插入、更新与删除

本指南将带您了解集合内的数据操作，包括插入、更新和删除。

开始之前

您已安装所选 SDK。要安装 SDK，请参阅安装 SDK。
您已创建一个集合。要创建集合，请参阅管理集合。
若要插入大量数据，建议使用数据导入。

概述

在 Milvus 集合的上下文中，实体是指集合内的单个可识别实例。它代表特定类别的一个独特成员，无论是图书馆中的一本书，基因组中的一个基因，还是其他任何可识别实体。

集合内的实体共享一组称为模式的属性，概述了每个实体必须遵守的结构，包括字段名称、数据类型和任何其他约束。

成功将实体插入集合需要提供的数据应包含目标集合的所有模式定义字段。此外，如果启用了动态字段，还可以包含非模式定义字段。有关详细信息，请参阅启用动态字段。

准备工作

下面的代码片段重新利用现有代码，以建立与 Milvus 集群的连接并快速设置集合。

在准备工作中，使用 MilvusClient 连接到 Milvus 服务器，并使用 create_collection() 在快速设置模式下创建集合。

在准备工作中，使用 MilvusClientV2 连接到 Milvus 服务器，并使用 createCollection() 在快速设置模式下创建集合。

在准备工作中，使用 MilvusClient 连接到 Milvus 服务器，并使用 createCollection() 在快速设置模式下创建集合。

Python Java Node.js

from pymilvus import MilvusClient

# 1. 设置一个 Milvus 客户端
client = MilvusClient(
    uri="http://localhost:19530"
)

# 2. 创建一个集合
client.create_collection(
    collection_name="quick_setup",
    dimension=5,
    metric_type="IP"
)

import io.milvus.v2.client.ConnectConfig;
import io.milvus.v2.client.MilvusClientV2;
import io.milvus.v2.service.collection.request.CreateCollectionReq;

String CLUSTER_ENDPOINT = "http://localhost:19530";

// 1. 连接到 Milvus 服务器
ConnectConfig connectConfig = ConnectConfig.builder()
    .uri(CLUSTER_ENDPOINT)
    .build();

MilvusClientV2 client = new MilvusClientV2(connectConfig);

// 2. 在快速设置模式下创建一个集合
CreateCollectionReq quickSetupReq = CreateCollectionReq.builder()
    .collectionName("quick_setup")
    .dimension(5)
    .metricType("IP")
    .build();

client.createCollection(quickSetupReq);

const { MilvusClient, DataType, sleep } = require("@zilliz/milvus2-sdk-node")

const address = "http://localhost:19530"

// 1. 设置一个 Milvus 客户端
client = new MilvusClient({address});

// 2. 在快速设置模式下创建一个集合
await client.createCollection({
    collection_name: "quick_setup",
    dimension: 5,
    metric_type: "IP"
});  

注意

上述代码中生成的集合仅包含两个字段：id（作为主键）和vector（作为向量字段），默认启用auto id和enable dynamic_field设置。在插入数据时，

您无需在要插入的数据中包含id，因为主字段会随着数据插入而自动递增。
未在模式中定义的字段将保存为键值对，存储在名为$meta的保留 JSON 字段中。

插入实体

要插入实体，您需要将数据组织成字典列表，其中每个字典表示一个实体。每个字典包含与目标集合中预定义字段和动态字段对应的键。

要将实体插入集合，请使用insert()方法。

Python Java Node.js

```python
# 3. 插入一些数据
data=[
    {"id": 0, "vector": [0.3580376395471989, -0.6023495712049978, 0.18414012509913835, -0.26286205330961354, 0.9029438446296592], "color": "pink_8682"},
    {"id": 1, "vector": [0.19886812562848388, 0.06023560599112088, 0.6976963061752597, 0.2614474506242501, 0.838729485096104], "color": "red_7025"},
    {"id": 2, "vector": [0.43742130801983836, -0.5597502546264526, 0.6457887650909682, 0.7894058910881185, 0.20785793220625592], "color": "orange_6781"},
    {"id": 3, "vector": [0.3172005263489739, 0.9719044792798428, -0.36981146090600725, -0.4860894583077995, 0.95791889146345], "color": "pink_9298"},
    {"id": 4, "vector": [0.4452349528804562, -0.8757026943054742, 0.8220779437047674, 0.46406290649483184, 0.30337481143159106], "color": "red_4794"},
    {"id": 5, "vector": [0.985825131989184, -0.8144651566660419, 0.6299267002202009, 0.1206906911183383, -0.1446277761879955], "color": "yellow_4222"},
    {"id": 6, "vector": [0.8371977790571115, -0.015764369584852833, -0.31062937026679327, -0.562666951622192, -0.8984947637863987], "color": "red_9392"},
    {"id": 7, "vector": [-0.33445148015177995, -0.2567135004164067, 0.8987539745369246, 0.9402995886420709, 0.5378064918413052], "color": "grey_8510"},
    {"id": 8, "vector": [0.39524717779832685, 0.4000257286739164, -0.5890507376891594, -0.8650502298996872, -0.6140360785406336], "color": "white_9381"},
    {"id": 9, "vector": [0.5718280481994695, 0.24070317428066512, -0.3737913482606834, -0.06726932177492717, -0.6980531615588608], "color": "purple_4976"}
]

res = client.insert(
    collection_name="quick_setup",
    data=data
)

print(res)

# 输出
#
# {
#     "insert_count": 10,
#     "ids": [
#         0,
#         1,
#         2,
#         3,
#         4,
#         5,
#         6,
#         7,
#         8,
#         9
#     ]
# }

import java.util.Arrays;
import java.util.List;
import java.util.Map;
import io.milvus.v2.service.vector.request.InsertReq;
import io.milvus.v2.service.vector.response.InsertResp;

// 3. 插入一些数据
List<JSONObject> data = Arrays.asList(
    new JSONObject(Map.of("id", 0L, "vector", Arrays.asList(0.3580376395471989f, -0.6023495712049978f, 0.18414012509913835f, -0.26286205330961354f, 0.9029438446296592f), "color", "pink_8682")),
    new JSONObject(Map.of("id", 1L, "vector", Arrays.asList(0.19886812562848388f, 0.06023560599112088f, 0.6976963061752597f, 0.2614474506242501f, 0.838729485096104f), "color", "red_7025")),
    new JSONObject(Map.of("id", 2L, "vector", Arrays.asList(0.43742130801983836f, -0.5597502546264526f, 0.6457887650909682f, 0.7894058910881185f, 0.20785793220625592f), "color", "orange_6781")),
    new JSONObject(Map.of("id", 3L, "vector", Arrays.asList(0.3172005263489739f, 0.9719044792798428f, -0.36981146090600725f, -0.4860894583077995f, 0.95791889146345f), "color", "pink_9298")),
    new JSONObject(Map.of("id", 4L, "vector", Arrays.asList(0.4452349528804562f, -0.8757026943054742f, 0.8220779437047674f, 0.46406290649483184f, 0.30337481143159106f), "color", "red_4794")),
    new JSONObject(Map.of("id", 5L, "vector", Arrays.asList(0.985825131989184f, -0.8144651566660419f, 0.6299267002202009f, 0.1206906911183383f, -0.1446277761879955f), "color", "yellow_4222")),
    new JSONObject(Map.of("id", 6L, "vector", Arrays.asList(0.8371977790571115f, -0.015764369584852833f, -0.31062937026679327f, -0.562666951622192f, -0.8984947637863987f), "color", "red_9392")),
    new JSONObject(Map.of("id", 7L, "vector", Arrays.asList(-0.33445148015177995f, -0.2567135004164067f, 0.8987539745369246f, 0.9402995886420709f, 0.5378064918413052f), "color", "grey_8510")),
    new JSONObject(Map.of("id", 8L, "vector", Arrays.asList(0.39524717779832685f, 0.4000257286739164f, -0.5890507376891594f, -0.8650502298996872f, -0.6140360785406336f), "color", "white_9381")),
    new JSONObject(Map.of("id", 9L, "vector", Arrays.asList(0.5718280481994695f, 0.24070317428066512f, -0.3737913482606834f, -0.06726932177492717f, -0.6980531615588608f), "color", "purple_4976"))
);

InsertReq insertReq = InsertReq.builder()
    .collectionName("quick_setup")
    .data(data)
    .build();

InsertResp insertResp = client.insert(insertReq);

System.out.println(JSONObject.toJSON(insertResp));

// 输出:
// {"insertCnt": 10}

// 3. 插入一些数据

var data = [
    {id: 0, vector: [0.3580376395471989, -0.6023495712049978, 0.18414012509913835, -0.26286205330961354, 0.9029438446296592], color: "pink_8682"},
    {id: 1, vector: [0.19886812562848388, 0.06023560599112088, 0.6976963061752597, 0.2614474506242501, 0.838729485096104], color: "red_7025"},
    {id: 2, vector: [0.43742130801983836, -0.5597502546264526, 0.6457887650909682, 0.7894058910881185, 0.20785793220625592], color: "orange_6781"},
    {id: 3, vector: [0.3172005263489739, 0.9719044792798428, -0.36981146090600725, -0.4860894583077995, 0.95791889146345], color: "pink_9298"},
    {id: 4, vector: [0.4452349528804562, -0.8757026943054742, 0.8220779437047674, 0.46406290649483184, 0.30337481143159106], color: "red_4794"},
    {id: 5, vector: [0.985825131989184, -0.8144651566660419, 0.6299267002202009, 0.1206906911183383, -0.1446277761879955], color: "yellow_4222"},
    {id: 6, vector: [0.8371977790571115, -0.015764369584852833, -0.31062937026679327, -0.562666951622192, -0.8984947637863987], color: "red_9392"},
    {id: 7, vector: [-0.33445148015177995, -0.2567135004164067, 0.8987539745369246, 0.9402995886420709, 0.5378064918413052], color: "grey_8510"},
    {id: 8, vector: [0.39524717779832685, 0.4000257286739164, -0.5890507376891594, -0.8650502298996872, -0.6140360785406336], color: "white_9381"},
    {id: 9, vector: [0.5718280481994695, 0.24070317428066512, -0.3737913482606834, -0.06726932177492717, -0.6980531615588608], color: "purple_4976"}        
]

var res = await client.insert({
    collection_name: "quick_setup",
    data: data,
})

console.log(res.insert_cnt)

// 输出
// 
// 10
// 

插入到分区

要将数据插入到特定分区，您可以在插入请求中指定分区的名称，如下所示：

Python Java Node.js

# 4. 插入更多数据到特定分区
data=[
    {"id": 10, "vector": [-0.5570353903748935, -0.8997887893201304, -0.7123782431855732, -0.6298990746450119, 0.6699215060604258], "color": "red_1202"},
    {"id": 11, "vector": [0.6319019033373907, 0.6821488267878275, 0.8552303045704168, 0.36929791364943054, -0.14152860714878068], "color": "blue_4150"},
    {"id": 12, "vector": [0.9483947484855766, -0.32294203351925344, 0.9759290319978025, 0.8262982148666174, -0.8351194181285713], "color": "orange_4590"},
    {"id": 13, "vector": [-0.5449109892498731, 0.043511240563786524, -0.25105249484790804, -0.012030655265886425, -0.0010987671273892108], "color": "pink_9619"},
    {"id": 14, "vector": [0.6603339372951424, -0.10866551787442225, -0.9435597754324891, 0.8230244263466688, -0.7986720938400362], "color": "orange_4863"},
    {"id": 15, "vector": [-0.8825129181091456, -0.9204557711667729, -0.935350065513425, 0.5484069690287079, 0.24448151140671204], "color": "orange_7984"},
    {"id": 16, "vector": [0.6285586391568163, 0.5389064528263487, -0.3163366239905099, 0.22036279378888013, 0.15077052220816167], "color": "blue_9010"},
    {"id": 17, "vector": [-0.20151825016059233, -0.905239387635804, 0.6749305353372479, -0.7324272081377843, -0.33007998971889263], "color": "blue_4521"},
    {"id": 18, "vector": [0.2432286610792349, 0.01785636564206139, -0.651356982731391, -0.35848148851027895, -0.7387383128324057], "color": "orange_2529"},
    {"id": 19, "vector": [0.055512329053363674, 0.7100266349039421, 0.4956956543575197, 0.24541352586717702, 0.4209030729923515], "color": "red_9437"}
]

client.create_partition(
    collection_name="quick_setup",
    partition_name="partitionA"
)

res = client.insert(
    collection_name="quick_setup",
    data=data,
    partition_name="partitionA"
)

print(res)

# 输出
#
# {
#     "insert_count": 10,
#     "ids": [
#         10,
#         11,
#         12,
#         13,
#         14,
#         15,
#         16,
#         17,
#         18,
#         19
#     ]
# }

// 4. 插入更多数据到特定分区
data = Arrays.asList(
    new JSONObject(Map.of("id", 10L, "vector", Arrays.asList(-0.5570353903748935f, -0.8997887893201304f, -0.7123782431855732f, -0.6298990746450119f, 0.6699215060604258f), "color", "red_1202")),
    new JSONObject(Map.of("id", 11L, "vector", Arrays.asList(0.6319019033373907f, 0.6821488267878275f, 0.8552303045704168f, 0.36929791364943054f, -0.14152860714878068f), "color", "blue_4150")),
    new JSONObject(Map.of("id", 12L, "vector", Arrays.asList(0.9483947484855766f, -0.32294203351925344f, 0.9759290319978025f, 0.8262982148666174f, -0.8351194181285713f), "color", "orange_4590")),
    new JSONObject(Map.of("id", 13L, "vector", Arrays.asList(-0.5449109892498731f, 0.043511240563786524f, -0.25105249484790804f, -0.012030655265886425f, -0.0010987671273892108f), "color", "pink_9619")),
    new JSONObject(Map.of("id", 14L, "vector", Arrays.asList(0.6603339372951424f, -0.10866551787442225f, -0.9435597754324891f, 0.8230244263466688f, -0.7986720938400362f), "color", "orange_4863")),
    new JSONObject(Map.of("id", 15L, "vector", Arrays.asList(-0.8825129181091456f, -0.9204557711667729f, -0.935350065513425f, 0.5484069690287079f, 0.24448151140671204f), "color", "orange_7984")),
    new JSONObject(Map.of("id", 16L, "vector", Arrays.asList(0.6285586391568163f, 0.5389064528263487f, -0.3163366239905099f, 0.22036279378888013f, 0.15077052220816167f), "color", "blue_9010")),
    new JSONObject(Map.of("id", 17L, "vector", Arrays.asList(-0.20151825016059233f, -0.905239387635804f, 0.6749305353372479f, -0.7324272081377843f, -0.33007998971889263f), "color", "blue_4521")),
    new JSONObject(Map.of("id", 18L, "vector", Arrays.asList(0.2432286610792349f, 0.01785636564206139f, -0.651356982731391f, -0.35848148851027895f, -0.7387383128324057f), "color", "orange_2529")),
    new JSONObject(Map.of("id", 19L, "vector", Arrays.asList(0.055512329053363674f, 0.7100266349039421f, 0.4956956543575197f, 0.24541352586717702f, 0.4209030729923515f), "color", "red_9437"))
);

CreatePartitionReq createPartitionReq = CreatePartitionReq.builder()
    .collectionName("quick_setup")
    .partitionName("partitionA")
    .build();

client.createPartition(createPartitionReq);

insertReq = InsertReq.builder()
    .collectionName("quick_setup")
    .data(data)
    .partitionName("partitionA")
    .build();

insertResp = client.insert(insertReq);

System.out.println(JSONObject.toJSON(insertResp));

// 输出:
// {"insertCnt": 10}

// 4. 将更多数据插入特定分区
data = [
    {id: 10, vector: [-0.5570353903748935, -0.8997887893201304, -0.7123782431855732, -0.6298990746450119, 0.6699215060604258], color: "red_1202"},
    {id: 11, vector: [0.6319019033373907, 0.6821488267878275, 0.8552303045704168, 0.36929791364943054, -0.14152860714878068], color: "blue_4150"},
    {id: 12, vector: [0.9483947484855766, -0.32294203351925344, 0.9759290319978025, 0.8262982148666174, -0.8351194181285713], color: "orange_4590"},
    {id: 13, vector: [-0.5449109892498731, 0.043511240563786524, -0.25105249484790804, -0.012030655265886425, -0.0010987671273892108], color: "pink_9619"},
    {id: 14, vector: [0.6603339372951424, -0.10866551787442225, -0.9435597754324891, 0.8230244263466688, -0.7986720938400362], color: "orange_4863"},
    {id: 15, vector: [-0.8825129181091456, -0.9204557711667729, -0.935350065513425, 0.5484069690287079, 0.24448151140671204], color: "orange_7984"},
    {id: 16, vector: [0.6285586391568163, 0.5389064528263487, -0.3163366239905099, 0.22036279378888013, 0.15077052220816167], color: "blue_9010"},
    {id: 17, vector: [-0.20151825016059233, -0.905239387635804, 0.6749305353372479, -0.7324272081377843, -0.33007998971889263], color: "blue_4521"},
    {id: 18, vector: [0.2432286610792349, 0.01785636564206139, -0.651356982731391, -0.35848148851027895, -0.7387383128324057], color: "orange_2529"},
    {id: 19, vector: [0.055512329053363674, 0.7100266349039421, 0.4956956543575197, 0.24541352586717702, 0.4209030729923515], color: "red_9437"}
]

await client.createPartition({
    collection_name: "quick_setup",
    partition_name: "partitionA"
})

res = await client.insert({
    collection_name: "quick_setup",
    data: data,
    partition_name: "partitionA"
})

console.log(res.insert_cnt)

// 输出
// 
// 10
// 

输出是一个包含受影响实体统计信息的字典。有关分区操作的详细信息，请参阅管理分区。

更新实体

更新数据是更新和插入操作的组合。在 Milvus 中，更新操作执行数据级操作，根据实体的主键是否已存在于集合中，执行插入或更新操作。具体来说：

如果实体的主键已存在于集合中，则现有实体将被覆盖。
如果主键在集合中不存在，则将插入新实体。

要更新实体，请使用upsert()方法。

Python Java Node.js

# 5. Upsert some data
data=[
    {"id": 0, "vector": [-0.619954382375778, 0.4479436794798608, -0.17493894838751745, -0.4248030059917294, -0.8648452746018911], "color": "black_9898"},
    {"id": 1, "vector": [0.4762662251462588, -0.6942502138717026, -0.4490002642657902, -0.628696575798281, 0.9660395877041965], "color": "red_7319"},
    {"id": 2, "vector": [-0.8864122635045097, 0.9260170474445351, 0.801326976181461, 0.6383943392381306, 0.7563037341572827], "color": "white_6465"},
    {"id": 3, "vector": [0.14594326235891586, -0.3775407299900644, -0.3765479013078812, 0.20612075380355122, 0.4902678929632145], "color": "orange_7580"},
    {"id": 4, "vector": [0.4548498669607359, -0.887610217681605, 0.5655081329910452, 0.19220509387904117, 0.016513983433433577], "color": "red_3314"},
    {"id": 5, "vector": [0.11755001847051827, -0.7295149788999611, 0.2608115847524266, -0.1719167007897875, 0.7417611743754855], "color": "black_9955"},
    {"id": 6, "vector": [0.9363032158314308, 0.030699901477745373, 0.8365910312319647, 0.7823840208444011, 0.2625222076909237], "color": "yellow_2461"},
    {"id": 7, "vector": [0.0754823906014721, -0.6390658668265143, 0.5610517334334937, -0.8986261118798251, 0.9372056764266794], "color": "white_5015"},
    {"id": 8, "vector": [-0.3038434006935904, 0.1279149203380523, 0.503958664270957, -0.2622661156746988, 0.7407627307791929], "color": "purple_6414"},
    {"id": 9, "vector": [-0.7125086947677588, -0.8050968321012257, -0.32608864121785786, 0.3255654958645424, 0.26227968923834233], "color": "brown_7231"}
]

res = client.upsert(
    collection_name='quick_setup',
    data=data
)

print(res)

# Output
#
# {
#     "upsert_count": 10
# }

// 5. 插入一些数据
data = Arrays.asList(
    new JSONObject(Map.of("id", 0L, "vector", Arrays.asList(-0.619954382375778f, 0.4479436794798608f, -0.17493894838751745f, -0.4248030059917294f, -0.8648452746018911f), "color", "black_9898")),
    new JSONObject(Map.of("id", 1L, "vector", Arrays.asList(0.4762662251462588f, -0.6942502138717026f, -0.4490002642657902f, -0.628696575798281f, 0.9660395877041965f), "color", "red_7319")),
    new JSONObject(Map.of("id", 2L, "vector", Arrays.asList(-0.8864122635045097f, 0.9260170474445351f, 0.801326976181461f, 0.6383943392381306f, 0.7563037341572827f), "color", "white_6465")),
    new JSONObject(Map.of("id", 3L, "vector", Arrays.asList(0.14594326235891586f, -0.3775407299900644f, -0.3765479013078812f, 0.20612075380355122f, 0.4902678929632145f), "color", "orange_7580")),
    new JSONObject(Map.of("id", 4L, "vector", Arrays.asList(0.4548498669607359f, -0.887610217681605f, 0.5655081329910452f, 0.19220509387904117f, 0.016513983433433577f), "color", "red_3314")),
    new JSONObject(Map.of("id", 5L, "vector", Arrays.asList(0.11755001847051827f, -0.7295149788999611f, 0.2608115847524266f, -0.1719167007897875f, 0.7417611743754855f), "color", "black_9955")),
    new JSONObject(Map.of("id", 6L, "vector", Arrays.asList(0.9363032158314308f, 0.030699901477745373f, 0.8365910312319647f, 0.7823840208444011f, 0.2625222076909237f), "color", "yellow_2461")),
    new JSONObject(Map.of("id", 7L, "vector", Arrays.asList(0.0754823906014721f, -0.6390658668265143f, 0.5610517334334937f, -0.8986261118798251f, 0.9372056764266794f), "color", "white_5015")),
    new JSONObject(Map.of("id", 8L, "vector", Arrays.asList(-0.3038434006935904f, 0.1279149203380523f, 0.503958664270957f, -0.2622661156746988f, 0.7407627307791929f), "color", "purple_6414")),
    new JSONObject(Map.of("id", 9L, "vector", Arrays.asList(-0.7125086947677588f, -0.8050968321012257f, -0.32608864121785786f, 0.3255654958645424f, 0.26227968923834233f), "color", "brown_7231"))
);

UpsertReq upsertReq = UpsertReq.builder()
    .collectionName("quick_setup")
    .data(data)
    .build();

UpsertResp upsertResp = client.upsert(upsertReq);

System.out.println(JSONObject.toJSON(upsertResp));

// 输出:
// {"upsertCnt": 10}

// 5. 更新或插入一些数据
data = [
    {id: 0, vector: [-0.619954382375778, 0.4479436794798608, -0.17493894838751745, -0.4248030059917294, -0.8648452746018911], color: "black_9898"},
    {id: 1, vector: [0.4762662251462588, -0.6942502138717026, -0.4490002642657902, -0.628696575798281, 0.9660395877041965], color: "red_7319"},
    {id: 2, vector: [-0.8864122635045097, 0.9260170474445351, 0.801326976181461, 0.6383943392381306, 0.7563037341572827], color: "white_6465"},
    {id: 3, vector: [0.14594326235891586, -0.3775407299900644, -0.3765479013078812, 0.20612075380355122, 0.4902678929632145], color: "orange_7580"},
    {id: 4, vector: [0.4548498669607359, -0.887610217681605, 0.5655081329910452, 0.19220509387904117, 0.016513983433433577], color: "red_3314"},
    {id: 5, vector: [0.11755001847051827, -0.7295149788999611, 0.2608115847524266, -0.1719167007897875, 0.7417611743754855], color: "black_9955"},
    {id: 6, vector: [0.9363032158314308, 0.030699901477745373, 0.8365910312319647, 0.7823840208444011, 0.2625222076909237], color: "yellow_2461"},
    {id: 7, vector: [0.0754823906014721, -0.6390658668265143, 0.5610517334334937, -0.8986261118798251, 0.9372056764266794], color: "white_5015"},
    {id: 8, vector: [-0.3038434006935904, 0.1279149203380523, 0.503958664270957, -0.2622661156746988, 0.7407627307791929], color: "purple_6414"},
    {id: 9, vector: [-0.7125086947677588, -0.8050968321012257, -0.32608864121785786, 0.3255654958645424, 0.26227968923834233], color: "brown_7231"}
]

res = await client.upsert({
    collection_name: "quick_setup",
    data: data,
})

console.log(res.upsert_cnt)

// 输出
// 
// 10
// 

在分区中更新数据

要将数据更新到特定分区，您可以在插入请求中指定分区的名称，如下所示：

Python Java Node.js

```python
# 6. 分区中的数据更新
data=[
    {"id": 10, "vector": [0.06998888224297328, 0.8582816610326578, -0.9657938677934292, 0.6527905683627726, -0.8668460657158576], "color": "black_3651"},
    {"id": 11, "vector": [0.6060703043917468, -0.3765080534566074, -0.7710758854987239, 0.36993888322346136, 0.5507513364206531], "color": "grey_2049"},
    {"id": 12, "vector": [-0.9041813104515337, -0.9610546012461163, 0.20033003106083358, 0.11842506351635174, 0.8327356724591011], "color": "blue_6168"},
    {"id": 13, "vector": [0.3202914977909075, -0.7279137773695252, -0.04747830871620273, 0.8266053056909548, 0.8277957187455489], "color": "blue_1672"},
    {"id": 14, "vector": [0.2975811497890859, 0.2946936202691086, 0.5399463833894609, 0.8385334966677529, -0.4450543984655133], "color": "pink_1601"},
    {"id": 15, "vector": [-0.04697464305600074, -0.08509022265734134, 0.9067184632552001, -0.2281912685064822, -0.9747503428652762], "color": "yellow_9925"},
    {"id": 16, "vector": [-0.9363075919673911, -0.8153981031085669, 0.7943039120490902, -0.2093886809842529, 0.0771191335807897], "color": "orange_9872"},
    {"id": 17, "vector": [-0.050451522820639916, 0.18931572752321935, 0.7522886192190488, -0.9071793089474034, 0.6032647330692296], "color": "red_6450"},
    {"id": 18, "vector": [-0.9181544231141592, 0.6700755998126806, -0.014174674636136642, 0.6325780463623432, -0.49662222164032976], "color": "purple_7392"},
    {"id": 19, "vector": [0.11426945899602536, 0.6089190684002581, -0.5842735738352236, 0.057050610092692855, -0.035163433018196244], "color": "pink_4996"}
]

res = client.upsert(
    collection_name="quick_setup",
    data=data,
    partition_name="partitionA"
)

print(res)

# 输出
#
# {
#     "upsert_count": 10
# }

import io.milvus.v2.service.vector.request.UpsertReq;
import io.milvus.v2.service.vector.response.UpsertResp;

// 6. 在分区中更新数据

data = Arrays.asList(
    new JSONObject(Map.of("id", 10L, "vector", Arrays.asList(0.06998888224297328f, 0.8582816610326578f, -0.9657938677934292f, 0.6527905683627726f, -0.8668460657158576f), "color", "black_3651")),
    new JSONObject(Map.of("id", 11L, "vector", Arrays.asList(0.6060703043917468f, -0.3765080534566074f, -0.7710758854987239f, 0.36993888322346136f, 0.5507513364206531f), "color", "grey_2049")),
    new JSONObject(Map.of("id", 12L, "vector", Arrays.asList(-0.9041813104515337f, -0.9610546012461163f, 0.20033003106083358f, 0.11842506351635174f, 0.8327356724591011f), "color", "blue_6168")),
    new JSONObject(Map.of("id", 13L, "vector", Arrays.asList(0.3202914977909075f, -0.7279137773695252f, -0.04747830871620273f, 0.8266053056909548f, 0.8277957187455489f), "color", "blue_1672")),
    new JSONObject(Map.of("id", 14L, "vector", Arrays.asList(0.2975811497890859f, 0.2946936202691086f, 0.5399463833894609f, 0.8385334966677529f, -0.4450543984655133f), "color", "pink_1601")),
    new JSONObject(Map.of("id", 15L, "vector", Arrays.asList(-0.04697464305600074f, -0.08509022265734134f, 0.9067184632552001f, -0.2281912685064822f, -0.9747503428652762f), "color", "yellow_9925")),
    new JSONObject(Map.of("id", 16L, "vector", Arrays.asList(-0.9363075919673911f, -0.8153981031085669f, 0.7943039120490902f, -0.2093886809842529f, 0.0771191335807897f), "color", "orange_9872")),
    new JSONObject(Map.of("id", 17L, "vector", Arrays.asList(-0.050451522820639916f, 0.18931572752321935f, 0.7522886192190488f, -0.9071793089474034f, 0.6032647330692296f), "color", "red_6450")),
    new JSONObject(Map.of("id", 18L, "vector", Arrays.asList(-0.9181544231141592f, 0.6700755998126806f, -0.014174674636136642f, 0.6325780463623432f, -0.49662222164032976f), "color", "purple_7392")),
    new JSONObject(Map.of("id", 19L, "vector", Arrays.asList(0.11426945899602536f, 0.6089190684002581f, -0.5842735738352236f, 0.057050610092692855f, -0.035163433018196244f), "color", "pink_4996"))
);

upsertReq = UpsertReq.builder()
    .collectionName("quick_setup")
    .data(data)
    .partitionName("partitionA")
    .build();

upsertResp = client.upsert(upsertReq);

System.out.println(JSONObject.toJSON(upsertResp));

// 输出:
// {"upsertCnt": 10}

// 6. 分区中的数据更新
data = [
    {id: 10, vector: [0.06998888224297328, 0.8582816610326578, -0.9657938677934292, 0.6527905683627726, -0.8668460657158576], color: "black_3651"},
    {id: 11, vector: [0.6060703043917468, -0.3765080534566074, -0.7710758854987239, 0.36993888322346136, 0.5507513364206531], color: "grey_2049"},
    {id: 12, vector: [-0.9041813104515337, -0.9610546012461163, 0.20033003106083358, 0.11842506351635174, 0.8327356724591011], color: "blue_6168"},
    {id: 13, vector: [0.3202914977909075, -0.7279137773695252, -0.04747830871620273, 0.8266053056909548, 0.8277957187455489], color: "blue_1672"},
    {id: 14, vector: [0.2975811497890859, 0.2946936202691086, 0.5399463833894609, 0.8385334966677529, -0.4450543984655133], color: "pink_1601"},
    {id: 15, vector: [-0.04697464305600074, -0.08509022265734134, 0.9067184632552001, -0.2281912685064822, -0.9747503428652762], color: "yellow_9925"},
    {id: 16, vector: [-0.9363075919673911, -0.8153981031085669, 0.7943039120490902, -0.2093886809842529, 0.0771191335807897], color: "orange_9872"},
    {id: 17, vector: [-0.050451522820639916, 0.18931572752321935, 0.7522886192190488, -0.9071793089474034, 0.6032647330692296], color: "red_6450"},
    {id: 18, vector: [-0.9181544231141592, 0.6700755998126806, -0.014174674636136642, 0.6325780463623432, -0.49662222164032976], color: "purple_7392"},
    {id: 19, vector: [0.11426945899602536, 0.6089190684002581, -0.5842735738352236, 0.057050610092692855, -0.035163433018196244], color: "pink_4996"}
]

res = await client.upsert({
    collection_name: "quick_setup",
    data: data,
    partition_name: "partitionA"
})

console.log(res.upsert_cnt)

// 输出
// 
// 10
// 

输出是一个包含受影响实体统计信息的字典。有关分区操作的详细信息，请参阅管理分区。

删除实体

如果不再需要某个实体，您可以使用delete()从集合中删除它。

Milvus提供了两种方法来标识要删除的实体。

通过过滤器删除实体

Python Java Node.js

# 7. 删除实体
res = client.delete(
    collection_name="quick_setup",
    filter="id in [4,5,6]"
)

print(res)

# 输出
#
# {
#     "delete_count": 3
# }

import io.milvus.v2.service.vector.request.DeleteReq;
import io.milvus.v2.service.vector.response.DeleteResp;


// 7. 删除实体

DeleteReq deleteReq = DeleteReq.builder()
    .collectionName("quick_setup")
    .filter("id in [4, 5, 6]")
    .build();

DeleteResp deleteResp = client.delete(deleteReq);

System.out.println(JSONObject.toJSON(deleteResp));

// 输出:
// {"deleteCnt": 3}

// 7. 删除实体
res = await client.delete({
    collection_name: "quick_setup",
    filter: "id in [4,5,6]"
})

console.log(res.delete_cnt)

// 输出
// 
// 3
// 

通过ID删除实体

以下代码片段演示了如何通过ID从特定分区删除实体。如果不指定分区名称，也可以使用。

Python Java Node.js

res = client.delete(
    collection_name="quick_setup",
    ids=[18, 19],
    partition_name="partitionA"
)

print(res)

# 输出
#
# {
#     "delete_count": 2
# }

deleteReq = DeleteReq.builder()
    .collectionName("quick_setup")
    .ids(Arrays.asList(18L, 19L))
    .partitionName("partitionA")
    .build();

deleteResp = client.delete(deleteReq);

System.out.println(JSONObject.toJSON(deleteResp));

// 输出:
// {"deleteCnt": 2}

res = await client.delete({
    collection_name: "quick_setup",
    ids: [18, 19],

partition_name: "partitionA"
})

console.log(res.delete_cnt)

// 输出
// 
// 2
// 

有关如何使用过滤表达式的详细信息，请参阅Get & Scalar Query。

插入、更新与删除

开始之前​

概述​

准备工作​

插入实体​

插入到分区​

更新实体​

在分区中更新数据​

删除实体​

开始之前

概述

准备工作

插入实体

插入到分区

更新实体

在分区中更新数据

删除实体