# Copyright (C) 2019-2020 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 random from pymilvus import ( connections, list_collections, FieldSchema, CollectionSchema, DataType, Collection ) def hello_milvus(host="127.0.0.1"): import time # create connection connections.connect(host=host, port="19530") print(f"\nList collections...") print(list_collections()) # create collection dim = 128 default_fields = [ FieldSchema(name="count", dtype=DataType.INT64, is_primary=True), FieldSchema(name="random_value", dtype=DataType.DOUBLE), FieldSchema(name="float_vector", dtype=DataType.FLOAT_VECTOR, dim=dim) ] default_schema = CollectionSchema(fields=default_fields, description="test collection") print(f"\nCreate collection...") collection = Collection(name="hello_milvus", schema=default_schema) print(f"\nList collections...") print(list_collections()) # insert data nb = 3000 vectors = [[random.random() for _ in range(dim)] for _ in range(nb)] t0 = time.time() collection.insert( [ [i for i in range(nb)], [float(random.randrange(-20, -10)) for _ in range(nb)], vectors ] ) t1 = time.time() print(f"\nInsert {nb} vectors cost {t1 - t0} seconds") t0 = time.time() print(f"\nGet collection entities...") print(collection.num_entities) t1 = time.time() print(f"\nGet collection entities cost {t1 - t0} seconds") # create index and load table default_index = {"index_type": "IVF_FLAT", "params": {"nlist": 128}, "metric_type": "L2"} print(f"\nCreate index...") collection.create_index(field_name="float_vector", index_params=default_index) print(f"\nload collection...") t0 = time.time() collection.load() t1 = time.time() print(f"\nload collection cost {t1 - t0} seconds") # load and search topK = 5 search_params = {"metric_type": "L2", "params": {"nprobe": 10}} start_time = time.time() print(f"\nSearch...") # define output_fields of search result res = collection.search( vectors[-2:], "float_vector", search_params, topK, "count > 100", output_fields=["count", "random_value"] ) end_time = time.time() # show result for hits in res: for hit in hits: # Get value of the random value field for search result print(hit, hit.entity.get("random_value")) print("search latency = %.4fs" % (end_time - start_time)) #query expr = "count in [2,4,6,8]" output_fields = ["count", "random_value"] res = collection.query(expr, output_fields) sorted_res = sorted(res, key=lambda k: k['count']) for r in sorted_res: print(r) collection.release() import argparse parser = argparse.ArgumentParser(description='host ip') parser.add_argument('--host', type=str, default='127.0.0.1', help='host ip') args = parser.parse_args() # add time stamp import time print(f"\nStart time: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))}") hello_milvus(args.host)