文件 AWS 開發套件範例 GitHub 儲存庫中有更多可用的 [AWS SDK 範例](https://github.com/awsdocs/aws-doc-sdk-examples)。

本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。

# `CreateMatchingWorkflow` 搭配 AWS SDK 使用
<a name="entityresolution_example_entityresolution_CreateMatchingWorkflow_section"></a>

下列程式碼範例示範如何使用 `CreateMatchingWorkflow`。

動作範例是大型程式的程式碼摘錄，必須在內容中執行。您可以在下列程式碼範例的內容中看到此動作：
+  [了解基本概念](entityresolution_example_entityresolution_Scenario_section.md) 

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#### [ Java ]

**SDK for Java 2.x**  
 GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/entityresolution#code-examples)中設定和執行。

```
    /**
     * Creates an asynchronous CompletableFuture to manage the creation of a matching workflow.
     *
     * @param roleARN                 the AWS IAM role ARN to be used for the workflow execution
     * @param workflowName            the name of the workflow to be created
     * @param outputBucket            the S3 bucket path where the workflow output will be stored
     * @param jsonGlueTableArn        the ARN of the Glue Data Catalog table to be used as the input source
     * @param jsonErSchemaMappingName the name of the schema to be used for the input source
     * @return a CompletableFuture that, when completed, will return the ARN of the created workflow
     */
    public CompletableFuture<String> createMatchingWorkflowAsync(
        String roleARN
        , String workflowName
        , String outputBucket
        , String jsonGlueTableArn
        , String jsonErSchemaMappingName
        , String csvGlueTableArn
        , String csvErSchemaMappingName) {

        InputSource jsonInputSource = InputSource.builder()
            .inputSourceARN(jsonGlueTableArn)
            .schemaName(jsonErSchemaMappingName)
            .applyNormalization(false)
            .build();

        InputSource csvInputSource = InputSource.builder()
            .inputSourceARN(csvGlueTableArn)
            .schemaName(csvErSchemaMappingName)
            .applyNormalization(false)
            .build();

        OutputAttribute idOutputAttribute = OutputAttribute.builder()
            .name("id")
            .build();

        OutputAttribute nameOutputAttribute = OutputAttribute.builder()
            .name("name")
            .build();

        OutputAttribute emailOutputAttribute = OutputAttribute.builder()
            .name("email")
            .build();

        OutputAttribute phoneOutputAttribute = OutputAttribute.builder()
            .name("phone")
            .build();

        OutputSource outputSource = OutputSource.builder()
            .outputS3Path("s3://" + outputBucket + "/eroutput")
            .output(idOutputAttribute, nameOutputAttribute, emailOutputAttribute, phoneOutputAttribute)
            .applyNormalization(false)
            .build();

        ResolutionTechniques resolutionType = ResolutionTechniques.builder()
            .resolutionType(ResolutionType.ML_MATCHING)
            .build();

        CreateMatchingWorkflowRequest workflowRequest = CreateMatchingWorkflowRequest.builder()
            .roleArn(roleARN)
            .description("Created by using the AWS SDK for Java")
            .workflowName(workflowName)
            .inputSourceConfig(List.of(jsonInputSource, csvInputSource))
            .outputSourceConfig(List.of(outputSource))
            .resolutionTechniques(resolutionType)
            .build();

        return getResolutionAsyncClient().createMatchingWorkflow(workflowRequest)
            .whenComplete((response, exception) -> {
                if (response != null) {
                    logger.info("Workflow created successfully.");
                } else {
                    Throwable cause = exception.getCause();
                    if (cause instanceof ValidationException) {
                        throw new CompletionException("Invalid request: Please check input parameters.", cause);
                    }

                    if (cause instanceof ConflictException) {
                        throw new CompletionException("A conflicting workflow already exists. Resolve conflicts before proceeding.", cause);
                    }
                    throw new CompletionException("Failed to create workflow: " + exception.getMessage(), exception);
                }
            })
            .thenApply(CreateMatchingWorkflowResponse::workflowArn);
    }
```
+  如需 API 詳細資訊，請參閱《AWS SDK for Java 2.x API 參考》**中的 [CreateMatchingWorkflow](https://docs.aws.amazon.com/goto/SdkForJavaV2/entityresolution-2018-05-10/CreateMatchingWorkflow)。

------
#### [ JavaScript ]

**適用於 JavaScript (v3) 的 SDK**  
 GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javascriptv3/example_code/entityresolution#code-examples)中設定和執行。

```
//The default inputs for this demo are read from the ../inputs.json.

import { fileURLToPath } from "node:url";

import {
  CreateMatchingWorkflowCommand,
  EntityResolutionClient,
} from "@aws-sdk/client-entityresolution";
import data from "../inputs.json" with { type: "json" };

const region = "eu-west-1";
const erClient = new EntityResolutionClient({ region: region });

export const main = async () => {
  const createMatchingWorkflowParams = {
    roleArn: `${data.inputs.roleArn}`,
    workflowName: `${data.inputs.workflowName}`,
    description: "Created by using the AWS SDK for JavaScript (v3).",
    inputSourceConfig: [
      {
        inputSourceARN: `${data.inputs.JSONinputSourceARN}`,
        schemaName: `${data.inputs.schemaNameJson}`,
        applyNormalization: false,
      },
      {
        inputSourceARN: `${data.inputs.CSVinputSourceARN}`,
        schemaName: `${data.inputs.schemaNameCSV}`,
        applyNormalization: false,
      },
    ],
    outputSourceConfig: [
      {
        outputS3Path: `s3://${data.inputs.myBucketName}/eroutput`,
        output: [
          {
            name: "id",
          },
          {
            name: "name",
          },
          {
            name: "email",
          },
          {
            name: "phone",
          },
        ],
        applyNormalization: false,
      },
    ],
    resolutionTechniques: { resolutionType: "ML_MATCHING" },
  };
  try {
    const command = new CreateMatchingWorkflowCommand(
      createMatchingWorkflowParams,
    );
    const response = await erClient.send(command);

    console.log(
      `Workflow created successfully.\n The workflow ARN is: ${response.workflowArn}`,
    );
  } catch (caught) {
    console.error(caught.message);
    throw caught;
  }
};
```
+  如需 API 詳細資訊，請參閱《適用於 JavaScript 的 AWS SDK API 參考》**中的 [CreateMatchingWorkflow](https://docs.aws.amazon.com/AWSJavaScriptSDK/v3/latest/client/entityresolution/command/CreateMatchingWorkflowCommand)。

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