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Version: User Guides (Cloud)

Insert Entities

Entities in a collection are data records that share the same set of fields. Field values in every data record form an entity. This page introduces how to insert entities into a collection.

📘Notes
  • Duplicate handling: The standard insert operation does not check for duplicate primary keys. Inserting data with an existing primary key creates a new entity with the same key, leading to data duplication and potential application issues. To update existing entities or avoid duplicates, use the upsert operation instead. For more information, refer to Upsert Entities.

Overview

In Zilliz Cloud clusters, an Entity refers to data records in a Collection that share the same Schema, with the data in each field of a row constituting an Entity. Therefore, the Entities within the same Collection have the same attributes (such as field names, data types, and other constraints).

When inserting an Entity into a Collection, the Entity to be inserted can only be successfully added if it contains all the fields defined in the Schema. The inserted Entity will enter a Partition named _default in the order of insertion. Provided that a certain Partition exists, you can also insert Entities into that Partition by specifying the Partition name in the insertion request.

Zilliz Cloud also supports dynamic fields to maintain the scalability of the Collection. When the dynamic field is enabled, you can insert fields that are not defined in the Schema into the Collection. These fields and values will be stored as key-value pairs in a reserved field named $meta. For more information about dynamic fields, please refer to Dynamic Field.

Insert Entities into a Collection

Before inserting data, you need to organize your data into a list of dictionaries according to the Schema, with each dictionary representing an Entity and containing all the fields defined in the Schema. If the Collection has the dynamic field enabled, each dictionary can also include fields that are not defined in the Schema.

In this section, you will insert entities into a Collection created in the quick-setup manner. A Collection created in this manner has only two fields, named id and vector. Additionally, this Collection has the dynamic field enabled, so the Entities in the example code include a field called color that is not defined in the Schema.

from pymilvus import MilvusClient

client = MilvusClient(
uri="YOUR_CLUSTER_ENDPOINT",
token="YOUR_CLUSTER_TOKEN"
)

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]}

Insert Entities into a Partition

You can also insert entities into a specified partition. The following code snippets assume that you have a partition named PartitionA in your collection.

data=[
{"id": 10, "vector": [0.3580376395471989, -0.6023495712049978, 0.18414012509913835, -0.26286205330961354, 0.9029438446296592], "color": "pink_8682"},
{"id": 11, "vector": [0.19886812562848388, 0.06023560599112088, 0.6976963061752597, 0.2614474506242501, 0.838729485096104], "color": "red_7025"},
{"id": 12, "vector": [0.43742130801983836, -0.5597502546264526, 0.6457887650909682, 0.7894058910881185, 0.20785793220625592], "color": "orange_6781"},
{"id": 13, "vector": [0.3172005263489739, 0.9719044792798428, -0.36981146090600725, -0.4860894583077995, 0.95791889146345], "color": "pink_9298"},
{"id": 14, "vector": [0.4452349528804562, -0.8757026943054742, 0.8220779437047674, 0.46406290649483184, 0.30337481143159106], "color": "red_4794"},
{"id": 15, "vector": [0.985825131989184, -0.8144651566660419, 0.6299267002202009, 0.1206906911183383, -0.1446277761879955], "color": "yellow_4222"},
{"id": 16, "vector": [0.8371977790571115, -0.015764369584852833, -0.31062937026679327, -0.562666951622192, -0.8984947637863987], "color": "red_9392"},
{"id": 17, "vector": [-0.33445148015177995, -0.2567135004164067, 0.8987539745369246, 0.9402995886420709, 0.5378064918413052], "color": "grey_8510"},
{"id": 18, "vector": [0.39524717779832685, 0.4000257286739164, -0.5890507376891594, -0.8650502298996872, -0.6140360785406336], "color": "white_9381"},
{"id": 19, "vector": [0.5718280481994695, 0.24070317428066512, -0.3737913482606834, -0.06726932177492717, -0.6980531615588608], "color": "purple_4976"}
]

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

print(res)

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