About Milvus
Get Started
Concepts
User Guide
Models
Milvus Migration
Administration Guide
Tools
Integrations
Tutorials
FAQs
API Reference

Insert, Upsert & Delete

This guide walks you through the data manipulation operations within a collection, including insertion, upsertion, and deletion.

Before you start

You have installed the SDK of your choice. To install an SDK, refer to Install SDKs.
You have created a collection. To create a collection, refer to Manage Collections.
To insert a large volume of data, you are advised to use Data Import.

Overview

An entity, within the context of Milvus collections, is a singular, identifiable instance within a collection. It represents a distinct member of a particular class, be it a book in a library, a gene in a genome, or any other identifiable entity.

Entities within a collection share a common set of attributes, termed schema, outlining the structure that each entity must adhere to, including field names, data types, and any other constraints.

Successful insertion of entities into a collection requires that the provided data should contain all the schema-defined fields of the target collection. Additionally, you can also include non-schema-defined fields only if you have enabled the dynamic field. For details, refer to Enable Dynamic Field.

Preparations

The code snippet below repurposes the existing code to establish a connection to a Milvus cluster and quickly set up a collection.

For preparations, use MilvusClient to connect to the Milvus server and create_collection() to create a collection in a quick-setup mode.

For preparations, use MilvusClientV2 to connect to the Milvus server and createCollection() to create a collection in a quick-setup mode.

For preparations, use MilvusClient to connect to the Milvus server and createCollection() to create a collection in a quick-setup mode.

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"
});

notes

The collection generated in the above code contains only two fields: id (as the primary key) and vector (as the vector field), with auto_id and enable_dynamic_field settings enabled by default. When inserting data,

You do not need to include id in the data to be inserted, because the primary field automatically increments as data is inserted.
Non-schema-defined fields will be saved as key-value pairs in a reserved JSON field named $meta.

Insert entities

To insert entities, you need to organize the data into a list of dictionaries, where each dictionary represents an entity. Each dictionary contains the keys corresponding to both pre-defined and dynamic fields in the target collection.

To insert entities into a collection, use the insert() method.

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
//

Insert into partitions

To insert data into a specific partition, you can specify the name of the partition in the insert request as follows:

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
//

The output is a dictionary containing the statistics on the affected entities. For details on partition operations, refer to Manage Partitions.

Upsert entities

Upserting data is a combination of update and insert operations. In Milvus, an upsert operation performs a data-level action to either insert or update an entity based on whether its primary key already exists in a collection. Specifically:

If the primary key of the entity already exists in the collection, the existing entity will be overwritten.
If the primary key does not exist in the collection, a new entity will be inserted.

Upsert operations will not update the primary keys.
Upsert operations does not support collections with autoID enabled.
If you plan to use the upsert operation instead of insert for large-scale data ingestion (e.g. millions of vectors), be aware that this can lead to high memory consumption on Milvus data nodes.

To upsert entities, use the upsert() method.

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
//

Upsert data in partitions

To upsert data into a specific partition, you can specify the name of the partition in the insert request as follows:

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
//

The output is a dictionary containing the statistics on the affected entities. For details on partition operations, refer to Manage Partitions.

Delete entities

If an entity is no longer needed, you can delete it from the collection by using delete().

Milvus offers two ways for you to identify the entities to delete.

Delete entities by filter.

When using filter expressions to delete entities, ensure the collection has been loaded. Otherwise, Milvus will return an error.

Python Java Node.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
//

Delete entities by IDs.

The following snippets demonstrate how to delete entities by IDs from a specific partition. It also works if you leave the partition name unspecified.

Python Java Node.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
//

For details on how to use filter expressions, refer to Get & Scalar Query.

Insert, Upsert & Delete
Before you start
Overview
Preparations
Insert entities
Upsert entities
Delete entities

Feedback

Was this page helpful?

Insert, Upsert & Delete

Before you start

Overview

Preparations

Insert entities

Insert into partitions

Upsert entities

Upsert data in partitions

Delete entities

Table of contents

Feedback