collection属于某个db。
api参考docs:
https://milvus.io/docs
使用attu创建collection。
使用pymilvus创建collection,并写入数据。
import uuid
import numpy as np
from pymilvus import (
connections,
FieldSchema, CollectionSchema, DataType,
Collection,
)
collection_name = "hello_milvus"
host = "192.168.230.71"
port = 19530
username = ""
password = ""
num_entities, dim = 1000, 128
total_num = 3000
def generate_uuids(number_of_uuids):
uuids = [str(uuid.uuid4()) for _ in range(number_of_uuids)]
return uuids
print("start connecting to Milvus")
connections.connect("default", host=host, port=port,user=username,password=password)
fields = [
FieldSchema(name="pk", dtype=DataType.INT64, is_primary=True, auto_id=False),
FieldSchema(name="random", dtype=DataType.DOUBLE),
FieldSchema(name="comment", dtype=DataType.VARCHAR, max_length=200),
FieldSchema(name="embeddings", dtype=DataType.FLOAT_VECTOR, dim=dim)
]
schema = CollectionSchema(fields, "hello_milvus is the simplest demo to introduce the APIs")
print("Create collection `hello_world`")
coll = Collection(collection_name, schema, consistency_level="Bounded",shards_num=1)
print("Start inserting entities")
rng = np.random.default_rng(seed=19530)
entities = [
[i for i in range(num_entities)],
rng.random(num_entities).tolist(),
generate_uuids(num_entities),
rng.random((num_entities, dim)),
]
insert_result = coll.insert(entities)
print("Start flush")
coll.flush()
print("done")
在向量类型字段上创建索引,然后才可以load进内存。
将索引加载进内存。
collection加载进内存后才可以预览和查看表数据。
随机生成一个向量进行搜索。
使用原始向量进行搜索。
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。