Activity Runs - Query By Pipeline Run

參考

服務:: Data Factory

API 版本:: 2018-06-01

查詢活動會根據輸入篩選條件執行。

POST https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.DataFactory/factories/{factoryName}/pipelineruns/{runId}/queryActivityruns?api-version=2018-06-01

URI 參數

名稱	位於	必要	類型	Description
factoryName	path	True	string minLength: 3 maxLength: 63 pattern: ^[A-Za-z0-9]+(?:-[A-Za-z0-9]+)*$	Factory 名稱。
resourceGroupName	path	True	string minLength: 1 maxLength: 90 pattern: ^[-\w\._\(\)]+$	資源組名。
runId	path	True	string	管線執行標識碼。
subscriptionId	path	True	string	訂用帳戶標識碼。
api-version	query	True	string	API 版本。

要求本文

名稱	必要	類型	Description
lastUpdatedAfter	True	string (date-time)	執行事件以『ISO 8601』格式更新的時間或之後。
lastUpdatedBefore	True	string (date-time)	執行事件在『ISO 8601』格式更新之前的時間。
continuationToken		string	取得下一頁結果的接續令牌。第一頁的 Null。
filters		RunQueryFilter[]	篩選清單。
orderBy		RunQueryOrderBy[]	OrderBy 選項的清單。

回應

名稱	類型	Description
200 OK	ActivityRunsQueryResponse	還行。
Other Status Codes	CloudError	從 Azure Data Factory 服務收到的錯誤回應。

安全性

azure_auth

Azure Active Directory OAuth2 Flow。

類型: oauth2
Flow: implicit
授權 URL: https://login.microsoftonline.com/common/oauth2/authorize

範圍

名稱	Description
user_impersonation	模擬您的用戶帳戶

範例

ActivityRuns_QueryByPipelineRun

範例要求

POST https://management.azure.com/subscriptions/12345678-1234-1234-1234-12345678abc/resourceGroups/exampleResourceGroup/providers/Microsoft.DataFactory/factories/exampleFactoryName/pipelineruns/2f7fdb90-5df1-4b8e-ac2f-064cfa58202b/queryActivityruns?api-version=2018-06-01

{
  "lastUpdatedAfter": "2018-06-16T00:36:44.3345758Z",
  "lastUpdatedBefore": "2018-06-16T00:49:48.3686473Z"
}


import com.azure.resourcemanager.datafactory.models.RunFilterParameters;
import java.time.OffsetDateTime;

/**
 * Samples for ActivityRuns QueryByPipelineRun.
 */
public final class Main {
    /*
     * x-ms-original-file: specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/
     * ActivityRuns_QueryByPipelineRun.json
     */
    /**
     * Sample code: ActivityRuns_QueryByPipelineRun.
     * 
     * @param manager Entry point to DataFactoryManager.
     */
    public static void
        activityRunsQueryByPipelineRun(com.azure.resourcemanager.datafactory.DataFactoryManager manager) {
        manager.activityRuns().queryByPipelineRunWithResponse("exampleResourceGroup", "exampleFactoryName",
            "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b",
            new RunFilterParameters().withLastUpdatedAfter(OffsetDateTime.parse("2018-06-16T00:36:44.3345758Z"))
                .withLastUpdatedBefore(OffsetDateTime.parse("2018-06-16T00:49:48.3686473Z")),
            com.azure.core.util.Context.NONE);
    }
}

To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue

from azure.identity import DefaultAzureCredential

from azure.mgmt.datafactory import DataFactoryManagementClient

"""
# PREREQUISITES
    pip install azure-identity
    pip install azure-mgmt-datafactory
# USAGE
    python activity_runs_query_by_pipeline_run.py

    Before run the sample, please set the values of the client ID, tenant ID and client secret
    of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
    AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
    https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
"""


def main():
    client = DataFactoryManagementClient(
        credential=DefaultAzureCredential(),
        subscription_id="12345678-1234-1234-1234-12345678abc",
    )

    response = client.activity_runs.query_by_pipeline_run(
        resource_group_name="exampleResourceGroup",
        factory_name="exampleFactoryName",
        run_id="2f7fdb90-5df1-4b8e-ac2f-064cfa58202b",
        filter_parameters={
            "lastUpdatedAfter": "2018-06-16T00:36:44.3345758Z",
            "lastUpdatedBefore": "2018-06-16T00:49:48.3686473Z",
        },
    )
    print(response)


# x-ms-original-file: specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/ActivityRuns_QueryByPipelineRun.json
if __name__ == "__main__":
    main()

To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue

package armdatafactory_test

import (
	"context"
	"log"

	"time"

	"github.com/Azure/azure-sdk-for-go/sdk/azcore/to"
	"github.com/Azure/azure-sdk-for-go/sdk/azidentity"
	"github.com/Azure/azure-sdk-for-go/sdk/resourcemanager/datafactory/armdatafactory/v9"
)

// Generated from example definition: https://github.com/Azure/azure-rest-api-specs/blob/ab04533261eff228f28e08900445d0edef3eb70c/specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/ActivityRuns_QueryByPipelineRun.json
func ExampleActivityRunsClient_QueryByPipelineRun() {
	cred, err := azidentity.NewDefaultAzureCredential(nil)
	if err != nil {
		log.Fatalf("failed to obtain a credential: %v", err)
	}
	ctx := context.Background()
	clientFactory, err := armdatafactory.NewClientFactory("<subscription-id>", cred, nil)
	if err != nil {
		log.Fatalf("failed to create client: %v", err)
	}
	res, err := clientFactory.NewActivityRunsClient().QueryByPipelineRun(ctx, "exampleResourceGroup", "exampleFactoryName", "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b", armdatafactory.RunFilterParameters{
		LastUpdatedAfter:  to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:36:44.334Z"); return t }()),
		LastUpdatedBefore: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:49:48.368Z"); return t }()),
	}, nil)
	if err != nil {
		log.Fatalf("failed to finish the request: %v", err)
	}
	// You could use response here. We use blank identifier for just demo purposes.
	_ = res
	// If the HTTP response code is 200 as defined in example definition, your response structure would look as follows. Please pay attention that all the values in the output are fake values for just demo purposes.
	// res.ActivityRunsQueryResponse = armdatafactory.ActivityRunsQueryResponse{
	// 	Value: []*armdatafactory.ActivityRun{
	// 		{
	// 			AdditionalProperties: map[string]any{
	// 				"retryAttempt": nil,
	// 				"userProperties": map[string]any{
	// 				},
	// 			},
	// 			ActivityName: to.Ptr("ExampleForeachActivity"),
	// 			ActivityRunEnd: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:38:11.544Z"); return t}()),
	// 			ActivityRunID: to.Ptr("f30c5514-fb85-43ed-9fa4-768d42e58680"),
	// 			ActivityRunStart: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:37:49.480Z"); return t}()),
	// 			ActivityType: to.Ptr("ForEach"),
	// 			DurationInMs: to.Ptr[int32](22064),
	// 			Error: map[string]any{
	// 				"errorCode": "",
	// 				"failureType": "",
	// 				"message": "",
	// 				"target": "ExampleForeachActivity",
	// 			},
	// 			Input: map[string]any{
	// 			},
	// 			LinkedServiceName: to.Ptr(""),
	// 			Output: map[string]any{
	// 			},
	// 			PipelineName: to.Ptr("examplePipeline"),
	// 			PipelineRunID: to.Ptr("2f7fdb90-5df1-4b8e-ac2f-064cfa58202b"),
	// 			Status: to.Ptr("Succeeded"),
	// 		},
	// 		{
	// 			AdditionalProperties: map[string]any{
	// 				"retryAttempt": nil,
	// 				"userProperties": map[string]any{
	// 				},
	// 			},
	// 			ActivityName: to.Ptr("ExampleCopyActivity"),
	// 			ActivityRunEnd: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:38:07.418Z"); return t}()),
	// 			ActivityRunID: to.Ptr("a96678c8-7167-4f00-b629-afccfbad4e51"),
	// 			ActivityRunStart: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:37:50.246Z"); return t}()),
	// 			ActivityType: to.Ptr("Copy"),
	// 			DurationInMs: to.Ptr[int32](17172),
	// 			Error: map[string]any{
	// 				"errorCode": "",
	// 				"failureType": "",
	// 				"message": "",
	// 				"target": "ExampleCopyActivity",
	// 			},
	// 			Input: map[string]any{
	// 				"dataIntegrationUnits": float64(32),
	// 				"sink":map[string]any{
	// 					"type": "BlobSink",
	// 				},
	// 				"source":map[string]any{
	// 					"type": "BlobSource",
	// 				},
	// 			},
	// 			LinkedServiceName: to.Ptr(""),
	// 			Output: map[string]any{
	// 				"copyDuration": float64(6),
	// 				"dataRead": float64(142000),
	// 				"dataWritten": float64(142000),
	// 				"effectiveIntegrationRuntime": "DefaultIntegrationRuntime (East US)",
	// 				"errors":[]any{
	// 				},
	// 				"executionDetails":[]any{
	// 					map[string]any{
	// 						"detailedDurations":map[string]any{
	// 							"queuingDuration": float64(4),
	// 							"transferDuration": float64(2),
	// 						},
	// 						"duration": float64(6),
	// 						"sink":map[string]any{
	// 							"type": "AzureBlob",
	// 						},
	// 						"source":map[string]any{
	// 							"type": "AzureBlob",
	// 						},
	// 						"start": "2018-06-16T00:37:50.68834Z",
	// 						"status": "Succeeded",
	// 						"usedCloudDataMovementUnits": float64(4),
	// 						"usedParallelCopies": float64(1),
	// 					},
	// 				},
	// 				"filesRead": float64(1),
	// 				"filesWritten": float64(1),
	// 				"throughput": float64(23.112),
	// 				"usedCloudDataMovementUnits": float64(4),
	// 				"usedParallelCopies": float64(1),
	// 			},
	// 			PipelineName: to.Ptr("examplePipeline"),
	// 			PipelineRunID: to.Ptr("2f7fdb90-5df1-4b8e-ac2f-064cfa58202b"),
	// 			Status: to.Ptr("Succeeded"),
	// 	}},
	// }
}

To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue

const { DataFactoryManagementClient } = require("@azure/arm-datafactory");
const { DefaultAzureCredential } = require("@azure/identity");

/**
 * This sample demonstrates how to Query activity runs based on input filter conditions.
 *
 * @summary Query activity runs based on input filter conditions.
 * x-ms-original-file: specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/ActivityRuns_QueryByPipelineRun.json
 */
async function activityRunsQueryByPipelineRun() {
  const subscriptionId =
    process.env["DATAFACTORY_SUBSCRIPTION_ID"] || "12345678-1234-1234-1234-12345678abc";
  const resourceGroupName = process.env["DATAFACTORY_RESOURCE_GROUP"] || "exampleResourceGroup";
  const factoryName = "exampleFactoryName";
  const runId = "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b";
  const filterParameters = {
    lastUpdatedAfter: new Date("2018-06-16T00:36:44.3345758Z"),
    lastUpdatedBefore: new Date("2018-06-16T00:49:48.3686473Z"),
  };
  const credential = new DefaultAzureCredential();
  const client = new DataFactoryManagementClient(credential, subscriptionId);
  const result = await client.activityRuns.queryByPipelineRun(
    resourceGroupName,
    factoryName,
    runId,
    filterParameters,
  );
  console.log(result);
}

To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue

using Azure;
using Azure.ResourceManager;
using System;
using System.Threading.Tasks;
using Azure.Core;
using Azure.Core.Expressions.DataFactory;
using Azure.Identity;
using Azure.ResourceManager.DataFactory.Models;
using Azure.ResourceManager.DataFactory;

// Generated from example definition: specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/ActivityRuns_QueryByPipelineRun.json
// this example is just showing the usage of "ActivityRuns_QueryByPipelineRun" operation, for the dependent resources, they will have to be created separately.

// get your azure access token, for more details of how Azure SDK get your access token, please refer to https://learn.microsoft.com/en-us/dotnet/azure/sdk/authentication?tabs=command-line
TokenCredential cred = new DefaultAzureCredential();
// authenticate your client
ArmClient client = new ArmClient(cred);

// this example assumes you already have this DataFactoryResource created on azure
// for more information of creating DataFactoryResource, please refer to the document of DataFactoryResource
string subscriptionId = "12345678-1234-1234-1234-12345678abc";
string resourceGroupName = "exampleResourceGroup";
string factoryName = "exampleFactoryName";
ResourceIdentifier dataFactoryResourceId = DataFactoryResource.CreateResourceIdentifier(subscriptionId, resourceGroupName, factoryName);
DataFactoryResource dataFactory = client.GetDataFactoryResource(dataFactoryResourceId);

// invoke the operation and iterate over the result
string runId = "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b";
RunFilterContent content = new RunFilterContent(DateTimeOffset.Parse("2018-06-16T00:36:44.3345758Z"), DateTimeOffset.Parse("2018-06-16T00:49:48.3686473Z"));
await foreach (PipelineActivityRunInformation item in dataFactory.GetActivityRunAsync(runId, content))
{
    Console.WriteLine($"Succeeded: {item}");
}

Console.WriteLine("Succeeded");

To use the Azure SDK library in your project, see this documentation. To provide feedback on this code sample, open a GitHub issue

az datafactory activity-run query-by-pipeline-run --factory-name "exampleFactoryName" --last-updated-after "2018-06-16T00:36:44.3345758Z" --last-updated-before "2018-06-16T00:49:48.3686473Z" --resource-group "exampleResourceGroup" --run-id "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b"

Click here to learn more about the Azure CLI command.

範例回覆

狀態碼:: 200

Date: Sat, 16 Jun 2018 00:40:13 GMT
X-Content-Type-Options: nosniff
x-ms-ratelimit-remaining-subscription-writes: 1187
x-ms-request-id: 5465cf41-2e71-4ce6-8db4-9de1b92ffda9
x-ms-correlation-request-id: 5465cf41-2e71-4ce6-8db4-9de1b92ffda9

{
  "value": [
    {
      "activityRunEnd": "2018-06-16T00:38:11.5445431Z",
      "activityName": "ExampleForeachActivity",
      "activityRunStart": "2018-06-16T00:37:49.4804925Z",
      "activityType": "ForEach",
      "durationInMs": 22064,
      "retryAttempt": null,
      "error": {
        "errorCode": "",
        "message": "",
        "failureType": "",
        "target": "ExampleForeachActivity"
      },
      "activityRunId": "f30c5514-fb85-43ed-9fa4-768d42e58680",
      "input": {},
      "linkedServiceName": "",
      "output": {},
      "userProperties": {},
      "pipelineName": "examplePipeline",
      "pipelineRunId": "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b",
      "status": "Succeeded"
    },
    {
      "activityRunEnd": "2018-06-16T00:38:07.4188923Z",
      "activityName": "ExampleCopyActivity",
      "activityRunStart": "2018-06-16T00:37:50.2460952Z",
      "activityType": "Copy",
      "durationInMs": 17172,
      "retryAttempt": null,
      "error": {
        "errorCode": "",
        "message": "",
        "failureType": "",
        "target": "ExampleCopyActivity"
      },
      "activityRunId": "a96678c8-7167-4f00-b629-afccfbad4e51",
      "input": {
        "source": {
          "type": "BlobSource"
        },
        "sink": {
          "type": "BlobSink"
        },
        "dataIntegrationUnits": 32
      },
      "linkedServiceName": "",
      "output": {
        "dataRead": 142000,
        "dataWritten": 142000,
        "filesRead": 1,
        "filesWritten": 1,
        "copyDuration": 6,
        "throughput": 23.112,
        "errors": [],
        "effectiveIntegrationRuntime": "DefaultIntegrationRuntime (East US)",
        "usedCloudDataMovementUnits": 4,
        "usedParallelCopies": 1,
        "executionDetails": [
          {
            "source": {
              "type": "AzureBlob"
            },
            "sink": {
              "type": "AzureBlob"
            },
            "status": "Succeeded",
            "start": "2018-06-16T00:37:50.68834Z",
            "duration": 6,
            "usedCloudDataMovementUnits": 4,
            "usedParallelCopies": 1,
            "detailedDurations": {
              "queuingDuration": 4,
              "transferDuration": 2
            }
          }
        ]
      },
      "userProperties": {},
      "pipelineName": "examplePipeline",
      "pipelineRunId": "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b",
      "status": "Succeeded"
    }
  ]
}

定義

名稱	Description
ActivityRun	管線中執行活動的相關信息。
ActivityRunsQueryResponse	清單活動會執行。
CloudError	對象，定義 Azure Data Factory 錯誤響應的結構。
RunFilterParameters	清單執行的查詢參數。
RunQueryFilter	清單執行的查詢篩選選項。
RunQueryFilterOperand	要用於篩選的參數名稱。查詢管線執行的允許作數為 PipelineName、RunStart、RunEnd 和 Status;若要查詢活動執行，則為 ActivityName、ActivityRunStart、ActivityRunEnd、ActivityType 和 Status，而查詢觸發程式執行則為 TriggerName、TriggerRunTimestamp 和 Status。
RunQueryFilterOperator	要用於篩選的運算子。
RunQueryOrder	參數的排序順序。
RunQueryOrderBy	要依清單執行選項提供順序的物件。
RunQueryOrderByField	要用於排序依據的參數名稱。管線執行的允許參數為 PipelineName、RunStart、RunEnd 和 Status;針對活動執行為 ActivityName、ActivityRunStart、ActivityRunEnd 和 Status;若為觸發程式執行，則為 TriggerName、TriggerRunTimestamp 和 Status。

ActivityRun

Object

管線中執行活動的相關信息。

名稱	類型	Description
activityName	string	活動的名稱。
activityRunEnd	string (date-time)	活動的結束時間會以『ISO 8601』格式執行。
activityRunId	string	活動執行的標識碼。
activityRunStart	string (date-time)	活動的開始時間會以『ISO 8601』格式執行。
activityType	string	活動的型別。
durationInMs	integer	活動執行的持續時間。
error	object	如果活動有任何執行，則為錯誤。
input	object	活動的輸入。
linkedServiceName	string	計算連結服務的名稱。
output	object	活動的輸出。
pipelineName	string	管線的名稱。
pipelineRunId	string	管線執行的標識碼。
status	string	活動執行的狀態。

ActivityRunsQueryResponse

Object

清單活動會執行。

名稱	類型	Description
continuationToken	string	如果有任何剩餘的結果存在，則為取得下一頁結果的接續令牌，否則為 null。
value	ActivityRun[]	活動執行清單。

CloudError

Object

對象，定義 Azure Data Factory 錯誤響應的結構。

名稱	類型	Description
error.code	string	錯誤碼。
error.details	CloudError[]	具有其他錯誤詳細數據的陣列。
error.message	string	錯誤資訊。
error.target	string	與錯誤相關聯之要求中的屬性名稱/路徑。

RunFilterParameters

Object

清單執行的查詢參數。

名稱	類型	Description
continuationToken	string	取得下一頁結果的接續令牌。第一頁的 Null。
filters	RunQueryFilter[]	篩選清單。
lastUpdatedAfter	string (date-time)	執行事件以『ISO 8601』格式更新的時間或之後。
lastUpdatedBefore	string (date-time)	執行事件在『ISO 8601』格式更新之前的時間。
orderBy	RunQueryOrderBy[]	OrderBy 選項的清單。

RunQueryFilter

Object

清單執行的查詢篩選選項。

名稱	類型	Description
operand	RunQueryFilterOperand	要用於篩選的參數名稱。查詢管線執行的允許作數為 PipelineName、RunStart、RunEnd 和 Status;若要查詢活動執行，則為 ActivityName、ActivityRunStart、ActivityRunEnd、ActivityType 和 Status，而查詢觸發程式執行則為 TriggerName、TriggerRunTimestamp 和 Status。
operator	RunQueryFilterOperator	要用於篩選的運算子。
values	string[]	篩選值的清單。

RunQueryFilterOperand

列舉型別

要用於篩選的參數名稱。查詢管線執行的允許作數為 PipelineName、RunStart、RunEnd 和 Status;若要查詢活動執行，則為 ActivityName、ActivityRunStart、ActivityRunEnd、ActivityType 和 Status，而查詢觸發程式執行則為 TriggerName、TriggerRunTimestamp 和 Status。

值	Description
ActivityName
ActivityRunEnd
ActivityRunStart
ActivityType
LatestOnly
PipelineName
RunEnd
RunGroupId
RunStart
Status
TriggerName
TriggerRunTimestamp

RunQueryFilterOperator

列舉型別

要用於篩選的運算子。

值	Description
Equals
In
NotEquals
NotIn

RunQueryOrder

列舉型別

參數的排序順序。

值	Description
ASC
DESC

RunQueryOrderBy

Object

要依清單執行選項提供順序的物件。

名稱	類型	Description
order	RunQueryOrder	參數的排序順序。
orderBy	RunQueryOrderByField	要用於排序依據的參數名稱。管線執行的允許參數為 PipelineName、RunStart、RunEnd 和 Status;針對活動執行為 ActivityName、ActivityRunStart、ActivityRunEnd 和 Status;若為觸發程式執行，則為 TriggerName、TriggerRunTimestamp 和 Status。

RunQueryOrderByField

列舉型別

要用於排序依據的參數名稱。管線執行的允許參數為 PipelineName、RunStart、RunEnd 和 Status;針對活動執行為 ActivityName、ActivityRunStart、ActivityRunEnd 和 Status;若為觸發程式執行，則為 TriggerName、TriggerRunTimestamp 和 Status。

值	Description
ActivityName
ActivityRunEnd
ActivityRunStart
PipelineName
RunEnd
RunStart
Status
TriggerName
TriggerRunTimestamp