aws-cdk-lib.aws_lookoutmetrics.CfnAnomalyDetector.MetricSetProperty

interface MetricSetProperty

LanguageType name
.NETAmazon.CDK.AWS.LookoutMetrics.CfnAnomalyDetector.MetricSetProperty
Gogithub.com/aws/aws-cdk-go/awscdk/v2/awslookoutmetrics#CfnAnomalyDetector_MetricSetProperty
Javasoftware.amazon.awscdk.services.lookoutmetrics.CfnAnomalyDetector.MetricSetProperty
Pythonaws_cdk.aws_lookoutmetrics.CfnAnomalyDetector.MetricSetProperty
TypeScript aws-cdk-lib » aws_lookoutmetrics » CfnAnomalyDetector » MetricSetProperty

Contains information about a dataset.

Example

// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import { aws_lookoutmetrics as lookoutmetrics } from 'aws-cdk-lib';
const metricSetProperty: lookoutmetrics.CfnAnomalyDetector.MetricSetProperty = {
  metricList: [{
    aggregationFunction: 'aggregationFunction',
    metricName: 'metricName',

    // the properties below are optional
    namespace: 'namespace',
  }],
  metricSetName: 'metricSetName',
  metricSource: {
    appFlowConfig: {
      flowName: 'flowName',
      roleArn: 'roleArn',
    },
    cloudwatchConfig: {
      roleArn: 'roleArn',
    },
    rdsSourceConfig: {
      databaseHost: 'databaseHost',
      databaseName: 'databaseName',
      databasePort: 123,
      dbInstanceIdentifier: 'dbInstanceIdentifier',
      roleArn: 'roleArn',
      secretManagerArn: 'secretManagerArn',
      tableName: 'tableName',
      vpcConfiguration: {
        securityGroupIdList: ['securityGroupIdList'],
        subnetIdList: ['subnetIdList'],
      },
    },
    redshiftSourceConfig: {
      clusterIdentifier: 'clusterIdentifier',
      databaseHost: 'databaseHost',
      databaseName: 'databaseName',
      databasePort: 123,
      roleArn: 'roleArn',
      secretManagerArn: 'secretManagerArn',
      tableName: 'tableName',
      vpcConfiguration: {
        securityGroupIdList: ['securityGroupIdList'],
        subnetIdList: ['subnetIdList'],
      },
    },
    s3SourceConfig: {
      fileFormatDescriptor: {
        csvFormatDescriptor: {
          charset: 'charset',
          containsHeader: false,
          delimiter: 'delimiter',
          fileCompression: 'fileCompression',
          headerList: ['headerList'],
          quoteSymbol: 'quoteSymbol',
        },
        jsonFormatDescriptor: {
          charset: 'charset',
          fileCompression: 'fileCompression',
        },
      },
      roleArn: 'roleArn',

      // the properties below are optional
      historicalDataPathList: ['historicalDataPathList'],
      templatedPathList: ['templatedPathList'],
    },
  },

  // the properties below are optional
  dimensionList: ['dimensionList'],
  metricSetDescription: 'metricSetDescription',
  metricSetFrequency: 'metricSetFrequency',
  offset: 123,
  timestampColumn: {
    columnFormat: 'columnFormat',
    columnName: 'columnName',
  },
  timezone: 'timezone',
};

Properties

NameTypeDescription
metricListIResolvable | IResolvable | MetricProperty[]A list of metrics that the dataset will contain.
metricSetNamestringThe name of the dataset.
metricSourceIResolvable | MetricSourcePropertyContains information about how the source data should be interpreted.
dimensionList?string[]A list of the fields you want to treat as dimensions.
metricSetDescription?stringA description of the dataset you are creating.
metricSetFrequency?stringThe frequency with which the source data will be analyzed for anomalies.
offset?numberAfter an interval ends, the amount of seconds that the detector waits before importing data.
timestampColumn?IResolvable | TimestampColumnPropertyContains information about the column used for tracking time in your source data.
timezone?stringThe time zone in which your source data was recorded.

metricList

Type: IResolvable | IResolvable | MetricProperty[]

A list of metrics that the dataset will contain.


metricSetName

Type: string

The name of the dataset.


metricSource

Type: IResolvable | MetricSourceProperty

Contains information about how the source data should be interpreted.


dimensionList?

Type: string[] (optional)

A list of the fields you want to treat as dimensions.


metricSetDescription?

Type: string (optional)

A description of the dataset you are creating.


metricSetFrequency?

Type: string (optional)

The frequency with which the source data will be analyzed for anomalies.


offset?

Type: number (optional)

After an interval ends, the amount of seconds that the detector waits before importing data.

Offset is only supported for S3, Redshift, Athena and datasources.


timestampColumn?

Type: IResolvable | TimestampColumnProperty (optional)

Contains information about the column used for tracking time in your source data.


timezone?

Type: string (optional)

The time zone in which your source data was recorded.