pb2 import Registry as RegistryProto
from feast.protos.feast.core.SqliteTable_pb2 import SqliteTable as SqliteTableProto
from feast.protos.feast.types.EntityKey_pb2 import EntityKey as EntityKeyProto
from feast.protos.feast.types.Value_pb2 import Value as ValueProto
from feast.repo_config import FeastConfigBaseModel, RepoConfig
from feast.utils import _build_retrieve_online_document_record, to_naive_utc
class SqliteOnlineStoreConfig(FeastConfigBaseModel, VectorStoreConfig):
    """Online store config for local (SQLite-based) store"""
    type: Literal["sqlite", "feast.infra.online_stores.sqlite.SqliteOnlineStore"] = (
        "sqlite"
    """ Online store type selector"""
    path: StrictStr = "data/online.db"
    """ (optional) Path to sqlite db """
class SqliteOnlineStore(OnlineStore):
    SQLite implementation of the online store interface. Not recommended for production usage.
    Attributes:
        _conn: SQLite connection.
    _conn: Optional[sqlite3.Connection] = None
    @staticmethod
    def _get_db_path(config: RepoConfig) -> str:
        assert (
            config.online_store.type == "sqlite"
            or config.online_store.type.endswith("SqliteOnlineStore")
        if config.repo_path and not Path(config.online_store.path).is_absolute():
            db_path = str(config.repo_path / config.online_store.path)
        else:
            db_path = config.online_store.path
        return db_path
    def _get_conn(self, config: RepoConfig):
        if not self._conn:
            db_path = self._get_db_path(config)
            self._conn = _initialize_conn(db_path)
            if sys.version_info[0:2] == (3, 10) and config.online_store.vector_enabled:
                import sqlite_vec  # noqa: F401
                self._conn.enable_load_extension(True)  # type: ignore
                sqlite_vec.load(self._conn)
        return self._conn
    def online_write_batch(
        self,
        config: RepoConfig,
        table: FeatureView,
        data: List[
            Tuple[
                EntityKeyProto,
                Dict[str, ValueProto],
                datetime,
                Optional[datetime],
        progress: Optional[Callable[[int], Any]],
    ) -> None:
        conn = self._get_conn(config)
        project = config.project
        with conn:
            for entity_key, values, timestamp, created_ts in data:
                entity_key_bin = serialize_entity_key(
                    entity_key,
                    entity_key_serialization_version=config.entity_key_serialization_version,
                timestamp = to_naive_utc(timestamp)
                if created_ts is not None:
                    created_ts = to_naive_utc(created_ts)
                table_name = _table_id(project, table)
                for feature_name, val in values.items():
                    if config.online_store.vector_enabled:
                        vector_bin = serialize_f32(
                            val.float_list_val.val, config.online_store.vector_len
                        )  # type: ignore
                        conn.execute(
                                    UPDATE {table_name}
                                    SET value = ?, vector_value = ?, event_ts = ?, created_ts = ?
                                    WHERE (entity_key = ? AND feature_name = ?)
                                val.SerializeToString(),
                                vector_bin,
                                timestamp,
                                created_ts,
                                entity_key_bin,
                                feature_name,
                        conn.execute(
                            f"""INSERT OR IGNORE INTO {table_name}
                                (entity_key, feature_name, value, vector_value, event_ts, created_ts)
                                VALUES (?, ?, ?, ?, ?, ?)""",
                                entity_key_bin,
                                feature_name,
                                val.SerializeToString(),
                                vector_bin,
                                timestamp,
                                created_ts,
                        conn.execute(
                                UPDATE {table_name}
                                SET value = ?, event_ts = ?, created_ts = ?
                                WHERE (entity_key = ? AND feature_name = ?)
                                val.SerializeToString(),
                                timestamp,
                                created_ts,
                                entity_key_bin,
                                feature_name,
                        conn.execute(
                            f"""INSERT OR IGNORE INTO {table_name}
                                (entity_key, feature_name, value, event_ts, created_ts)
                                VALUES (?, ?, ?, ?, ?)""",
                                entity_key_bin,
                                feature_name,
                                val.SerializeToString(),
                                timestamp,
                                created_ts,
                if progress:
                    progress(1)
    def online_read(
        self,
        config: RepoConfig,
        table: FeatureView,
        entity_keys: List[EntityKeyProto],
        requested_features: Optional[List[str]] = None,
    ) -> List[Tuple[Optional[datetime], Optional[Dict[str, ValueProto]]]]:
        conn = self._get_conn(config)
        cur = conn.cursor()
        result: List[Tuple[Optional[datetime], Optional[Dict[str, ValueProto]]]] = []
        # Fetch all entities in one go
        cur.execute(
            f"SELECT entity_key, feature_name, value, event_ts "
            f"FROM {_table_id(config.project, table)} "
            f"WHERE entity_key IN ({','.join('?' * len(entity_keys))}) "
            f"ORDER BY entity_key",
                serialize_entity_key(
                    entity_key,
                    entity_key_serialization_version=config.entity_key_serialization_version,
                for entity_key in entity_keys
        rows = cur.fetchall()
        rows = {
            k: list(group) for k, group in itertools.groupby(rows, key=lambda r: r[0])
        for entity_key in entity_keys:
            entity_key_bin = serialize_entity_key(
                entity_key,
                entity_key_serialization_version=config.entity_key_serialization_version,
            res = {}
            res_ts = None
            for _, feature_name, val_bin, ts in rows.get(entity_key_bin, []):
                val = ValueProto()
                val.ParseFromString(val_bin)
                res[feature_name] = val
                res_ts = ts
            if not res:
                result.append((None, None))
            else:
                result.append((res_ts, res))
        return result
    def update(
        self,
        config: RepoConfig,
        tables_to_delete: Sequence[FeatureView],
        tables_to_keep: Sequence[FeatureView],
        entities_to_delete: Sequence[Entity],
        entities_to_keep: Sequence[Entity],
        partial: bool,
        conn = self._get_conn(config)
        project = config.project
        for table in tables_to_keep:
            conn.execute(
                f"CREATE TABLE IF NOT EXISTS {_table_id(project, table)} (entity_key BLOB, feature_name TEXT, value BLOB, vector_value BLOB, event_ts timestamp, created_ts timestamp,  PRIMARY KEY(entity_key, feature_name))"
            conn.execute(
                f"CREATE INDEX IF NOT EXISTS {_table_id(project, table)}_ek ON {_table_id(project, table)} (entity_key);"
        for table in tables_to_delete:
            conn.execute(f"DROP TABLE IF EXISTS {_table_id(project, table)}")
    def plan(
        self, config: RepoConfig, desired_registry_proto: RegistryProto
    ) -> List[InfraObject]:
        project = config.project
        infra_objects: List[InfraObject] = [
            SqliteTable(
                path=self._get_db_path(config),
                name=_table_id(project, FeatureView.from_proto(view)),
            for view in [
                *desired_registry_proto.feature_views,
                *desired_registry_proto.stream_feature_views,
        return infra_objects
    def teardown(
        self,
        config: RepoConfig,
        tables: Sequence[FeatureView],
        entities: Sequence[Entity],
        try:
            os.unlink(self._get_db_path(config))
        except FileNotFoundError:
            pass
    def retrieve_online_documents(
        self,
        config: RepoConfig,
        table: FeatureView,
        requested_feature: str,
        embedding: List[float],
        top_k: int,
        distance_metric: Optional[str] = None,
    ) -> List[
        Tuple[
            Optional[datetime],
            Optional[EntityKeyProto],
            Optional[ValueProto],
            Optional[ValueProto],
            Optional[ValueProto],
        """
        Args:
            config: Feast configuration object
            table: FeatureView object as the table to search
            requested_feature: The requested feature as the column to search
            embedding: The query embedding to search for
            top_k: The number of items to return
        Returns:
            List of tuples containing the event timestamp, the document feature, the vector value, and the distance
        """
        project = config.project
        if not config.online_store.vector_enabled:
            raise ValueError("sqlite-vss is not enabled in the online store config")
        conn = self._get_conn(config)
        cur = conn.cursor()
        # Convert the embedding to a binary format instead of using SerializeToString()
        query_embedding_bin = serialize_f32(embedding, config.online_store.vector_len)
        table_name = _table_id(project, table)
        cur.execute(
            f"""
            CREATE VIRTUAL TABLE vec_example using vec0(
                vector_value float[{config.online_store.vector_len}]
        """
        # Currently I can only insert the embedding value without crashing SQLite, will report a bug
        cur.execute(
            f"""
            INSERT INTO vec_example(rowid, vector_value)
            select rowid, vector_value from {table_name}
        """
        cur.execute(
            INSERT INTO vec_example(rowid, vector_value)
                VALUES (?, ?)
        """,
            (0, query_embedding_bin),
        # Have to join this with the {table_name} to get the feature name and entity_key
        # Also the `top_k` doesn't appear to be working for some reason
        cur.execute(
            f"""
            select
                fv.entity_key,
                f.vector_value,
                fv.value,
                f.distance,
                fv.event_ts
            from (
                select
                    rowid,
                    vector_value,
                    distance
                from vec_example
                where vector_value match ?
                order by distance
                limit ?
            left join {table_name} fv
            on f.rowid = fv.rowid
        """,
            (query_embedding_bin, top_k),
        rows = cur.fetchall()
        result: List[
            Tuple[
                Optional[datetime],
                Optional[EntityKeyProto],
                Optional[ValueProto],
                Optional[ValueProto],
                Optional[ValueProto],
        ] = []
        for entity_key, _, string_value, distance, event_ts in rows:
            result.append(
                _build_retrieve_online_document_record(
                    entity_key,
                    string_value if string_value else b"",
                    embedding,
                    distance,
                    event_ts,
                    config.entity_key_serialization_version,
        return result
def _initialize_conn(db_path: str):
        import sqlite_vec  # noqa: F401
    except ModuleNotFoundError:
        logging.warning("Cannot use sqlite_vec for vector search")
    Path(db_path).parent.mkdir(exist_ok=True)
    return sqlite3.connect(
        db_path,
        detect_types=sqlite3.PARSE_DECLTYPES | sqlite3.PARSE_COLNAMES,
        check_same_thread=False,
def _table_id(project: str, table: FeatureView) -> str:
    return f"{project}_{table.name}"
def serialize_f32(
    vector: Union[RepeatedScalarFieldContainer[float], List[float]], vector_length: int
) -> bytes:
    """serializes a list of floats into a compact "raw bytes" format"""
    return struct.pack(f"{vector_length}f", *vector)
def deserialize_f32(byte_vector: bytes, vector_length: int) -> List[float]:
    """deserializes a list of floats from a compact "raw bytes" format"""
    num_floats = vector_length // 4  # 4 bytes per float
    return list(struct.unpack(f"{num_floats}f", byte_vector))
class SqliteTable(InfraObject):
    A Sqlite table managed by Feast.
    Attributes:
        path: The absolute path of the Sqlite file.
        name: The name of the table.
        conn: SQLite connection.
    path: str
    conn: sqlite3.Connection
    def __init__(self, path: str, name: str):
        super().__init__(name)
        self.path = path
        self.conn = _initialize_conn(path)
    def to_infra_object_proto(self) -> InfraObjectProto:
        sqlite_table_proto = self.to_proto()
        return InfraObjectProto(
            infra_object_class_type=SQLITE_INFRA_OBJECT_CLASS_TYPE,
            sqlite_table=sqlite_table_proto,
    def to_proto(self) -> Any:
        sqlite_table_proto = SqliteTableProto()
        sqlite_table_proto.path = self.path
        sqlite_table_proto.name = self.name
        return sqlite_table_proto
    @staticmethod
    def from_infra_object_proto(infra_object_proto: InfraObjectProto) -> Any:
        return SqliteTable(
            path=infra_object_proto.sqlite_table.path,
            name=infra_object_proto.sqlite_table.name,
    @staticmethod
    def from_proto(sqlite_table_proto: SqliteTableProto) -> Any:
        return SqliteTable(
            path=sqlite_table_proto.path,
            name=sqlite_table_proto.name,
    def update(self):
        if sys.version_info[0:2] == (3, 10):
            try:
                import sqlite_vec  # noqa: F401
                self.conn.enable_load_extension(True)
                sqlite_vec.load(self.conn)
            except ModuleNotFoundError:
                logging.warning("Cannot use sqlite_vec for vector search")
        self.conn.execute(
            f"CREATE TABLE IF NOT EXISTS {self.name} (entity_key BLOB, feature_name TEXT, value BLOB, vector_value BLOB, event_ts timestamp, created_ts timestamp,  PRIMARY KEY(entity_key, feature_name))"
        self.conn.execute(
            f"CREATE INDEX IF NOT EXISTS {self.name}_ek ON {self.name} (entity_key);"
    def teardown(self):
        self.conn.execute(f"DROP TABLE IF EXISTS {self.name}")
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