스키마 및 데이터세트 생성

import boto3

personalize = boto3.client('personalize')

with open('schemaFile.json') as f:
    createSchemaResponse = personalize.create_schema(
        name = 'schema name',
        schema = f.read()
    )

schema_arn = createSchemaResponse['schemaArn']

print('Schema ARN:' + schema_arn )

public static String createSchema(PersonalizeClient personalizeClient, String schemaName, String filePath) {
    
    String schema = null;
    
    try {
        schema = new String(Files.readAllBytes(Paths.get(filePath)));
    } catch (IOException e) {
        System.out.println(e.getMessage());
    }
    
    try {
        CreateSchemaRequest createSchemaRequest = CreateSchemaRequest.builder()
                .name(schemaName)
                .schema(schema)
                .build();

        String schemaArn = personalizeClient.createSchema(createSchemaRequest).schemaArn();    
        System.out.println("Schema arn: " + schemaArn);

        return schemaArn;

    } catch(PersonalizeException e) {
        System.err.println(e.awsErrorDetails().errorMessage());
        System.exit(1);
    }
    return "";
}

// Get service clients module and commands using ES6 syntax.
import { CreateSchemaCommand } from
  "@aws-sdk/client-personalize";
import { personalizeClient } from "./libs/personalizeClients.js";

// Or, create the client here.
// const personalizeClient = new PersonalizeClient({ region: "REGION"});

import fs from 'fs';

let schemaFilePath = "SCHEMA_PATH";
let mySchema = "";

try {
  mySchema = fs.readFileSync(schemaFilePath).toString();
} catch (err) {
  mySchema = 'TEST' // For unit tests.
}
// Set the schema parameters.
export const createSchemaParam = {
  name: 'NAME', /* required */
  schema: mySchema /* required */
};

export const run = async () => {
  try {
    const response = await personalizeClient.send(new CreateSchemaCommand(createSchemaParam));
    console.log("Success", response);
    return response; // For unit tests.
  } catch (err) {
    console.log("Error", err);
  }
};
run();

import boto3

personalize = boto3.client('personalize')

response = personalize.create_dataset(
    name = 'dataset_name',
    schemaArn = 'schema_arn',
    datasetGroupArn = 'dataset_group_arn',
    datasetType = 'dataset_type'
)

print ('Dataset Arn: ' + response['datasetArn'])

public static String createDataset(PersonalizeClient personalizeClient, 
                                    String datasetName, 
                                    String datasetGroupArn, 
                                    String datasetType, 
                                    String schemaArn) {
    try {
        CreateDatasetRequest request = CreateDatasetRequest.builder()
                .name(datasetName)
                .datasetGroupArn(datasetGroupArn)
                .datasetType(datasetType)
                .schemaArn(schemaArn).build();
    
        String datasetArn = personalizeClient.createDataset(request).datasetArn();
        System.out.println("Dataset " + datasetName + " created. Dataset ARN: " + datasetArn);
        
        return datasetArn;
        
    } catch(PersonalizeException e) {
        System.err.println(e.awsErrorDetails().errorMessage());
        System.exit(1);
    }
    return "";
}

// Get service clients module and commands using ES6 syntax.
import { CreateDatasetCommand } from
  "@aws-sdk/client-personalize";
import { personalizeClient } from "./libs/personalizeClients.js";

// Or, create the client here.
// const personalizeClient = new PersonalizeClient({ region: "REGION"});

// Set the dataset's parameters.
export const createDatasetParam = {
  datasetGroupArn: 'DATASET_GROUP_ARN', /* required */
  datasetType: 'DATASET_TYPE', /* required */
  name: 'NAME', /* required */
  schemaArn: 'SCHEMA_ARN' /* required */
}

export const run = async () => {
  try {
    const response = await personalizeClient.send(new CreateDatasetCommand(createDatasetParam));
    console.log("Success", response);
    return response; // For unit tests.
  } catch (err) {
    console.log("Error", err);
  }
};
run();