AnomalyDetectorClient.DetectMultivariateBatchAnomaly Method

Definition

Namespace:

Azure.AI.AnomalyDetector

Assembly:

Azure.AI.AnomalyDetector.dll

Package:

Azure.AI.AnomalyDetector v3.0.0-preview.7

Overloads

DetectMultivariateBatchAnomaly(String, MultivariateBatchDetectionOptions, CancellationToken)	Detect Multivariate Anomaly.
DetectMultivariateBatchAnomaly(String, RequestContent, RequestContext)	[Protocol Method] Detect Multivariate Anomaly This protocol method allows explicit creation of the request and processing of the response for advanced scenarios. Please try the simpler DetectMultivariateBatchAnomaly(String, MultivariateBatchDetectionOptions, CancellationToken) convenience overload with strongly typed models first.

DetectMultivariateBatchAnomaly(String, MultivariateBatchDetectionOptions, CancellationToken)

Source:

AnomalyDetectorClient.cs

Detect Multivariate Anomaly.

public virtual Azure.Response<Azure.AI.AnomalyDetector.MultivariateDetectionResult> DetectMultivariateBatchAnomaly (string modelId, Azure.AI.AnomalyDetector.MultivariateBatchDetectionOptions options, System.Threading.CancellationToken cancellationToken = default);

abstract member DetectMultivariateBatchAnomaly : string * Azure.AI.AnomalyDetector.MultivariateBatchDetectionOptions * System.Threading.CancellationToken -> Azure.Response<Azure.AI.AnomalyDetector.MultivariateDetectionResult>
override this.DetectMultivariateBatchAnomaly : string * Azure.AI.AnomalyDetector.MultivariateBatchDetectionOptions * System.Threading.CancellationToken -> Azure.Response<Azure.AI.AnomalyDetector.MultivariateDetectionResult>

Public Overridable Function DetectMultivariateBatchAnomaly (modelId As String, options As MultivariateBatchDetectionOptions, Optional cancellationToken As CancellationToken = Nothing) As Response(Of MultivariateDetectionResult)

Parameters

modelId

String

Model identifier.

options

MultivariateBatchDetectionOptions

Request of multivariate anomaly detection.

cancellationToken

CancellationToken

The cancellation token to use.

Returns

Response<MultivariateDetectionResult>

Exceptions

ArgumentNullException

modelId or options is null.

ArgumentException

modelId is an empty string, and was expected to be non-empty.

Examples

This sample shows how to call DetectMultivariateBatchAnomaly with required parameters.

var credential = new AzureKeyCredential("<key>");
var endpoint = new Uri("<https://my-service.azure.com>");
var client = new AnomalyDetectorClient(endpoint, credential);

var options = new MultivariateBatchDetectionOptions("<dataSource>", 1234, DateTimeOffset.UtcNow, DateTimeOffset.UtcNow);
var result = client.DetectMultivariateBatchAnomaly("<modelId>", options);

Remarks

Submit a multivariate anomaly detection task with the modelId value of a trained model and inference data. The input schema should be the same with the training request. The request will finish asynchronously and return a resultId value to query the detection result. The request should be a source link to indicate an externally accessible Azure Storage URI that either points to an Azure Blob Storage folder or points to a CSV file in Azure Blob Storage.

DetectMultivariateBatchAnomaly(String, RequestContent, RequestContext)

Source:

AnomalyDetectorClient.cs

[Protocol Method] Detect Multivariate Anomaly

• This protocol method allows explicit creation of the request and processing of the response for advanced scenarios.
• Please try the simpler DetectMultivariateBatchAnomaly(String, MultivariateBatchDetectionOptions, CancellationToken) convenience overload with strongly typed models first.

public virtual Azure.Response DetectMultivariateBatchAnomaly (string modelId, Azure.Core.RequestContent content, Azure.RequestContext context = default);

abstract member DetectMultivariateBatchAnomaly : string * Azure.Core.RequestContent * Azure.RequestContext -> Azure.Response
override this.DetectMultivariateBatchAnomaly : string * Azure.Core.RequestContent * Azure.RequestContext -> Azure.Response

Public Overridable Function DetectMultivariateBatchAnomaly (modelId As String, content As RequestContent, Optional context As RequestContext = Nothing) As Response

Parameters

modelId

String

Model identifier.

content

RequestContent

The content to send as the body of the request.

context

RequestContext

The request context, which can override default behaviors of the client pipeline on a per-call basis.

Returns

Response

The response returned from the service.

Exceptions

ArgumentNullException

modelId or content is null.

ArgumentException

modelId is an empty string, and was expected to be non-empty.

RequestFailedException

Service returned a non-success status code.

Examples

This sample shows how to call DetectMultivariateBatchAnomaly with required parameters and request content and parse the result.

var credential = new AzureKeyCredential("<key>");
var endpoint = new Uri("<https://my-service.azure.com>");
var client = new AnomalyDetectorClient(endpoint, credential);

var data = new {
    dataSource = "<dataSource>",
    topContributorCount = 1234,
    startTime = "2022-05-10T14:57:31.2311892-04:00",
    endTime = "2022-05-10T14:57:31.2311892-04:00",
};

Response response = client.DetectMultivariateBatchAnomaly("<modelId>", RequestContent.Create(data), new RequestContext());

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("resultId").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("status").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("errors")[0].GetProperty("code").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("errors")[0].GetProperty("message").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("variableStates")[0].GetProperty("variable").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("variableStates")[0].GetProperty("filledNARatio").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("variableStates")[0].GetProperty("effectiveCount").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("variableStates")[0].GetProperty("firstTimestamp").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("variableStates")[0].GetProperty("lastTimestamp").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("dataSource").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("topContributorCount").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("startTime").ToString());
Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("endTime").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("timestamp").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("isAnomaly").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("severity").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("score").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("interpretation")[0].GetProperty("variable").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("interpretation")[0].GetProperty("contributionScore").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("interpretation")[0].GetProperty("correlationChanges").GetProperty("changedVariables")[0].ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("errors")[0].GetProperty("code").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("errors")[0].GetProperty("message").ToString());

Remarks

Submit multivariate anomaly detection task with the modelId of trained model and inference data, the input schema should be the same with the training request. The request will complete asynchronously and return a resultId to query the detection result.The request should be a source link to indicate an externally accessible Azure storage Uri, either pointed to an Azure blob storage folder, or pointed to a CSV file in Azure blob storage.

Below is the JSON schema for the request and response payloads.

Request Body:

Schema for MultivariateBatchDetectionOptions:

{
  dataSource: string, # Required.
  topContributorCount: number, # Required.
  startTime: string (date & time), # Required.
  endTime: string (date & time), # Required.
}

Response Body:

Schema for MultivariateDetectionResult:

{
  resultId: string, # Required.
  summary: {
    status: "CREATED" | "RUNNING" | "READY" | "FAILED", # Required.
    errors: [ErrorResponse], # Optional.
    variableStates: [VariableState], # Optional.
    setupInfo: {
      dataSource: string, # Required.
      topContributorCount: number, # Required.
      startTime: string (date & time), # Required.
      endTime: string (date & time), # Required.
    }, # Required.
  }, # Required.
  results: [
    {
      timestamp: string (date & time), # Required.
      value: {
        isAnomaly: boolean, # Required.
        severity: number, # Required.
        score: number, # Required.
        interpretation: [AnomalyInterpretation], # Optional.
      }, # Optional.
      errors: [ErrorResponse], # Optional.
    }
  ], # Required.
}