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feat: Faiss and In memory store (feast-dev#4464)
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* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add faiss & in memory online store

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* add dependency

Signed-off-by: cmuhao <sduxuhao@gmail.com>

* update package name

Signed-off-by: cmuhao <sduxuhao@gmail.com>

---------

Signed-off-by: cmuhao <sduxuhao@gmail.com>
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@HaoXuAI @emgeee
HaoXuAI authored and emgeee committed Oct 23, 2024
1 parent 80b9c99 commit 0397817
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236 changes: 236 additions & 0 deletions sdk/python/feast/infra/online_stores/contrib/faiss_online_store.py
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import logging
from datetime import datetime
from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple

import faiss
import numpy as np
from google.protobuf.timestamp_pb2 import Timestamp

from feast import Entity, FeatureView, RepoConfig
from feast.infra.key_encoding_utils import serialize_entity_key
from feast.infra.online_stores.online_store import OnlineStore
from feast.protos.feast.types.EntityKey_pb2 import EntityKey
from feast.protos.feast.types.Value_pb2 import Value
from feast.repo_config import FeastConfigBaseModel


class FaissOnlineStoreConfig(FeastConfigBaseModel):
dimension: int
index_path: str
index_type: str = "IVFFlat"
nlist: int = 100


class InMemoryStore:
def __init__(self):
self.feature_names: List[str] = []
self.entity_keys: Dict[str, int] = {}

def update(self, feature_names: List[str], entity_keys: Dict[str, int]):
self.feature_names = feature_names
self.entity_keys = entity_keys

def delete(self, entity_keys: List[str]):
for entity_key in entity_keys:
if entity_key in self.entity_keys:
del self.entity_keys[entity_key]

def read(self, entity_keys: List[str]) -> List[Optional[int]]:
return [self.entity_keys.get(entity_key) for entity_key in entity_keys]

def teardown(self):
self.feature_names = []
self.entity_keys = {}


class FaissOnlineStore(OnlineStore):
_index: Optional[faiss.IndexIVFFlat] = None
_in_memory_store: InMemoryStore = InMemoryStore()
_config: Optional[FaissOnlineStoreConfig] = None
_logger: logging.Logger = logging.getLogger(__name__)

def _get_index(self, config: RepoConfig) -> faiss.IndexIVFFlat:
if self._index is None or self._config is None:
raise ValueError("Index is not initialized")
return self._index

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,
):
feature_views = tables_to_keep
if not feature_views:
return

feature_names = [f.name for f in feature_views[0].features]
dimension = len(feature_names)

self._config = FaissOnlineStoreConfig(**config.online_store.dict())
if self._index is None or not partial:
quantizer = faiss.IndexFlatL2(dimension)
self._index = faiss.IndexIVFFlat(quantizer, dimension, self._config.nlist)
self._index.train(
np.random.rand(self._config.nlist * 100, dimension).astype(np.float32)
)
self._in_memory_store = InMemoryStore()

self._in_memory_store.update(feature_names, {})

def teardown(
self,
config: RepoConfig,
tables: Sequence[FeatureView],
entities: Sequence[Entity],
):
self._index = None
self._in_memory_store.teardown()

def online_read(
self,
config: RepoConfig,
table: FeatureView,
entity_keys: List[EntityKey],
requested_features: Optional[List[str]] = None,
) -> List[Tuple[Optional[datetime], Optional[Dict[str, Value]]]]:
if self._index is None:
return [(None, None)] * len(entity_keys)

results: List[Tuple[Optional[datetime], Optional[Dict[str, Any]]]] = []
for entity_key in entity_keys:
serialized_key = serialize_entity_key(
entity_key, config.entity_key_serialization_version
).hex()
idx = self._in_memory_store.entity_keys.get(serialized_key, -1)
if idx == -1:
results.append((None, None))
else:
feature_vector = self._index.reconstruct(int(idx))
feature_dict = {
name: Value(double_val=value)
for name, value in zip(
self._in_memory_store.feature_names, feature_vector
)
}
results.append((None, feature_dict))
return results

def online_write_batch(
self,
config: RepoConfig,
table: FeatureView,
data: List[Tuple[EntityKey, Dict[str, Value], datetime, Optional[datetime]]],
progress: Optional[Callable[[int], Any]],
) -> None:
if self._index is None:
self._logger.warning("Index is not initialized. Skipping write operation.")
return

feature_vectors = []
serialized_keys = []

for entity_key, feature_dict, _, _ in data:
serialized_key = serialize_entity_key(
entity_key, config.entity_key_serialization_version
).hex()
feature_vector = np.array(
[
feature_dict[name].double_val
for name in self._in_memory_store.feature_names
],
dtype=np.float32,
)

feature_vectors.append(feature_vector)
serialized_keys.append(serialized_key)

feature_vectors_array = np.array(feature_vectors)

existing_indices = [
self._in_memory_store.entity_keys.get(sk, -1) for sk in serialized_keys
]
mask = np.array(existing_indices) != -1
if np.any(mask):
self._index.remove_ids(
np.array([idx for idx in existing_indices if idx != -1])
)

new_indices = np.arange(
self._index.ntotal, self._index.ntotal + len(feature_vectors_array)
)
self._index.add(feature_vectors_array)

for sk, idx in zip(serialized_keys, new_indices):
self._in_memory_store.entity_keys[sk] = idx

if progress:
progress(len(data))

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[Value],
Optional[Value],
Optional[Value],
]
]:
if self._index is None:
self._logger.warning("Index is not initialized. Returning empty result.")
return []

query_vector = np.array(embedding, dtype=np.float32).reshape(1, -1)
distances, indices = self._index.search(query_vector, top_k)

results: List[
Tuple[
Optional[datetime],
Optional[Value],
Optional[Value],
Optional[Value],
]
] = []
for i, idx in enumerate(indices[0]):
if idx == -1:
continue

feature_vector = self._index.reconstruct(int(idx))

timestamp = Timestamp()
timestamp.GetCurrentTime()

feature_value = Value(string_val=",".join(map(str, feature_vector)))
vector_value = Value(string_val=",".join(map(str, feature_vector)))
distance_value = Value(float_val=distances[0][i])

results.append(
(
timestamp.ToDatetime(),
feature_value,
vector_value,
distance_value,
)
)

return results

async def online_read_async(
self,
config: RepoConfig,
table: FeatureView,
entity_keys: List[EntityKey],
requested_features: Optional[List[str]] = None,
) -> List[Tuple[Optional[datetime], Optional[Dict[str, Value]]]]:
# Implement async read if needed
raise NotImplementedError("Async read is not implemented for FaissOnlineStore")
4 changes: 4 additions & 0 deletions setup.py
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Expand Up @@ -144,6 +144,8 @@

MSSQL_REQUIRED = ["ibis-framework[mssql]>=9.0.0,<10"]

FAISS_REQUIRED = ["faiss-cpu>=1.7.0,<2"]

CI_REQUIRED = (
[
"build",
Expand Down Expand Up @@ -210,6 +212,7 @@
+ SQLITE_VEC_REQUIRED
+ SINGLESTORE_REQUIRED
+ OPENTELEMETRY
+ FAISS_REQUIRED
)

DOCS_REQUIRED = CI_REQUIRED
Expand Down Expand Up @@ -279,6 +282,7 @@
"sqlite_vec": SQLITE_VEC_REQUIRED,
"singlestore": SINGLESTORE_REQUIRED,
"opentelemetry": OPENTELEMETRY,
"faiss": FAISS_REQUIRED,
},
include_package_data=True,
license="Apache",
Expand Down

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