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插入、上插和删除

本指南将指导你在集合中进行数据操作，包括插入、上载和删除。

开始之前

  • 您已安装了所选的 SDK。要安装 SDK，请参阅安装 SDK。

  • 您已创建了一个数据集。要创建数据集，请参阅管理数据集。

  • 要插入大量数据，建议使用数据导入。

概述

在 Milvus 数据集中，实体是一个数据集中可识别的单一实例。它代表特定类别中的一个独特成员，无论是图书馆中的一本书、基因组中的一个基因，还是任何其他可识别的实体。

集合中的实体共享一组共同的属性，称为模式，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限制。

要将实体成功插入到集合中，所提供的数据必须包含目标集合的所有模式定义字段。此外，只有启用了Dynamic Field，才能包含非模式定义的字段。有关详细信息，请参阅启用Dynamic Field。

准备工作

下面的代码片段重新利用了现有代码，以建立与 Milvus 集群的连接，并快速建立一个数据集。

对于准备工作，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。

对于准备工作，使用 MilvusClientV2连接到 Milvus 服务器 createCollection()以快速设置模式创建采集。

对于准备工作，使用 MilvusClient连接到 Milvus 服务器 createCollection()以快速设置模式创建集合。

Python Java Node.js
from pymilvus import MilvusClient

# 1. Set up a Milvus client
client = MilvusClient(
uri="http://localhost:19530"
)

# 2. Create a collection
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. Connect to Milvus server
ConnectConfig connectConfig = ConnectConfig.builder()
    .uri(CLUSTER_ENDPOINT)
    .build();

MilvusClientV2 client = new MilvusClientV2(connectConfig);

// 2. Create a collection in quick setup mode
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. Set up a Milvus Client
client = new MilvusClient({address});

// 2. Create a collection in quick setup mode
await client.createCollection({
    collection_name: "quick_setup",
    dimension: 5,
    metric_type: "IP"
});

注释

上述代码生成的集合只包含两个字段：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。插入数据时、

  • 无需在要插入的数据中包含id，因为主字段会在插入数据时自动递增。

  • 非模式定义的字段将以键值对的形式保存在名为$meta 的预留 JSON 字段中。

插入实体

要插入实体，需要将数据组织成一个字典列表，其中每个字典代表一个实体。每个字典都包含与目标集合中预定义字段和Dynamic Field相对应的键。

要在集合中插入实体，请使用 insert()方法。

要将实体插入集合，请使用 insert()方法。

要将实体插入集合，请使用 insert()方法。

Python Java Node.js
# 3. Insert some data
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)

# Output
#
# {
# "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. Insert some data
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));

// Output:
// {"insertCnt": 10}

// 3. Insert some data

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)

// Output
// 
// 10
//

插入分区

要将数据插入特定分区，可在插入请求中指定分区名称，如下所示：

Python Java Node.js
# 4. Insert some more data into a specific partition
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)

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

// 4. Insert some more data into a specific partition
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));

// Output:
// {"insertCnt": 10}

// 4. Insert some more data into a specific partition
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)

// Output
// 
// 10
//

输出结果是一个字典，其中包含受影响实体的统计数据。有关分区操作的详细信息，请参阅管理分区。

倒插实体

向上插入数据是更新和插入操作的组合。在 Milvus 中，upsert 操作会根据实体的主键是否已存在于集合中，执行插入或更新实体的数据级操作。具体来说

  • 如果实体的主键已存在于集合中，现有实体将被覆盖。

  • 如果集合中不存在主键，则会插入一个新实体。

  • Upsert 操作不会更新主键。
  • Upsert 操作不支持已启用autoID 的集合。
  • 如果计划在大规模数据摄取（如数百万向量）时使用upsert 操作而不是insert ，请注意这会导致 Milvus 数据节点的内存消耗过高。

要向上插入实体，请使用 upsert()方法。

要插入实体，请使用 upsert()方法。

要上载实体，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. Upsert some data
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));

// Output:
// {"upsertCnt": 10}

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

console.log(res.upsert_cnt)

// Output
// 
// 10
//

向上插入分区中的数据

要向上插入数据到特定分区，可在插入请求中指定分区名称，如下所示：

Python Java Node.js
# 6. Upsert data in partitions
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)

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

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

// 6. Upsert data in parition

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));

// Output:
// {"upsertCnt": 10}

// 6. Upsert data in partitions
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)

// Output
// 
// 10
//

输出结果是一个字典，其中包含受影响实体的统计数据。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，可以使用 delete().

如果不再需要某个实体，可以使用 delete().

如果不再需要实体，可以使用 delete().

Milvus 提供了两种方法来确定要删除的实体。

  • 通过过滤器删除实体。

    使用过滤表达式删除实体时，请确保已加载集合。否则，Milvus 将返回错误信息。

    Python JavaNode.js

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

print(res)

# Output
#
# {
# "delete_count": 3
# }

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


// 7. Delete entities

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));

// Output:
// {"deleteCnt": 3}

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

console.log(res.delete_cnt)

// Output
// 
// 3
//

  • 通过 ID 删除实体

    以下代码段演示了如何按 ID 从特定分区删除实体。如果不指定分区名称，该方法也同样有效。

    Python JavaNode.js

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

print(res)

# Output
#
# {
# "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));

// Output:
// {"deleteCnt": 2}

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

console.log(res.delete_cnt)

// Output
// 
// 2
//

    有关如何使用过滤表达式的详细信息，请参阅获取和标量查询。

  • 按分区名称删除实体

    如果想删除特定分区中的实体，可以在delete() 方法中使用partition_name 参数指定分区名称。下面的示例删除了partitionA 中颜色以blue 开头的实体。

    Python JavaNode.js

    res = client.delete(
collection_name='quick_setup',
partition_name='partitionA',
filter='color like "blue%"'
)

print("Entities deleted from partitionA: ", res['delete_count'])

# Output:
# Entities deleted from partitionA: 3

    deleteReq = DeleteReq.builder()
    .collectionName("quick_setup")
    .filter('color like "blue%"')
    .partitionName("partitionA")
    .build();

deleteResp = client.delete(deleteReq);

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

// Output:
// {"deleteCnt": 3}

    res = await client.delete({
collection_name: "quick_setup",
partition_name: "partitionA",
filter: 'color like "blue%"'
})

console.log("Entities deleted from partitionA: " + res.delete_cnt)

// Output:
// Entities deleted from partitionA: 3

翻译自DeepLogo

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