Pipeline Runs - Query By Factory

服務:

Data Factory

API 版本:

2018-06-01

查詢管線會根據輸入篩選條件在處理站中執行。

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

URI 參數

名稱	位於	必要	類型	Description
factoryName	path	True	string	Factory 名稱。 Regex 模式: ^[A-Za-z0-9]+(?:-[A-Za-z0-9]+)*$
resourceGroupName	path	True	string	資源群組名稱。 Regex 模式: ^[-\w\._\(\)]+$
subscriptionId	path	True	string	訂用帳戶識別碼。
api-version	query	True	string	API 版本。

要求本文

名稱	必要	類型	Description
lastUpdatedAfter	True	string	在 或 之後，執行事件會以 'ISO 8601' 格式更新的時間。
lastUpdatedBefore	True	string	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	PipelineRunsQueryResponse	正常。
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

PipelineRuns_QueryByFactory

範例要求

HTTP

POST https://management.azure.com/subscriptions/12345678-1234-1234-1234-12345678abc/resourceGroups/exampleResourceGroup/providers/Microsoft.DataFactory/factories/exampleFactoryName/queryPipelineRuns?api-version=2018-06-01

{
  "lastUpdatedAfter": "2018-06-16T00:36:44.3345758Z",
  "lastUpdatedBefore": "2018-06-16T00:49:48.3686473Z",
  "filters": [
    {
      "operand": "PipelineName",
      "operator": "Equals",
      "values": [
        "examplePipeline"
      ]
    }
  ]
}

Java

import com.azure.resourcemanager.datafactory.models.RunFilterParameters;
import com.azure.resourcemanager.datafactory.models.RunQueryFilter;
import com.azure.resourcemanager.datafactory.models.RunQueryFilterOperand;
import com.azure.resourcemanager.datafactory.models.RunQueryFilterOperator;
import java.time.OffsetDateTime;
import java.util.Arrays;

/**
 * Samples for PipelineRuns QueryByFactory.
 */
public final class Main {
    /*
     * x-ms-original-file: specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/
     * PipelineRuns_QueryByFactory.json
     */
    /**
     * Sample code: PipelineRuns_QueryByFactory.
     * 
     * @param manager Entry point to DataFactoryManager.
     */
    public static void pipelineRunsQueryByFactory(com.azure.resourcemanager.datafactory.DataFactoryManager manager) {
        manager.pipelineRuns().queryByFactoryWithResponse("exampleResourceGroup", "exampleFactoryName",
            new RunFilterParameters().withLastUpdatedAfter(OffsetDateTime.parse("2018-06-16T00:36:44.3345758Z"))
                .withLastUpdatedBefore(OffsetDateTime.parse("2018-06-16T00:49:48.3686473Z"))
                .withFilters(Arrays.asList(new RunQueryFilter().withOperand(RunQueryFilterOperand.PIPELINE_NAME)
                    .withOperator(RunQueryFilterOperator.EQUALS).withValues(Arrays.asList("examplePipeline")))),
            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

Python

from azure.identity import DefaultAzureCredential

from azure.mgmt.datafactory import DataFactoryManagementClient

"""
# PREREQUISITES
    pip install azure-identity
    pip install azure-mgmt-datafactory
# USAGE
    python pipeline_runs_query_by_factory.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.pipeline_runs.query_by_factory(
        resource_group_name="exampleResourceGroup",
        factory_name="exampleFactoryName",
        filter_parameters={
            "filters": [{"operand": "PipelineName", "operator": "Equals", "values": ["examplePipeline"]}],
            "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/PipelineRuns_QueryByFactory.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

Go

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/PipelineRuns_QueryByFactory.json
func ExamplePipelineRunsClient_QueryByFactory() {
	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.NewPipelineRunsClient().QueryByFactory(ctx, "exampleResourceGroup", "exampleFactoryName", armdatafactory.RunFilterParameters{
		Filters: []*armdatafactory.RunQueryFilter{
			{
				Operand:  to.Ptr(armdatafactory.RunQueryFilterOperandPipelineName),
				Operator: to.Ptr(armdatafactory.RunQueryFilterOperatorEquals),
				Values: []*string{
					to.Ptr("examplePipeline")},
			}},
		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.PipelineRunsQueryResponse = armdatafactory.PipelineRunsQueryResponse{
	// 	Value: []*armdatafactory.PipelineRun{
	// 		{
	// 			AdditionalProperties: map[string]any{
	// 				"annotations": []any{
	// 				},
	// 				"runDimension": map[string]any{
	// 					"JobId": "79c1cc52-265f-41a5-9553-be65e736fbd3",
	// 				},
	// 			},
	// 			DurationInMs: to.Ptr[int32](28105),
	// 			InvokedBy: &armdatafactory.PipelineRunInvokedBy{
	// 				Name: to.Ptr("Manual"),
	// 				ID: to.Ptr("80a01654a9d34ad18b3fcac5d5d76b67"),
	// 			},
	// 			LastUpdated: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:38:12.731Z"); return t}()),
	// 			Message: to.Ptr(""),
	// 			Parameters: map[string]*string{
	// 				"OutputBlobNameList": to.Ptr("[\"exampleoutput.csv\"]"),
	// 			},
	// 			PipelineName: to.Ptr("examplePipeline"),
	// 			RunEnd: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:38:12.731Z"); return t}()),
	// 			RunID: to.Ptr("2f7fdb90-5df1-4b8e-ac2f-064cfa58202b"),
	// 			RunStart: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:37:44.625Z"); return t}()),
	// 			Status: to.Ptr("Succeeded"),
	// 		},
	// 		{
	// 			AdditionalProperties: map[string]any{
	// 				"annotations": []any{
	// 				},
	// 				"runDimension": map[string]any{
	// 					"JobId": "84a3c493-0628-4b44-852f-ef5b3a11bdab",
	// 				},
	// 			},
	// 			InvokedBy: &armdatafactory.PipelineRunInvokedBy{
	// 				Name: to.Ptr("Manual"),
	// 				ID: to.Ptr("7c5fd7ef7e8a464b98b931cf15fcac66"),
	// 			},
	// 			LastUpdated: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:39:51.216Z"); return t}()),
	// 			Message: to.Ptr(""),
	// 			Parameters: map[string]*string{
	// 				"OutputBlobNameList": to.Ptr("[\"exampleoutput.csv\"]"),
	// 			},
	// 			PipelineName: to.Ptr("examplePipeline"),
	// 			RunID: to.Ptr("16ac5348-ff82-4f95-a80d-638c1d47b721"),
	// 			RunStart: to.Ptr(func() time.Time { t, _ := time.Parse(time.RFC3339Nano, "2018-06-16T00:39:49.274Z"); return t}()),
	// 			Status: to.Ptr("Cancelled"),
	// 	}},
	// }
}

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

JavaScript

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

/**
 * This sample demonstrates how to Query pipeline runs in the factory based on input filter conditions.
 *
 * @summary Query pipeline runs in the factory based on input filter conditions.
 * x-ms-original-file: specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/PipelineRuns_QueryByFactory.json
 */
async function pipelineRunsQueryByFactory() {
  const subscriptionId =
    process.env["DATAFACTORY_SUBSCRIPTION_ID"] || "12345678-1234-1234-1234-12345678abc";
  const resourceGroupName = process.env["DATAFACTORY_RESOURCE_GROUP"] || "exampleResourceGroup";
  const factoryName = "exampleFactoryName";
  const filterParameters = {
    filters: [
      {
        operand: "PipelineName",
        operator: "Equals",
        values: ["examplePipeline"],
      },
    ],
    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.pipelineRuns.queryByFactory(
    resourceGroupName,
    factoryName,
    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

dotnet

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

// Generated from example definition: specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/PipelineRuns_QueryByFactory.json
// this example is just showing the usage of "PipelineRuns_QueryByFactory" 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
RunFilterContent content = new RunFilterContent(DateTimeOffset.Parse("2018-06-16T00:36:44.3345758Z"), DateTimeOffset.Parse("2018-06-16T00:49:48.3686473Z"))
{
    Filters =
    {
    new RunQueryFilter(RunQueryFilterOperand.PipelineName,RunQueryFilterOperator.EqualsValue,new string[]
    {
    "examplePipeline"
    })
    },
};
await foreach (DataFactoryPipelineRunInfo item in dataFactory.GetPipelineRunsAsync(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

CLI

az datafactory pipeline-run query-by-factory --factory-name "exampleFactoryName" --filters operand="PipelineName" operator="Equals" values="examplePipeline" --last-updated-after "2018-06-16T00:36:44.3345758Z" --last-updated-before "2018-06-16T00:49:48.3686473Z" --resource-group "exampleResourceGroup"

Click here to learn more about the Azure CLI command.

範例回覆

狀態碼:

200

Date: Sat, 16 Jun 2018 00:40:01 GMT
X-Content-Type-Options: nosniff
x-ms-ratelimit-remaining-subscription-reads: 14989
x-ms-request-id: 2f955e10-c6df-45a7-97d4-81acdb8540cd
x-ms-correlation-request-id: 2f955e10-c6df-45a7-97d4-81acdb8540cd

{
  "value": [
    {
      "runId": "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b",
      "pipelineName": "examplePipeline",
      "parameters": {
        "OutputBlobNameList": "[\"exampleoutput.csv\"]"
      },
      "invokedBy": {
        "id": "80a01654a9d34ad18b3fcac5d5d76b67",
        "name": "Manual"
      },
      "runStart": "2018-06-16T00:37:44.6257014Z",
      "runEnd": "2018-06-16T00:38:12.7314495Z",
      "durationInMs": 28105,
      "status": "Succeeded",
      "message": "",
      "lastUpdated": "2018-06-16T00:38:12.7314495Z",
      "annotations": [],
      "runDimension": {
        "JobId": "79c1cc52-265f-41a5-9553-be65e736fbd3"
      }
    },
    {
      "runId": "16ac5348-ff82-4f95-a80d-638c1d47b721",
      "pipelineName": "examplePipeline",
      "parameters": {
        "OutputBlobNameList": "[\"exampleoutput.csv\"]"
      },
      "invokedBy": {
        "id": "7c5fd7ef7e8a464b98b931cf15fcac66",
        "name": "Manual"
      },
      "runStart": "2018-06-16T00:39:49.2745128Z",
      "runEnd": null,
      "durationInMs": null,
      "status": "Cancelled",
      "message": "",
      "lastUpdated": "2018-06-16T00:39:51.216097Z",
      "annotations": [],
      "runDimension": {
        "JobId": "84a3c493-0628-4b44-852f-ef5b3a11bdab"
      }
    }
  ]
}

定義

名稱	Description
CloudError	對象，定義 Azure Data Factory 錯誤響應的結構。
PipelineRun	管線執行的相關信息。
PipelineRunInvokedBy	提供啟動管線執行的實體名稱和標識碼。
PipelineRunsQueryResponse	清單管線會執行。
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。 允許的操作數可查詢管線執行為 PipelineName、RunStart、RunEnd 和 Status;若要查詢活動執行，則為 ActivityName、ActivityRunStart、ActivityRunEnd、ActivityType 和 Status，以及查詢觸發程式執行為 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。 允許針對管線執行排序的參數為 PipelineName、RunStart、RunEnd 和 Status;針對活動執行為 ActivityName、ActivityRunStart、ActivityRunEnd 和 Status;針對觸發程式執行，為 TriggerName、TriggerRunTimestamp 和 Status。

CloudError

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	錯誤訊息。
error.target	string	與錯誤相關聯的要求中的屬性名稱/路徑。

PipelineRun

管線執行的相關信息。

名稱	類型	Description
durationInMs	integer	管線執行的持續時間。
invokedBy	PipelineRunInvokedBy	啟動管線執行的實體。
isLatest	boolean	指出復原的管線執行是否在其群組中是最新的。
lastUpdated	string	管線執行事件的最後一個更新時間戳，格式為 ISO8601。
message	string	管線執行的訊息。
parameters	object	管線執行中使用的參數名稱、值組的完整或部分清單。
pipelineName	string	管線名稱。
runDimensions	object	管線執行所發出的執行維度。
runEnd	string	管線執行的結束時間ISO8601格式。
runGroupId	string	與管線執行的所有復原執行相互關聯的標識碼。
runId	string	執行的標識碼。
runStart	string	管線執行的開始時間ISO8601格式。
status	string	管線執行的狀態。 可能的值：Queued、InProgress、Succeeded、Failed、Canceling、Canceled

PipelineRunInvokedBy

提供啟動管線執行的實體名稱和標識碼。

名稱	類型	Description
id	string	啟動執行之實體的標識碼。
invokedByType	string	啟動執行之實體的類型。
name	string	啟動管線執行的實體名稱。
pipelineName	string	如果有的話，觸發執行之管線的名稱。
pipelineRunId	string	如果有任何情況，則觸發執行之管線的執行標識符。

PipelineRunsQueryResponse

清單管線會執行。

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	PipelineRun[]	管線執行的清單。

RunFilterParameters

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	在 或 之後，執行事件會以 'ISO 8601' 格式更新的時間。
lastUpdatedBefore	string	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

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。 允許的操作數可查詢管線執行為 PipelineName、RunStart、RunEnd 和 Status;若要查詢活動執行，則為 ActivityName、ActivityRunStart、ActivityRunEnd、ActivityType 和 Status，以及查詢觸發程式執行為 TriggerName、TriggerRunTimestamp 和 Status。
operator	RunQueryFilterOperator	要用於篩選的運算子。
values	string[]	篩選值的清單。

RunQueryFilterOperand

要用於篩選的參數名稱。 允許的操作數可查詢管線執行為 PipelineName、RunStart、RunEnd 和 Status;若要查詢活動執行，則為 ActivityName、ActivityRunStart、ActivityRunEnd、ActivityType 和 Status，以及查詢觸發程式執行為 TriggerName、TriggerRunTimestamp 和 Status。

名稱	類型	Description
ActivityName	string
ActivityRunEnd	string
ActivityRunStart	string
ActivityType	string
LatestOnly	string
PipelineName	string
RunEnd	string
RunGroupId	string
RunStart	string
Status	string
TriggerName	string
TriggerRunTimestamp	string

RunQueryFilterOperator

要用於篩選的運算子。

名稱	類型	Description
Equals	string
In	string
NotEquals	string
NotIn	string

RunQueryOrder

參數的排序順序。

名稱	類型	Description
ASC	string
DESC	string

RunQueryOrderBy

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。 允許針對管線執行排序的參數為 PipelineName、RunStart、RunEnd 和 Status;針對活動執行為 ActivityName、ActivityRunStart、ActivityRunEnd 和 Status;針對觸發程式執行，為 TriggerName、TriggerRunTimestamp 和 Status。

RunQueryOrderByField

要用於排序依據的參數名稱。 允許針對管線執行排序的參數為 PipelineName、RunStart、RunEnd 和 Status;針對活動執行為 ActivityName、ActivityRunStart、ActivityRunEnd 和 Status;針對觸發程式執行，為 TriggerName、TriggerRunTimestamp 和 Status。

名稱	類型	Description
ActivityName	string
ActivityRunEnd	string
ActivityRunStart	string
PipelineName	string
RunEnd	string
RunStart	string
Status	string
TriggerName	string
TriggerRunTimestamp	string