삽입, 위로 올리기 및 삭제
이 가이드에서는 삽입, 위로 삽입 및 삭제를 포함한 컬렉션 내 데이터 조작 작업을 안내합니다.
시작하기 전에
원하는 SDK를 설치했습니다. SDK를 설치하려면 SDK 설치를 참조하세요.
컬렉션을 만들었습니다. 컬렉션을 만들려면 컬렉션 관리를 참조하세요.
대량의 데이터를 삽입하려면 데이터 가져오기를 사용하는 것이 좋습니다.
개요
Milvus 컬렉션의 컨텍스트 내에서 엔티티는 컬렉션 내에서 식별 가능한 단일 인스턴스입니다. 이는 도서관의 책, 게놈의 유전자 또는 기타 식별 가능한 개체 등 특정 클래스의 고유한 구성원을 나타냅니다.
컬렉션 내의 엔티티는 스키마라고 하는 공통 속성 집합을 공유하며, 필드 이름, 데이터 유형 및 기타 제약 조건을 포함하여 각 엔티티가 준수해야 하는 구조를 간략하게 설명합니다.
컬렉션에 엔티티를 성공적으로 삽입하려면 제공된 데이터에 대상 컬렉션의 모든 스키마 정의 필드가 포함되어야 합니다. 또한 동적 필드를 활성화한 경우에만 스키마에 정의되지 않은 필드도 포함할 수 있습니다. 자세한 내용은 동적 필드 활성화를 참조하세요.
준비
아래 코드 스니펫은 기존 코드를 재구성하여 Milvus 클러스터에 대한 연결을 설정하고 컬렉션을 빠르게 설정합니다.
준비를 위해 MilvusClient 를 사용하여 Milvus 서버에 연결하고 create_collection() 를 사용하여 빠른 설정 모드로 컬렉션을 생성합니다.
준비하려면 MilvusClientV2 을 사용하여 Milvus 서버에 연결하고 createCollection() 를 사용하여 빠른 설정 모드에서 컬렉션을 생성합니다.
준비하려면 MilvusClient 을 사용하여 Milvus 서버에 연결하고 createCollection() 를 사용하여 빠른 설정 모드에서 컬렉션을 생성합니다.
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 com.google.gson.Gson;
import com.google.gson.JsonObject;
import io.milvus.v2.client.MilvusClientV2;
import io.milvus.v2.client.ConnectConfig;
import io.milvus.v2.service.collection.request.CreateCollectionReq;
import io.milvus.v2.service.partition.request.CreatePartitionReq;
import io.milvus.v2.service.vector.request.*;
import io.milvus.v2.service.vector.response.*;
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"
});
참고
위 코드에서 생성된 컬렉션에는 id (기본 키)와 vector (벡터 필드)의 두 필드만 포함되며, auto_id 및 enable_dynamic_field 설정이 기본적으로 활성화되어 있습니다. 데이터를 삽입할 때
데이터가 삽입되면 기본 필드가 자동으로 증가하므로 삽입할 데이터에 ID를 포함할 필요가 없습니다.
스키마에 정의되지 않은 필드는 $meta라는 예약된 JSON 필드에 키-값 쌍으로 저장됩니다.
엔티티 삽입
엔티티를 삽입하려면 데이터를 사전 목록으로 구성해야 하며, 각 사전은 엔티티를 나타냅니다. 각 사전에는 대상 컬렉션의 사전 정의된 필드와 동적 필드에 해당하는 키가 모두 포함되어 있습니다.
컬렉션에 엔티티를 삽입하려면 insert() 메서드를 사용합니다.
컬렉션에 엔티티를 삽입하려면 insert() 메서드를 사용합니다.
컬렉션에 엔티티를 삽입하려면 insert() 메서드를 사용합니다.
# 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
# ]
# }
// 3. Insert some data
Gson gson = new Gson();
List<JsonObject> data = Arrays.asList(
gson.fromJson("{\"id\": 0, \"vector\": [0.3580376395471989f, -0.6023495712049978f, 0.18414012509913835f, -0.26286205330961354f, 0.9029438446296592f], \"color\": \"pink_8682\"}", JsonObject.class),
gson.fromJson("{\"id\": 1, \"vector\": [0.19886812562848388f, 0.06023560599112088f, 0.6976963061752597f, 0.2614474506242501f, 0.838729485096104f], \"color\": \"red_7025\"}", JsonObject.class),
gson.fromJson("{\"id\": 2, \"vector\": [0.43742130801983836f, -0.5597502546264526f, 0.6457887650909682f, 0.7894058910881185f, 0.20785793220625592f], \"color\": \"orange_6781\"}", JsonObject.class),
gson.fromJson("{\"id\": 3, \"vector\": [0.3172005263489739f, 0.9719044792798428f, -0.36981146090600725f, -0.4860894583077995f, 0.95791889146345f], \"color\": \"pink_9298\"}", JsonObject.class),
gson.fromJson("{\"id\": 4, \"vector\": [0.4452349528804562f, -0.8757026943054742f, 0.8220779437047674f, 0.46406290649483184f, 0.30337481143159106f], \"color\": \"red_4794\"}", JsonObject.class),
gson.fromJson("{\"id\": 5, \"vector\": [0.985825131989184f, -0.8144651566660419f, 0.6299267002202009f, 0.1206906911183383f, -0.1446277761879955f], \"color\": \"yellow_4222\"}", JsonObject.class),
gson.fromJson("{\"id\": 6, \"vector\": [0.8371977790571115f, -0.015764369584852833f, -0.31062937026679327f, -0.562666951622192f, -0.8984947637863987f], \"color\": \"red_9392\"}", JsonObject.class),
gson.fromJson("{\"id\": 7, \"vector\": [-0.33445148015177995f, -0.2567135004164067f, 0.8987539745369246f, 0.9402995886420709f, 0.5378064918413052f], \"color\": \"grey_8510\"}", JsonObject.class),
gson.fromJson("{\"id\": 8, \"vector\": [0.39524717779832685f, 0.4000257286739164f, -0.5890507376891594f, -0.8650502298996872f, -0.6140360785406336f], \"color\": \"white_9381\"}", JsonObject.class),
gson.fromJson("{\"id\": 9, \"vector\": [0.5718280481994695f, 0.24070317428066512f, -0.3737913482606834f, -0.06726932177492717f, -0.6980531615588608f], \"color\": \"purple_4976\"}", JsonObject.class)
);
InsertReq insertReq = InsertReq.builder()
.collectionName("quick_setup")
.data(data)
.build();
InsertResp insertResp = client.insert(insertReq);
System.out.println(insertResp.getInsertCnt());
// Output:
// 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
//
파티션에 삽입
특정 파티션에 데이터를 삽입하려면 다음과 같이 삽입 요청에 파티션 이름을 지정할 수 있습니다:
# 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
Gson gson = new Gson();
List<JsonObject> data = Arrays.asList(
gson.fromJson("{\"id\": 10, \"vector\": [-0.5570353903748935f, -0.8997887893201304f, -0.7123782431855732f, -0.6298990746450119f, 0.6699215060604258f], \"color\": \"red_1202\"}", JsonObject.class),
gson.fromJson("{\"id\": 11, \"vector\": [0.6319019033373907f, 0.6821488267878275f, 0.8552303045704168f, 0.36929791364943054f, -0.14152860714878068f], \"color\": \"blue_4150\"}", JsonObject.class),
gson.fromJson("{\"id\": 12, \"vector\": [0.9483947484855766f, -0.32294203351925344f, 0.9759290319978025f, 0.8262982148666174f, -0.8351194181285713f], \"color\": \"orange_4590\"}", JsonObject.class),
gson.fromJson("{\"id\": 13, \"vector\": [-0.5449109892498731f, 0.043511240563786524f, -0.25105249484790804f, -0.012030655265886425f, -0.0010987671273892108f], \"color\": \"pink_9619\"}", JsonObject.class),
gson.fromJson("{\"id\": 14, \"vector\": [0.6603339372951424f, -0.10866551787442225f, -0.9435597754324891f, 0.8230244263466688f, -0.7986720938400362f], \"color\": \"orange_4863\"}", JsonObject.class),
gson.fromJson("{\"id\": 15, \"vector\": [-0.8825129181091456f, -0.9204557711667729f, -0.935350065513425f, 0.5484069690287079f, 0.24448151140671204f], \"color\": \"orange_7984\"}", JsonObject.class),
gson.fromJson("{\"id\": 16, \"vector\": [0.6285586391568163f, 0.5389064528263487f, -0.3163366239905099f, 0.22036279378888013f, 0.15077052220816167f], \"color\": \"blue_9010\"}", JsonObject.class),
gson.fromJson("{\"id\": 17, \"vector\": [-0.20151825016059233f, -0.905239387635804f, 0.6749305353372479f, -0.7324272081377843f, -0.33007998971889263f], \"color\": \"blue_4521\"}", JsonObject.class),
gson.fromJson("{\"id\": 18, \"vector\": [0.2432286610792349f, 0.01785636564206139f, -0.651356982731391f, -0.35848148851027895f, -0.7387383128324057f], \"color\": \"orange_2529\"}", JsonObject.class),
gson.fromJson("{\"id\": 19, \"vector\": [0.055512329053363674f, 0.7100266349039421f, 0.4956956543575197f, 0.24541352586717702f, 0.4209030729923515f], \"color\": \"red_9437\"}", JsonObject.class)
);
CreatePartitionReq createPartitionReq = CreatePartitionReq.builder()
.collectionName("quick_setup")
.partitionName("partitionA")
.build();
client.createPartition(createPartitionReq);
InsertReq insertReq = InsertReq.builder()
.collectionName("quick_setup")
.data(data)
.partitionName("partitionA")
.build();
InsertResp insertResp = client.insert(insertReq);
System.out.println(insertResp.getInsertCnt());
// Output:
// 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
//
출력은 영향을 받는 엔티티에 대한 통계가 포함된 딕셔너리입니다. 파티션 작업에 대한 자세한 내용은 파티션 관리를 참조하세요.
엔티티 삽입
데이터 삽입은 업데이트와 삽입 작업의 조합입니다. Milvus에서 업서트 작업은 기본 키가 컬렉션에 이미 존재하는지 여부에 따라 엔터티를 삽입하거나 업데이트하는 데이터 수준 작업을 수행합니다. 구체적으로 설명하면 다음과 같습니다:
엔티티의 기본 키가 컬렉션에 이미 존재하면 기존 엔티티를 덮어씁니다.
기본 키가 컬렉션에 존재하지 않으면 새 엔터티가 삽입됩니다.
- 업서트 작업은 기본 키를 업데이트하지 않습니다.
- 대규모 데이터 수집(예: 수백만 개의 벡터)을 위해
insert대신upsert작업을 사용하려는 경우, 이 경우 Milvus 데이터 노드에서 높은 메모리 소비가 발생할 수 있다는 점에 유의하세요.
엔티티를 삽입하려면 upsert() 메서드를 사용합니다.
엔티티를 삽입하려면 upsert() 메서드를 사용합니다.
엔티티를 삽입하려면 upsert() 메서드를 사용합니다.
# 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
Gson gson = new Gson();
List<JsonObject> data = Arrays.asList(
gson.fromJson("{\"id\": 0, \"vector\": [-0.619954382375778f, 0.4479436794798608f, -0.17493894838751745f, -0.4248030059917294f, -0.8648452746018911f], \"color\": \"black_9898\"}", JsonObject.class),
gson.fromJson("{\"id\": 1, \"vector\": [0.4762662251462588f, -0.6942502138717026f, -0.4490002642657902f, -0.628696575798281f, 0.9660395877041965f], \"color\": \"red_7319\"}", JsonObject.class),
gson.fromJson("{\"id\": 2, \"vector\": [-0.8864122635045097f, 0.9260170474445351f, 0.801326976181461f, 0.6383943392381306f, 0.7563037341572827f], \"color\": \"white_6465\"}", JsonObject.class),
gson.fromJson("{\"id\": 3, \"vector\": [0.14594326235891586f, -0.3775407299900644f, -0.3765479013078812f, 0.20612075380355122f, 0.4902678929632145f], \"color\": \"orange_7580\"}", JsonObject.class),
gson.fromJson("{\"id\": 4, \"vector\": [0.4548498669607359f, -0.887610217681605f, 0.5655081329910452f, 0.19220509387904117f, 0.016513983433433577f], \"color\": \"red_3314\"}", JsonObject.class),
gson.fromJson("{\"id\": 5, \"vector\": [0.11755001847051827f, -0.7295149788999611f, 0.2608115847524266f, -0.1719167007897875f, 0.7417611743754855f], \"color\": \"black_9955\"}", JsonObject.class),
gson.fromJson("{\"id\": 6, \"vector\": [0.9363032158314308f, 0.030699901477745373f, 0.8365910312319647f, 0.7823840208444011f, 0.2625222076909237f], \"color\": \"yellow_2461\"}", JsonObject.class),
gson.fromJson("{\"id\": 7, \"vector\": [0.0754823906014721f, -0.6390658668265143f, 0.5610517334334937f, -0.8986261118798251f, 0.9372056764266794f], \"color\": \"white_5015\"}", JsonObject.class),
gson.fromJson("{\"id\": 8, \"vector\": [-0.3038434006935904f, 0.1279149203380523f, 0.503958664270957f, -0.2622661156746988f, 0.7407627307791929f], \"color\": \"purple_6414\"}", JsonObject.class),
gson.fromJson("{\"id\": 9, \"vector\": [-0.7125086947677588f, -0.8050968321012257f, -0.32608864121785786f, 0.3255654958645424f, 0.26227968923834233f], \"color\": \"brown_7231\"}", JsonObject.class)
);
UpsertReq upsertReq = UpsertReq.builder()
.collectionName("quick_setup")
.data(data)
.build();
UpsertResp upsertResp = client.upsert(upsertReq);
System.out.println(upsertResp.getUpsertCnt());
// Output:
// 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
//
파티션에 데이터 삽입
특정 파티션에 데이터를 삽입하려면 다음과 같이 삽입 요청에 파티션의 이름을 지정할 수 있습니다:
# 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
Gson gson = new Gson();
List<JsonObject> data = Arrays.asList(
gson.fromJson("{\"id\": 10, \"vector\": [0.06998888224297328f, 0.8582816610326578f, -0.9657938677934292f, 0.6527905683627726f, -0.8668460657158576f], \"color\": \"black_3651\"}", JsonObject.class),
gson.fromJson("{\"id\": 11, \"vector\": [0.6060703043917468f, -0.3765080534566074f, -0.7710758854987239f, 0.36993888322346136f, 0.5507513364206531f], \"color\": \"grey_2049\"}", JsonObject.class),
gson.fromJson("{\"id\": 12, \"vector\": [-0.9041813104515337f, -0.9610546012461163f, 0.20033003106083358f, 0.11842506351635174f, 0.8327356724591011f], \"color\": \"blue_6168\"}", JsonObject.class),
gson.fromJson("{\"id\": 13, \"vector\": [0.3202914977909075f, -0.7279137773695252f, -0.04747830871620273f, 0.8266053056909548f, 0.8277957187455489f], \"color\": \"blue_1672\"}", JsonObject.class),
gson.fromJson("{\"id\": 14, \"vector\": [0.2975811497890859f, 0.2946936202691086f, 0.5399463833894609f, 0.8385334966677529f, -0.4450543984655133f], \"color\": \"pink_1601\"}", JsonObject.class),
gson.fromJson("{\"id\": 15, \"vector\": [-0.04697464305600074f, -0.08509022265734134f, 0.9067184632552001f, -0.2281912685064822f, -0.9747503428652762f], \"color\": \"yellow_9925\"}", JsonObject.class),
gson.fromJson("{\"id\": 16, \"vector\": [-0.9363075919673911f, -0.8153981031085669f, 0.7943039120490902f, -0.2093886809842529f, 0.0771191335807897f], \"color\": \"orange_9872\"}", JsonObject.class),
gson.fromJson("{\"id\": 17, \"vector\": [-0.050451522820639916f, 0.18931572752321935f, 0.7522886192190488f, -0.9071793089474034f, 0.6032647330692296f], \"color\": \"red_6450\"}", JsonObject.class),
gson.fromJson("{\"id\": 18, \"vector\": [-0.9181544231141592f, 0.6700755998126806f, -0.014174674636136642f, 0.6325780463623432f, -0.49662222164032976f], \"color\": \"purple_7392\"}", JsonObject.class),
gson.fromJson("{\"id\": 19, \"vector\": [0.11426945899602536f, 0.6089190684002581f, -0.5842735738352236f, 0.057050610092692855f, -0.035163433018196244f], \"color\": \"pink_4996\"}", JsonObject.class)
);
UpsertReq upsertReq = UpsertReq.builder()
.collectionName("quick_setup")
.partitionName("partitionA")
.data(data)
.build();
UpsertResp upsertResp = client.upsert(upsertReq);
System.out.println(upsertResp.getUpsertCnt());
// Output:
// 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
//
출력은 영향을 받는 엔티티에 대한 통계가 포함된 딕셔너리입니다. 파티션 작업에 대한 자세한 내용은 파티션 관리를 참조하세요.
엔터티 삭제
엔티티가 더 이상 필요하지 않은 경우 컬렉션에서 엔티티를 삭제하려면 delete().
엔티티가 더 이상 필요하지 않은 경우 다음을 사용하여 컬렉션에서 삭제할 수 있습니다. delete().
엔티티가 더 이상 필요하지 않은 경우 다음을 사용하여 컬렉션에서 삭제할 수 있습니다. delete().
Milvus는 삭제할 엔티티를 식별할 수 있는 두 가지 방법을 제공합니다.
필터로 엔티티를 삭제합니다.
필터 표현식을 사용하여 엔티티를 삭제할 때는 컬렉션이 로드되었는지 확인하세요. 그렇지 않으면 Milvus에서 오류를 반환합니다.
# 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(deleteResp.getDeleteCnt()); // Output: // 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 //ID별로 엔티티 삭제하기.
다음 코드 조각은 특정 파티션에서 ID별로 엔티티를 삭제하는 방법을 보여줍니다. 파티션 이름을 지정하지 않은 상태에서도 작동합니다.
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(deleteResp.getDeleteCnt()); // Output: // 2res = await client.delete({ collection_name: "quick_setup", ids: [18, 19], partition_name: "partitionA" }) console.log(res.delete_cnt) // Output // // 2 //필터 표현식을 사용하는 방법에 대한 자세한 내용은 가져오기 및 스칼라 쿼리를 참조하세요.
파티션 이름으로 엔터티 삭제하기.
특정 파티션에서 엔티티를 삭제하려면
delete()메서드에서partition_name파라미터로 파티션 이름을 지정하면 됩니다. 다음 예제는partitionA에서blue으로 시작하는 색상을 가진 엔티티를 삭제합니다.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: 3deleteReq = DeleteReq.builder() .collectionName("quick_setup") .filter('color like "blue%"') .partitionName("partitionA") .build(); deleteResp = client.delete(deleteReq); System.out.println(deleteResp.getDeleteCnt()); // Output: // 3res = 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
