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Add a Vector Database Service to allow stages to read and write to VD…
…Bs (#1225) Closes #1177 ## By Submitting this PR I confirm: - I am familiar with the [Contributing Guidelines](https://github.com/nv-morpheus/Morpheus/blob/main/docs/source/developer_guide/contributing.md). - When the PR is ready for review, new or existing tests cover these changes. - When the PR is ready for review, the documentation is up to date with these changes. Authors: - Bhargav Suryadevara (https://github.com/bsuryadevara) Approvers: - Michael Demoret (https://github.com/mdemoret-nv) URL: #1225
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# Copyright (c) 2023, NVIDIA CORPORATION. | ||
# | ||
# 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. |
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# Copyright (c) 2023, NVIDIA CORPORATION. | ||
# | ||
# 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. | ||
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import typing | ||
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from pymilvus import Collection | ||
from pymilvus import DataType | ||
from pymilvus import MilvusClient as PyMilvusClient | ||
from pymilvus.orm.mutation import MutationResult | ||
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# Milvus data type mapping dictionary | ||
MILVUS_DATA_TYPE_MAP = { | ||
"int8": DataType.INT8, | ||
"int16": DataType.INT16, | ||
"int32": DataType.INT32, | ||
"int64": DataType.INT64, | ||
"bool": DataType.BOOL, | ||
"float": DataType.FLOAT, | ||
"double": DataType.DOUBLE, | ||
"binary_vector": DataType.BINARY_VECTOR, | ||
"float_vector": DataType.FLOAT_VECTOR, | ||
"string": DataType.STRING, | ||
"varchar": DataType.VARCHAR, | ||
"json": DataType.JSON, | ||
} | ||
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def handle_exceptions(func_name: str, error_message: str) -> typing.Callable: | ||
""" | ||
Decorator function to handle exceptions and log errors. | ||
Parameters | ||
---------- | ||
func_name : str | ||
Name of the func being decorated. | ||
error_message : str | ||
Error message to log in case of an exception. | ||
Returns | ||
------- | ||
typing.Callable | ||
Decorated function. | ||
""" | ||
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def decorator(func): | ||
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def wrapper(*args, **kwargs): | ||
try: | ||
return func(*args, **kwargs) | ||
except Exception as ex: | ||
raise RuntimeError(f"{error_message} - Failed to execute {func_name}") from ex | ||
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return wrapper | ||
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return decorator | ||
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class MilvusClient(PyMilvusClient): | ||
""" | ||
Extension of the `MilvusClient` class with custom functions. | ||
Parameters | ||
---------- | ||
uri : str | ||
URI for connecting to Milvus server. | ||
user : str | ||
User name for authentication. | ||
password : str | ||
Password for authentication. | ||
db_name : str | ||
Name of the Milvus database. | ||
token : str | ||
Token for authentication. | ||
**kwargs : dict[str, typing.Any] | ||
Additional keyword arguments for the MilvusClient constructor. | ||
""" | ||
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def __init__(self, uri: str, user: str, password: str, db_name: str, token: str, **kwargs: dict[str, typing.Any]): | ||
super().__init__(uri=uri, user=user, password=password, db_name=db_name, token=token, **kwargs) | ||
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@handle_exceptions("has_collection", "Error checking collection existence") | ||
def has_collection(self, collection_name: str) -> bool: | ||
""" | ||
Check if a collection exists in the database. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection to check. | ||
Returns | ||
------- | ||
bool | ||
True if the collection exists, False otherwise. | ||
""" | ||
conn = self._get_connection() | ||
return conn.has_collection(collection_name) | ||
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@handle_exceptions("create_partition", "Error creating partition") | ||
def create_partition(self, collection_name: str, partition_name: str, timeout: float = 1.0) -> None: | ||
""" | ||
Create a partition within a collection. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection. | ||
partition_name : str | ||
Name of the partition to create. | ||
timeout : float, optional | ||
Timeout for the operation in seconds (default is 1.0). | ||
""" | ||
conn = self._get_connection() | ||
conn.create_partition(collection_name=collection_name, partition_name=partition_name, timeout=timeout) | ||
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@handle_exceptions("load_collection", "Error loading collection") | ||
def load_collection(self, collection_name: str) -> None: | ||
""" | ||
Load a collection into memory. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection to load. | ||
""" | ||
conn = self._get_connection() | ||
conn.load_collection(collection_name=collection_name) | ||
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@handle_exceptions("release_collection", "Error releasing collection") | ||
def release_collection(self, collection_name: str) -> None: | ||
""" | ||
Release a loaded collection from memory. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection to release. | ||
""" | ||
conn = self._get_connection() | ||
conn.release_collection(collection_name=collection_name) | ||
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@handle_exceptions("upsert", "Error upserting collection entities") | ||
def upsert(self, collection_name: str, entities: list, **kwargs: dict[str, typing.Any]) -> MutationResult: | ||
""" | ||
Upsert entities into a collection. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection to upsert into. | ||
entities : list | ||
List of entities to upsert. | ||
**kwargs : dict[str, typing.Any] | ||
Additional keyword arguments for the upsert operation. | ||
Returns | ||
------- | ||
MutationResult | ||
Result of the upsert operation. | ||
""" | ||
conn = self._get_connection() | ||
return conn.upsert(collection_name=collection_name, entities=entities, **kwargs) | ||
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@handle_exceptions("delete_by_expr", "Error deleting collection entities") | ||
def delete_by_expr(self, collection_name: str, expression: str, **kwargs: dict[str, typing.Any]) -> MutationResult: | ||
""" | ||
Delete entities from a collection using an expression. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection to delete from. | ||
expression : str | ||
Deletion expression. | ||
**kwargs : dict[str, typing.Any] | ||
Additional keyword arguments for the delete operation. | ||
Returns | ||
------- | ||
MutationResult | ||
Returns result of delete operation. | ||
""" | ||
conn = self._get_connection() | ||
return conn.delete(collection_name=collection_name, expression=expression, **kwargs) | ||
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@handle_exceptions("has_partition", "Error checking partition existence") | ||
def has_partition(self, collection_name: str, partition_name: str) -> bool: | ||
""" | ||
Check if a partition exists within a collection. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection. | ||
partition_name : str | ||
Name of the partition to check. | ||
Returns | ||
------- | ||
bool | ||
True if the partition exists, False otherwise. | ||
""" | ||
conn = self._get_connection() | ||
return conn.has_partition(collection_name=collection_name, partition_name=partition_name) | ||
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@handle_exceptions("drop_partition", "Error dropping partition") | ||
def drop_partition(self, collection_name: str, partition_name: str) -> None: | ||
""" | ||
Drop a partition from a collection. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection. | ||
partition_name : str | ||
Name of the partition to drop. | ||
""" | ||
conn = self._get_connection() | ||
conn.drop_partition(collection_name=collection_name, partition_name=partition_name) | ||
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@handle_exceptions("drop_index", "Error dropping index") | ||
def drop_index(self, collection_name: str, field_name: str, index_name: str) -> None: | ||
""" | ||
Drop an index from a collection. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection. | ||
field_name : str | ||
Name of the field associated with the index. | ||
index_name : str | ||
Name of the index to drop. | ||
""" | ||
conn = self._get_connection() | ||
conn.drop_index(collection_name=collection_name, field_name=field_name, index_name=index_name) | ||
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@handle_exceptions("get_collection", "Error getting collection object") | ||
def get_collection(self, collection_name: str, **kwargs: dict[str, typing.Any]) -> Collection: | ||
""" | ||
Returns `Collection` object associated with the given collection name. | ||
Parameters | ||
---------- | ||
collection_name : str | ||
Name of the collection to delete from. | ||
**kwargs : dict[str, typing.Any] | ||
Additional keyword arguments to get Collection instance. | ||
Returns | ||
------- | ||
Collection | ||
Returns pymilvus Collection instance. | ||
""" | ||
collection = Collection(name=collection_name, using=self._using, **kwargs) | ||
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return collection |
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