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# 更新 Amazon Personalize 指标归因
<a name="updating-metric-attribution"></a>

 更新指标归因时，您可以添加和移除指标以及修改其输出配置。您可以使用 Amazon Personalize 控制台或 Amazon SDK 更新指标归因。 Amazon Command Line Interface

**Topics**
+ [更新指标归因（控制台）](#updating-metric-attribution-console)
+ [更新指标归因 (Amazon CLI)](#updating-metric-attribution-cli)
+ [更新指标归因 (Amazon SDK)](#updating-metric-attribution-sdk)

## 更新指标归因（控制台）
<a name="updating-metric-attribution-console"></a>

要使用 Amazon Personalize 控制台更新指标归因，您可以在**指标归因**页面上进行更改。

**更新指标归因**

1. 在[https://console.aws.amazon.com/personalize/家](https://console.amazonaws.cn/personalize/home)中打开 Amazon Personalize 控制台并登录您的账户。

1. 选择您的数据集组。

1. 在导航窗格中，选择**指标归因**。

1. 在底部，选择**指标属性**选项卡或**指标归因配置**选项卡，以开始进行更改。
   + 要添加或删除指标，请选择**指标属性**选项卡，然后选择**编辑属性**。在**编辑指标属性**页面上进行更改，然后选择**更新**以保存更改。
   + 要更改 Amazon S3 输出存储桶或 IAM 服务角色，请选择**编辑指标归因配置**选项卡，然后在**编辑归因配置**页面上进行更改。单击**更新**以保存您的更改。

## 更新指标归因 (Amazon CLI)
<a name="updating-metric-attribution-cli"></a>

创建指标归因后，您可以使用 Amazon Command Line Interface (Amazon CLI) 添加和移除指标以及修改其输出配置。以下代码显示了如何使用 `update-metric-attribution` 命令删除指标：

```
aws personalize update-metric-attribution \
--metric-attribution-arn {{metric attribution arn}} \
--remove-metrics {{metricName1}} {{metricName2}}
```

 以下代码显示了如何添加其他指标和指定新的输出配置：

```
aws personalize update-metric-attribution \
--metric-attribution-arn {{metric attribution arn}} \
--metrics-output-config "{\"roleArn\": \"{{new role ARN}}\", \"s3DataDestination\":{\"kmsKeyArn\":\"{{kms key ARN}}\",\"path\":\"s3://{{amzn-s3-demo-bucket2}}/{{new-folder-name}}/\"}}" \
--add-metrics "[{
  \"eventType\": \"{{event type}}\",
  \"expression\": \"{{SUM(DatasetType.COLUMN_NAME)}}\",
  \"metricName\": \"{{metric name}}\"
}]"
```

 如果成功，则 Amazon Personalize 会返回您更新的指标归因的 ARN。要获得所有参数的完整列表，请参阅 [UpdateMetricAttribution](API_UpdateMetricAttribution.md)。

## 更新指标归因 (Amazon SDK)
<a name="updating-metric-attribution-sdk"></a>

创建指标归因后，您可以添加或移除指标以及修改其输出配置。以下代码显示了如何从指标归因中移除指标。

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

```
import boto3
            
personalize = boto3.client('personalize')

metricsToRemove = ["{{metricName1}}", "{{metricName2}}"]
            
response = personalize.update_metric_attribution(
  metricAttributionArn = "{{metric attribution ARN}}",
  removeMetrics = metricsToRemove
)
```

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

```
public static void removeMetrics(PersonalizeClient client,
                                 String metricAttributionArn,
                                 String metric1Name,
                                 String metric2Name) {

    ArrayList<String> metricsToRemove = new ArrayList<>(Arrays.asList(metric1Name, metric2Name));
    
    try {
    
        UpdateMetricAttributionRequest request = UpdateMetricAttributionRequest.builder()
                .metricAttributionArn(metricAttributionArn)
                .removeMetrics(metricsToRemove)
                .build();
                
        UpdateMetricAttributionResponse response = client.updateMetricAttribution(request);
        System.out.println(response);
        
    } catch (PersonalizeException e) {
        System.out.println(e.awsErrorDetails().errorMessage());
    }
}
```

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

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

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

// set the update request param
export const updateMetricAttributionParam = {
  metricAttributionArn: "METRIC_ATTRIBUTION_ARN",    /* required */
  removeMetrics: ["METRIC_NAME_1", "METRIC_NAME_2"]    /* specify list of names of metrics to delete */
};
export const run = async () => {
  try {
    const response = await personalizeClient.send(
      new UpdateMetricAttributionCommand(updateMetricAttributionParam)
    );
    console.log("Success", response);
    return response; // For unit tests.
  } catch (err) {
    console.log("Error", err);
  }
};
run();
```

------

 以下代码显示了如何添加其他指标和指定新的输出配置：

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

```
import boto3

personalize = boto3.client('personalize')

newMetrics = [{ 
      "eventType": "{{event type}}",
      "expression": "{{SUM(DatasetType.COLUMN_NAME)}}",
      "metricName": "{{metric name}}"
}]

newOutputConfig = {
  "roleArn": "{{Amazon Personalize service role ARN}}", 
  "s3DataDestination": {
    "kmsKeyArn": "{{key ARN}}", 
    "path": "{{s3://amzn-s3-demo-bucket/<folder>}}"
  }
}

response = personalize.update_metric_attribution(
  metricAttributionArn = "{{metric attribution arn}}",
  metricsOutputConfig = newOutputConfig,
  addMetrics = newMetrics
)
```

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

```
public static void addMetricsAndUpdateOutputConfig(PersonalizeClient personalizeClient,
                                                String metricAttributionArn,
                                                String newMetric1EventType,
                                                String newMetric1Expression,
                                                String newMetric1Name,
                                                String newMetric2EventType,
                                                String newMetric2Expression,
                                                String newMetric2Name,
                                                String roleArn,
                                                String s3Path,
                                                String kmsKeyArn) {
    try {
    
        MetricAttribute newAttribute = MetricAttribute.builder()
                .eventType(newMetric1EventType)
                .expression(newMetric1Expression)
                .metricName(newMetric1Name)
                .build();
                
        MetricAttribute newAttribute2 = MetricAttribute.builder()
                .eventType(newMetric2EventType)
                .expression(newMetric2Expression)
                .metricName(newMetric2Name)
                .build();

        ArrayList<MetricAttribute> newAttributes = new ArrayList<>(Arrays.asList(newAttribute, newAttribute2));

        S3DataConfig newDataDestination = S3DataConfig.builder()
                .kmsKeyArn(kmsKeyArn)
                .path(s3Path)
                .build();

        MetricAttributionOutput newOutputConfig = MetricAttributionOutput.builder()
                .roleArn(roleArn)
                .s3DataDestination(newDataDestination)
                .build();
                
        UpdateMetricAttributionRequest request = UpdateMetricAttributionRequest.builder()
                .metricAttributionArn(metricAttributionArn)
                .metricsOutputConfig(newOutputConfig)
                .addMetrics(newAttributes)
                .build();
                
        UpdateMetricAttributionResponse response = personalizeClient.updateMetricAttribution(request);
        System.out.println("New metrics added!");
        System.out.println(response);
        
    } catch (PersonalizeException e) {
        System.out.println(e.awsErrorDetails().errorMessage());
    }
}
```

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

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

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

export const updateMetricAttributionParam = {
  metricAttributionArn: "METRIC_ATTRIBUTION_ARN",
  addMetrics: [
    {
      eventType: "EVENT_TYPE",                      /* required for each metric */
      expression: "SUM(DatasetType.COLUMN_NAME)",   /* required for each metric */
      metricName: "METRIC_NAME",                    /* required for each metric */
    }
  ],
  metricsOutputConfig: {
    roleArn: "ROLE_ARN",                      /* required */
    s3DataDestination: {                
      kmsKeyArn: "KEY_ARN",                                                      /* optional */
      path: "s3://amzn-s3-demo-bucket/<folderName>/",    /* optional */
    },
  }
};

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

------

如果成功，则 Amazon Personalize 会返回您更新的指标归因的 ARN。要获得所有参数的完整列表，请参阅 [UpdateMetricAttribution](API_UpdateMetricAttribution.md)。