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# 将指标归因报告发布到 Amazon S3
<a name="metric-attribution-results-s3"></a>

对于所有批量数据，如果您在创建指标归因时提供了 Amazon S3 存储桶，则可以选择在每次为交互数据创建数据集导入作业时，将指标报告发布到您的 Amazon S3 存储桶。

要将指标发布到 Amazon S3，您需要在指标归因中提供指向 Amazon S3 存储桶的路径。然后，在创建数据集导入作业时，将报告发布到 Amazon S3。作业完成后，可以在 Amazon S3 存储桶中找到指标。每次发布指标时，Amazon Personalize 都会在您的 Amazon S3 存储桶中创建一个新文件。文件名包括导入方法和日期，如下所示：

`AggregatedAttributionMetrics - ImportMethod - Timestamp.csv`

以下是指标报告 CSV 文件前几行显示方式的示例。此示例中的指标报告两个不同推荐器在 15 分钟间隔内的总单击量。在 EVENT\$1ATTRIBUTION\$1SOURCE 列中，每个推荐器由其 Amazon 资源名称 (ARN) 标识。

```
METRIC_NAME,EVENT_TYPE,VALUE,MATH_FUNCTION,EVENT_ATTRIBUTION_SOURCE,TIMESTAMP
COUNTWATCHES,WATCH,12.0,samplecount,arn:aws:personalize:us-west-2:acctNum:recommender/recommender1Name,1666925124
COUNTWATCHES,WATCH,112.0,samplecount,arn:aws:personalize:us-west-2:acctNum:recommender/recommender2Name,1666924224
COUNTWATCHES,WATCH,10.0,samplecount,arn:aws:personalize:us-west-2:acctNum:recommender/recommender1Name,1666924224
COUNTWATCHES,WATCH,254.0,samplecount,arn:aws:personalize:us-west-2:acctNum:recommender/recommender2Name,1666922424
COUNTWATCHES,WATCH,112.0,samplecount,arn:aws:personalize:us-west-2:acctNum:recommender/recommender1Name,1666922424
COUNTWATCHES,WATCH,100.0,samplecount,arn:aws:personalize:us-west-2:acctNum:recommender/recommender2Name,1666922424
......
.....
```

## 将批量数据的指标发布到 Amazon S3（控制台）
<a name="metric-attribution-results-s3-console"></a>

要使用 Amazon Personalize 控制台将指标发布到 Amazon S3 存储桶，请创建数据集导入作业，然后在**将事件指标发布到 S3** 中选择**发布此导入作业的指标**。

 有关 step-by-step说明，请参阅[创建数据集导入作业（控制台）](bulk-data-import-step.md#bulk-data-import-console)。

## 将批量数据的指标发布到 Amazon S3 (AWS CLI)
<a name="metric-attributinon-resuslts-s3-cli"></a>

要使用 AWS Command Line Interface (AWS CLI) 将指标发布到 Amazon S3 存储桶，请使用以下代码创建数据集导入任务并提供标`publishAttributionMetricsToS3`志。如果您不想发布特定作业的指标，请忽略标志。有关每个参数的信息，请参阅[CreateDatasetImportJob](API_CreateDatasetImportJob.md)。

```
aws personalize create-dataset-import-job \
--job-name dataset import job name \
--dataset-arn dataset arn \
--data-source dataLocation=s3://amzn-s3-demo-bucket/filename \
--role-arn roleArn \
--import-mode INCREMENTAL \
--publish-attribution-metrics-to-s3
```

## 将批量数据的指标发布到 Amazon S3 (AWS SDKs)
<a name="metric-attributinon-resuslts-s3-sdk"></a>

要使用将指标发布到 Amazon S3 存储桶 AWS SDKs，请创建数据集导入任务并将其设置`publishAttributionMetricsToS3`为 true。有关每个参数的信息，请参阅[CreateDatasetImportJob](API_CreateDatasetImportJob.md)。

------
#### [ SDK for Python (Boto3) ]

```
import boto3

personalize = boto3.client('personalize')

response = personalize.create_dataset_import_job(
    jobName = 'YourImportJob',
    datasetArn = 'dataset_arn',
    dataSource = {'dataLocation':'s3://amzn-s3-demo-bucket/file.csv'},
    roleArn = 'role_arn',
    importMode = 'INCREMENTAL',
    publishAttributionMetricsToS3 = True
)

dsij_arn = response['datasetImportJobArn']

print ('Dataset Import Job arn: ' + dsij_arn)

description = personalize.describe_dataset_import_job(
    datasetImportJobArn = dsij_arn)['datasetImportJob']

print('Name: ' + description['jobName'])
print('ARN: ' + description['datasetImportJobArn'])
print('Status: ' + description['status'])
```

------
#### [ SDK for Java 2.x ]

```
public static String createPersonalizeDatasetImportJob(PersonalizeClient personalizeClient,
                                                      String jobName,
                                                      String datasetArn,
                                                      String s3BucketPath,
                                                      String roleArn,
                                                      ImportMode importMode,
                                                      boolean publishToS3) {

  long waitInMilliseconds = 60 * 1000;
  String status;
  String datasetImportJobArn;
  
  try {
      DataSource importDataSource = DataSource.builder()
              .dataLocation(s3BucketPath)
              .build();
      
      CreateDatasetImportJobRequest createDatasetImportJobRequest = CreateDatasetImportJobRequest.builder()
              .datasetArn(datasetArn)
              .dataSource(importDataSource)
              .jobName(jobName)
              .roleArn(roleArn)
              .importMode(importMode)
              .publishAttributionMetricsToS3(publishToS3)
              .build();
  
      datasetImportJobArn = personalizeClient.createDatasetImportJob(createDatasetImportJobRequest)
              .datasetImportJobArn();
      
      DescribeDatasetImportJobRequest describeDatasetImportJobRequest = DescribeDatasetImportJobRequest.builder()
              .datasetImportJobArn(datasetImportJobArn)
              .build();
  
      long maxTime = Instant.now().getEpochSecond() + 3 * 60 * 60;
  
      while (Instant.now().getEpochSecond() < maxTime) {
  
          DatasetImportJob datasetImportJob = personalizeClient
                  .describeDatasetImportJob(describeDatasetImportJobRequest)
                  .datasetImportJob();
  
          status = datasetImportJob.status();
          System.out.println("Dataset import job status: " + status);
  
          if (status.equals("ACTIVE") || status.equals("CREATE FAILED")) {
              break;
          }
          try {
              Thread.sleep(waitInMilliseconds);
          } catch (InterruptedException e) {
              System.out.println(e.getMessage());
          }
      }
      return datasetImportJobArn;
  
  } catch (PersonalizeException e) {
      System.out.println(e.awsErrorDetails().errorMessage());
  }
  return "";
}
```

------
#### [ SDK for JavaScript v3 ]

```
// Get service clients and commands using ES6 syntax.
import { CreateDatasetImportJobCommand, PersonalizeClient } from
  "@aws-sdk/client-personalize";

// create personalizeClient
const personalizeClient = new PersonalizeClient({
  region: "REGION"
});

// Set the dataset import job parameters.
export const datasetImportJobParam = {
  datasetArn: 'DATASET_ARN', /* required */
  dataSource: {  
    dataLocation: 's3://amzn-s3-demo-bucket/<folderName>/<CSVfilename>.csv'  /* required */
  },
  jobName: 'NAME',                        /* required */
  roleArn: 'ROLE_ARN',                    /* required */
  importMode: "FULL",                     /* optional, default is FULL */
  publishAttributionMetricsToS3: true     /* set to true to publish metrics to Amazon S3 bucket */
};

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();
```

------