目录

安装milvus客户端

创建milvus数据表

数据表插入向量

查询数据表

查向量数量

封装成类

python3.6版本

安装milvus客户端

pip install pymilvus==1.1.0 -i https://pypi.tuna.tsinghua.edu.cn/simple

创建milvus数据表

from milvus import Milvus, MetricType  milvus = Milvus(host='milvus机器ip', port='19530')  params = {'collection_name':'test01',           'dimension':512,           'index_file_size':1024,           'metric_type':MetricType.IP}  status = milvus.create_collection(params) print(status)

Status(code=0, message='Create collection successfully!')

数据表插入向量

模拟10条512维的特征向量

import random  vectors = [[random.random() for _ in range(512)] for _ in range(10)] print(len(vectors),len(vectors[0]))

10 512

模拟20条向量入库

from milvus import Milvus, MetricType  milvus = Milvus(host='milvus机器ip', port='19530')  params = {'collection_name':'test01',           'dimension':512,           'index_file_size':1024,           'metric_type':MetricType.IP}  status = milvus.create_collection(params) print(status)  vectors = [[1.0*i for _ in range(512)] for i in range(20)] print(vectors[0][0],vectors[-1][0])  status, ids = milvus.insert(collection_name='test01', records=vectors) print(status,ids)  milvus.flush(['test01']) milvus.close()

Status(code=0, message='Create collection successfully!') 0.0 9.0 Status(code=0, message='Add vectors successfully!') [168846, ..., 1688460]

查询数据表

from milvus import Milvus, MetricType from pprint import pprint  milvus = Milvus(host='milvus机器ip', port='19530')  status,info = milvus.get_collection_stats('test01') print(status,info)  print('-'*20) pprint(info)

Status(code=0, message='Success') {'partitions': [{'row_count': 20, 'segments': [{'data_size': 41120, 'index_name': 'IDMAP', 'name': '168846070', 'row_count': 20}], 'tag': '_default'}], 'row_count': 20} -------------------- {'partitions': [{'row_count': 20,                  'segments': [{'data_size': 41120,                                'index_name': 'IDMAP',                                'name': '1688460770',                                'row_count': 20}],                  'tag': '_default'}],  'row_count': 20} 

查向量数量

from milvus import Milvus, MetricType  milvus = Milvus(host='milvus机器ip', port='19530')  status,n = milvus.count_entities('test01') print(status,n)

Status(code=0, message='Success!') 20

封装成类

class MilvusVector:     def __init__(self):         self.milvus = Milvus(host='milvus机器ip', port='19530')         self.db_name = 'test01'         params = {'collection_name': self.db_name, 'dimension': 512, 'index_file_size': 1024, 'metric_type': MetricType.IP}         _, bool = self.milvus.has_collection(self.db_name)         if bool == True:             self.milvus.drop_collection(collection_name=self.db_name)             self.milvus.create_collection(params)             print('delete test01 ---> create test01')         else:             self.milvus.create_collection(params)             print('create test01')      def vectorNum(self):         status, n = self.milvus.count_entities(self.db_name)         return n      def close(self):         self.milvus.close()      def insert(self,vector):         status, ids = self.milvus.insert(collection_name=self.db_name,records=vector)         self.milvus.flush([self.db_name])         return ids[0]      def search(self,vector):         status, ips = self.milvus.search(collection_name=self.db_name, query_records=vector, top_k=1)         id, ip = ips.id_array[0][0], ips.distance_array[0][0]         return [id,ip]