Bulkinsert writer

Signed-off-by: yhmo <[email protected]>

examples/example_bulkwriter.py

@@ -0,0 +1,200 @@
+# Copyright (C) 2019-2023 Zilliz. All rights reserved.
+#
+# 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.
+
+import os
+import json
+import random
+import threading
+
+import logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("example_bulkwriter")
+
+from pymilvus import (
+    connections,
+    FieldSchema, CollectionSchema, DataType,
+    Collection,
+    utility,
+    LocalBulkWriter,
+    RemoteBulkWriter,
+    BulkFileType,
+    bulk_insert,
+    get_job_progress,
+    list_jobs,
+)
+
+# minio
+MINIO_ADDRESS = "0.0.0.0:9000"
+MINIO_SECRET_KEY = "minioadmin"
+MINIO_ACCESS_KEY = "minioadmin"
+
+# milvus
+HOST = '127.0.0.1'
+PORT = '19530'
+
+COLLECTION_NAME = "test_abc"
+DIM = 256
+
+def create_connection():
+    print(f"\nCreate connection...")
+    connections.connect(host=HOST, port=PORT)
+    print(f"\nConnected")
+
+
+def build_collection():
+    if utility.has_collection(COLLECTION_NAME):
+        utility.drop_collection(COLLECTION_NAME)
+
+    field1 = FieldSchema(name="id", dtype=DataType.INT64, auto_id=True, is_primary=True)
+    field2 = FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=DIM)
+    field3 = FieldSchema(name="desc", dtype=DataType.VARCHAR, max_length=100)
+    schema = CollectionSchema(fields=[field1, field2, field3])
+    collection = Collection(name=COLLECTION_NAME, schema=schema)
+    print("Collection created")
+    return collection.schema
+
+def test_local_writer_json(schema: CollectionSchema):
+    local_writer = LocalBulkWriter(schema=schema,
+                                   local_path="/tmp/bulk_data",
+                                   segment_size=4*1024*1024,
+                                   file_type=BulkFileType.JSON_RB,
+                                   )
+    for i in range(10):
+        local_writer.append({"id": i, "vector": [random.random() for _ in range(DIM)], "desc": f"description_{i}"})
+
+    local_writer.commit()
+    print("test local writer done!")
+    print(local_writer.data_path)
+    return local_writer.data_path
+
+def test_local_writer_npy(schema: CollectionSchema):
+    local_writer = LocalBulkWriter(schema=schema, local_path="/tmp/bulk_data", segment_size=4*1024*1024)
+    for i in range(10000):
+        local_writer.append({"id": i, "vector": [random.random() for _ in range(DIM)], "desc": f"description_{i}"})
+
+    local_writer.commit()
+    print("test local writer done!")
+    print(local_writer.data_path)
+    return local_writer.data_path
+
+
+def _append_row(writer: LocalBulkWriter, begin: int, end: int):
+    for i in range(begin, end):
+        writer.append({"id": i, "vector": [random.random() for _ in range(DIM)], "desc": f"description_{i}"})
+
+def test_parallel_append(schema: CollectionSchema):
+    local_writer = LocalBulkWriter(schema=schema,
+                                   local_path="/tmp/bulk_data",
+                                   segment_size=1000 * 1024 * 1024,
+                                   file_type=BulkFileType.JSON_RB,
+                                   )
+    threads = []
+    thread_count = 100
+    rows_per_thread = 1000
+    for k in range(thread_count):
+        x = threading.Thread(target=_append_row, args=(local_writer, k*rows_per_thread, (k+1)*rows_per_thread,))
+        threads.append(x)
+        x.start()
+        print(f"Thread '{x.name}' started")
+
+    for th in threads:
+        th.join()
+
+    local_writer.commit()
+    print(f"Append finished, {thread_count*rows_per_thread} rows")
+    file_path = os.path.join(local_writer.data_path, "1.json")
+    with open(file_path, 'r') as file:
+        data = json.load(file)
+
+    print("Verify the output content...")
+    rows = data['rows']
+    assert len(rows) == thread_count*rows_per_thread
+    for i in range(len(rows)):
+        row = rows[i]
+        assert row['desc'] == f"description_{row['id']}"
+
+
+def test_remote_writer(schema: CollectionSchema):
+    remote_writer = RemoteBulkWriter(schema=schema,
+                                     remote_path="bulk_data",
+                                     local_path="/tmp/bulk_data",
+                                     connect_param=RemoteBulkWriter.ConnectParam(
+                                         endpoint=MINIO_ADDRESS,
+                                         access_key=MINIO_ACCESS_KEY,
+                                         secret_key=MINIO_SECRET_KEY,
+                                         bucket_name="a-bucket",
+                                     ),
+                                     segment_size=50 * 1024 * 1024,
+                                     )
+
+    for i in range(10000):
+        if i % 1000 == 0:
+            logger.info(f"{i} rows has been append to remote writer")
+        remote_writer.append({"id": i, "vector": [random.random() for _ in range(DIM)], "desc": f"description_{i}"})
+
+    remote_writer.commit()
+    print("test remote writer done!")
+    print(remote_writer.data_path)
+    return remote_writer.data_path
+
+
+def test_cloud_bulkinsert():
+    host = "_your_cloud_url_"
+    cluster_id = "_your_cloud_instance_"
+    request_url = f"https://{host}/v1/vector/collections/import"
+
+    print(f"===================== import files to cloud vectordb ====================")
+    object_url = "_your_object_storage_service_url_"
+    object_url_access_key = "_your_object_storage_service_access_key_"
+    object_url_secret_key = "_your_object_storage_service_secret_key_"
+    resp = bulk_insert(
+        url=request_url,
+        object_url=object_url,
+        access_key=object_url_access_key,
+        secret_key=object_url_secret_key,
+        cluster_id=cluster_id,
+        collection_name=COLLECTION_NAME,
+    )
+    print(resp)
+
+    print(f"===================== get import job progress ====================")
+    job_id = resp['jobId']
+    request_url = f"https://{host}/v1/vector/collections/import/get"
+    resp = get_job_progress(
+        url=request_url,
+        job_id=job_id,
+        cluster_id=cluster_id,
+    )
+    print(resp)
+
+    print(f"===================== list import jobs ====================")
+    request_url = f"https://{host}/v1/vector/collections/import/list"
+    resp = list_jobs(
+        url=request_url,
+        cluster_id=cluster_id,
+        page_size=10,
+        current_page=1,
+    )
+    print(resp)
+
+
+if __name__ == '__main__':
+    create_connection()
+    schema = build_collection()
+
+    test_local_writer_json(schema)
+    test_local_writer_npy(schema)
+    test_remote_writer(schema)
+    test_parallel_append(schema)
+
+    # test_cloud_bulkinsert()
+

pymilvus/__init__.py

@@ -10,6 +10,22 @@
 # or implied. See the License for the specific language governing permissions and limitations under
 # the License.
 
+from .bulk_writer.bulk_import import (
+    bulk_insert,
+    get_job_progress,
+    list_jobs,
+)
+
+# bulk writer
+from .bulk_writer.constants import (
+    BulkFileType,
+)
+from .bulk_writer.local_bulk_writer import (
+    LocalBulkWriter,
+)
+from .bulk_writer.remote_bulk_writer import (
+    RemoteBulkWriter,
+)
 from .client import __version__
 from .client.prepare import Prepare
 from .client.stub import Milvus
@@ -124,4 +140,10 @@
     "ResourceGroupInfo",
     "Connections",
     "IndexType",
+    "BulkFileType",
+    "LocalBulkWriter",
+    "RemoteBulkWriter",
+    "bulk_insert",
+    "get_job_progress",
+    "list_jobs",
 ]

pymilvus/bulk_writer/buffer.py

@@ -0,0 +1,148 @@
+# Copyright (C) 2019-2023 Zilliz. All rights reserved.
+#
+# 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.
+
+import json
+import logging
+from pathlib import Path
+
+import numpy as np
+
+from pymilvus.exceptions import MilvusException
+from pymilvus.orm.schema import CollectionSchema
+
+from .constants import (
+    DYNAMIC_FIELD_NAME,
+    BulkFileType,
+)
+
+logger = logging.getLogger("bulk_buffer")
+logger.setLevel(logging.DEBUG)
+
+
+class Buffer:
+    def __init__(
+        self,
+        schema: CollectionSchema,
+        file_type: BulkFileType = BulkFileType.NPY,
+    ):
+        self._buffer = {}
+        self._file_type = file_type
+        for field in schema.fields:
+            self._buffer[field.name] = []
+
+        if len(self._buffer) == 0:
+            self._throw("Illegal collection schema: fields list is empty")
+
+        # dynamic field, internal name is '$meta'
+        if schema.enable_dynamic_field:
+            self._buffer[DYNAMIC_FIELD_NAME] = []
+
+    @property
+    def row_count(self) -> int:
+        if len(self._buffer) == 0:
+            return 0
+
+        for k in self._buffer:
+            return len(self._buffer[k])
+        return None
+
+    def _throw(self, msg: str):
+        logger.error(msg)
+        raise MilvusException(message=msg)
+
+    def append_row(self, row: dict):
+        dynamic_values = {}
+        if DYNAMIC_FIELD_NAME in row and not isinstance(row[DYNAMIC_FIELD_NAME], dict):
+            self._throw(f"Dynamic field '{DYNAMIC_FIELD_NAME}' value should be JSON format")
+
+        for k in row:
+            if k == DYNAMIC_FIELD_NAME:
+                dynamic_values.update(row[k])
+                continue
+
+            if k not in self._buffer:
+                dynamic_values[k] = row[k]
+            else:
+                self._buffer[k].append(row[k])
+
+        if DYNAMIC_FIELD_NAME in self._buffer:
+            self._buffer[DYNAMIC_FIELD_NAME].append(json.dumps(dynamic_values))
+
+    def persist(self, local_path: str) -> list:
+        # verify row count of fields are equal
+        row_count = -1
+        for k in self._buffer:
+            if row_count < 0:
+                row_count = len(self._buffer[k])
+            elif row_count != len(self._buffer[k]):
+                self._throw(
+                    "Column `{}` row count {} doesn't equal to the first column row count {}".format(
+                        k, len(self._buffer[k]), row_count
+                    )
+                )
+
+        # output files
+        if self._file_type == BulkFileType.NPY:
+            return self._persist_npy(local_path)
+        if self._file_type == BulkFileType.JSON_RB:
+            return self._persist_json_rows(local_path)
+
+        self._throw(f"Unsupported file tpye: {self._file_type}")
+        return []
+
+    def _persist_npy(self, local_path: str):
+        Path(local_path).mkdir(exist_ok=True)
+
+        file_list = []
+        for k in self._buffer:
+            full_file_name = Path(local_path).joinpath(k + ".npy")
+            file_list.append(full_file_name)
+            try:
+                np.save(full_file_name, self._buffer[k])
+            except Exception as e:
+                self._throw(f"Failed to persist column-based file {full_file_name}, error: {e}")
+
+            logger.info(f"Successfully persist column-based file {full_file_name}")
+
+        if len(file_list) != len(self._buffer):
+            logger.error("Some of fields were not persisted successfully, abort the files")
+            for f in file_list:
+                Path(f).unlink()
+            Path(local_path).rmdir()
+            file_list.clear()
+            self._throw("Some of fields were not persisted successfully, abort the files")
+
+        return file_list
+
+    def _persist_json_rows(self, local_path: str):
+        rows = []
+        row_count = len(next(iter(self._buffer.values())))
+        row_index = 0
+        while row_index < row_count:
+            row = {}
+            for k, v in self._buffer.items():
+                row[k] = v[row_index]
+            rows.append(row)
+            row_index = row_index + 1
+
+        data = {
+            "rows": rows,
+        }
+        file_path = Path(local_path + ".json")
+        try:
+            with file_path.open("w") as json_file:
+                json.dump(data, json_file, indent=2)
+        except Exception as e:
+            self._throw(f"Failed to persist row-based file {file_path}, error: {e}")
+
+        logger.info(f"Successfully persist row-based file {file_path}")
+        return [file_path]