域名数据集组入门（SDK适用于 JavaScript v3）

将以下 Avro 架构另存为工作目录中的JSON文件。此架构与您在完成时创建CSV的文件中的列相匹配创建训练数据（域数据集组）。

{
  "type": "record",
  "name": "Interactions",
  "namespace": "com.amazonaws.personalize.schema",
  "fields": [
      {
          "name": "USER_ID",
          "type": "string"
      },
      {
          "name": "ITEM_ID",
          "type": "string"
      },
      {
          "name": "EVENT_TYPE",
          "type": "string"
      },
      {
          "name": "TIMESTAMP",
          "type": "long"
      }
  ],
  "version": "1.0"
}

使用以下 createDomainSchema.js 代码创建 Amazon Personalize 域架构。将 SCHEMA_PATH 替换为您刚创建的 schema.json 文件的路径。更新 createSchemaParam 以指定架构的名称，对于 domain，指定 VIDEO_ON_DEMAND。

// 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 "node:fs";

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

try {
  mySchema = fs.readFileSync(schemaFilePath).toString();
} catch (err) {
  mySchema = "TEST"; // for unit tests.
}

// Set the domain schema parameters.
export const createDomainSchemaParam = {
  name: "NAME" /* required */,
  schema: mySchema /* required */,
  domain:
    "DOMAIN" /* required for a domain dataset group, specify ECOMMERCE or VIDEO_ON_DEMAND */,
};

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

使用以下 createDomainDatasetGroup.js 代码创建 Amazon Personalize 域数据集组。更新 domainDatasetGroupParams 以指定数据集组的名称，对于 domain，指定 VIDEO_ON_DEMAND。

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

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

// Set the domain dataset group parameters.
export const domainDatasetGroupParams = {
  name: "NAME" /* required */,
  domain:
    "DOMAIN" /* required for a domain dsg, specify ECOMMERCE or VIDEO_ON_DEMAND */,
};

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

使用以下 createDataset.js 代码在 Amazon Personalize 中创建物品交互数据集。更新createDatasetParam以指定您刚刚创建的数据集组和架构的 Amazon 资源名称 (ARN)，为datasetType数据集指定一个名称，然后指定Interactions。

// 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();

使用以下 createDatasetImportJob.js 代码导入数据。更新 datasetImportJobParam 以指定以下内容：

// Get service clients module and commands using ES6 syntax.
import { CreateDatasetImportJobCommand } 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 import job parameters.
export const datasetImportJobParam = {
  datasetArn: "DATASET_ARN" /* required */,
  dataSource: {
    /* required */
    dataLocation: "S3_PATH",
  },
  jobName: "NAME" /* required */,
  roleArn: "ROLE_ARN" /* required */,
};

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