Importing users individually

After you complete Creating a schema and a dataset to create a Users dataset, you can individually import one or more new users into the dataset. Individually importing users allows you to keep your Users dataset current with small batch imports as your catalog grows. You can import up to 10 users at a time. If you have a large amount of new users, we recommend that you first import data in bulk and then import user data individually as necessary. See Importing bulk data into Amazon Personalize with a dataset import job.

You can use the Amazon Personalize console, the AWS Command Line Interface (AWS CLI), or AWS SDKs to import users. If you import a user with the same userId as a user that's already in your Users dataset, Amazon Personalize replaces the user with the new one. You can import up to 10 users at a time.

For information about how Amazon Personalize updates filters for new records and how new records influence recommendations, see Importing individual records into an Amazon Personalize dataset.

Importing users individually (console)

You can import up to 10 users at a time. This procedure assumes you have already created a Users dataset. For information about creating datasets, see Creating a schema and a dataset.

Importing users individually (AWS CLI)

Add one or more users to your Users dataset with the PutUsers operation. You can import up to 10 users with a single PutUsers call. This section assumes that you have already created an Users dataset. For information about creating datasets, see Creating a schema and a dataset.

Use the following put-users command to add one or more users with the AWS CLI. Replace dataset arn with the Amazon Resource Name (ARN) of your dataset and user Id with the ID of the user. If an user with the same userId is already in your Users dataset, Amazon Personalize replaces it with the new one.

For properties, for each field in your Users dataset, replace the propertyName with the field name from your schema in camel case. For example, GENDER would be gender and MEMBERSHIP_TYPE would be membershipType. Replace user data with the data for the user. For categorical string data, to include multiple categories for a single property, separate each category with a pipe (|). For example \"Premium Class|Legacy Member\".

aws personalize-events put-users \
  --dataset-arn dataset arn \
  --users '[{
      "userId": "user Id", 
      "properties": "{\"propertyName\": "\user data\"}" 
    }, 
    {
      "userId": "user Id", 
      "properties": "{\"propertyName\": "\user data\"}" 
    }]'

Importing users individually (AWS SDKs)

Add one or more users to your Users dataset with the PutUsers operation. If a user with the same userId is already in your Users dataset, Amazon Personalize replaces it with the new one. You can import up to 10 users with a single PutUsers call. This section assumes that you have already created a Users dataset. For information about creating datasets, see Creating a schema and a dataset.

The following code shows how to add one or more users to your Users dataset. For each property name parameter, pass the field name from your schema in camel case. For example, GENDER would be gender and MEMBERSHIP_TYPE would be membershipType. For each property value parameter, pass the data for the user.

For categorical string data, to include multiple categories for a single property separate each category with a pipe (|). For example "Premium class|Legacy Member".

SDK for Python (Boto3)

import boto3

personalize_events = boto3.client(service_name='personalize-events')

personalize_events.put_users(
    datasetArn = 'dataset arn',
    users = [{
      'userId': 'user ID',
      'properties': "{\"propertyName\": \"user data\"}"   
      },
      {
      'userId': 'user ID',
      'properties': "{\"propertyName\": \"user data\"}"   
      }]
)

SDK for Java 2.x

public static int putUsers(PersonalizeEventsClient personalizeEventsClient,
                         String datasetArn,
                         String user1Id,
                         String user1PropertyName,
                         String user1PropertyValue,
                         String user2Id,
                         String user2PropertyName,
                         String user2PropertyValue) {

    int responseCode = 0;
    ArrayList<User> users = new ArrayList<>();

    try {
        User user1 = User.builder()
          .userId(user1Id)
          .properties(String.format("{\"%1$s\": \"%2$s\"}", user1PropertyName, user1PropertyValue))
          .build();

        users.add(user1);

        User user2 = User.builder()
          .userId(user2Id)
          .properties(String.format("{\"%1$s\": \"%2$s\"}", user2PropertyName, user2PropertyValue))
          .build();

        users.add(user2);

        PutUsersRequest putUsersRequest = PutUsersRequest.builder()
          .datasetArn(datasetArn)
          .build();

        responseCode = personalizeEventsClient.putUsers(putUsersRequest).sdkHttpResponse().statusCode();
        System.out.println("Response code: " + responseCode);
        return responseCode;

    } catch (PersonalizeEventsException e) {
        System.out.println(e.awsErrorDetails().errorMessage());
    }
    return responseCode;
}

SDK for JavaScript v3

import {
  PutUsersCommand,
  PersonalizeEventsClient,
} from "@aws-sdk/client-personalize-events";

const personalizeEventsClient = new PersonalizeEventsClient({
  region: "REGION",
});

// set the put users parameters
var putUsersParam = {
  datasetArn:
    "DATASET ARN",
  users: [
    {
      userId: "userId",
      properties: '{"column1Name": "value", "column2Name": "value"}',
    },
    {
      userId: "userId",
      properties: '{"column1Name": "value", "column2Name": "value"}',
    },
  ],
};
export const run = async () => {
  try {
    const response = await personalizeEventsClient.send(
      new PutUsersCommand(putUsersParam)
    );
    console.log("Success!", response);
    return response; // For unit tests.
  } catch (err) {
    console.log("Error", err);
  }
};
run();