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Pipeline Runs - Query By Factory

服务:

Data Factory

API 版本:

2018-06-01

查询管道根据输入筛选条件在工厂中运行。

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

URI 参数

名称	在	必需	类型	说明
factoryName	path	True	string	工厂名称。 正则表达式模式: ^[A-Za-z0-9]+(?:-[A-Za-z0-9]+)*$
resourceGroupName	path	True	string	资源组名称。 正则表达式模式: ^[-\w\._\(\)]+$
subscriptionId	path	True	string	订阅标识符。
api-version	query	True	string	API 版本。

请求正文

名称	必需	类型	说明
lastUpdatedAfter	True	string	以“ISO 8601”格式更新运行事件的时间。
lastUpdatedBefore	True	string	以“ISO 8601”格式更新运行事件的时间或之前的时间。
continuationToken		string	用于获取下一页结果的延续标记。 第一页为 Null。
filters		RunQueryFilter[]	筛选器列表。
orderBy		RunQueryOrderBy[]	OrderBy 选项的列表。

响应

名称	类型	说明
200 OK	PipelineRunsQueryResponse	没问题。
Other Status Codes	CloudError	从Azure 数据工厂服务收到的错误响应。

安全性

azure_auth

Azure Active Directory OAuth2 Flow。

类型: oauth2
流向: implicit
授权 URL: https://login.microsoftonline.com/common/oauth2/authorize

作用域

名称	说明
user_impersonation	模拟用户帐户

示例

PipelineRuns_QueryByFactory

示例请求

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.

示例响应

状态代码:

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"
      }
    }
  ]
}

定义

名称	说明
CloudError	定义Azure 数据工厂错误响应结构的对象。
PipelineRun	有关管道运行的信息。
PipelineRunInvokedBy	提供启动管道运行的实体名称和 ID。
PipelineRunsQueryResponse	列表管道运行。
RunFilterParameters	用于列出运行的查询参数。
RunQueryFilter	用于列出运行的查询筛选器选项。
RunQueryFilterOperand	要用于筛选的参数名称。 允许用于查询管道运行的操作数为 PipelineName、RunStart、RunEnd 和 Status;查询活动运行为 ActivityName、ActivityRunStart、ActivityRunEnd、ActivityType 和 Status，查询触发器运行为 TriggerName、TriggerRunTimestamp 和 Status。
RunQueryFilterOperator	要用于筛选的运算符。
RunQueryOrder	参数的排序顺序。
RunQueryOrderBy	一个 对象，用于按列表运行的选项提供顺序。
RunQueryOrderByField	要用于排序依据的参数名称。 允许按 管道运行排序的参数为 PipelineName、RunStart、RunEnd 和 Status;对于活动运行，为 ActivityName、ActivityRunStart、ActivityRunEnd 和 Status;的触发器运行为 TriggerName、TriggerRunTimestamp 和 Status。

CloudError

定义Azure 数据工厂错误响应结构的对象。

名称	类型	说明
error.code	string	错误代码。
error.details	CloudError[]	包含其他错误详细信息的数组。
error.message	string	错误消息。
error.target	string	与错误关联的请求中的属性名称/路径。

PipelineRun

有关管道运行的信息。

名称	类型	说明
durationInMs	integer	管道运行的持续时间。
invokedBy	PipelineRunInvokedBy	启动管道运行的实体。
isLatest	boolean	指示恢复的管道运行是否是其组中的最新运行。
lastUpdated	string	管道运行事件的上次更新时间戳，采用ISO8601格式。
message	string	来自管道运行的消息。
parameters	object	管道运行中使用的参数名称、值对的完整或部分列表。
pipelineName	string	管道名称。
runDimensions	object	管道运行发出的运行维度。
runEnd	string	管道运行的结束时间ISO8601格式。
runGroupId	string	关联管道运行的所有恢复运行的标识符。
runId	string	运行的标识符。
runStart	string	管道运行的开始时间ISO8601格式。
status	string	管道运行的状态。 可能的值：Queued、InProgress、Succeeded、Failed、Canceling、Canceled

PipelineRunInvokedBy

提供启动管道运行的实体名称和 ID。

名称	类型	说明
id	string	启动运行的实体的 ID。
invokedByType	string	启动运行的实体的类型。
name	string	启动管道运行的实体的名称。
pipelineName	string	触发运行的管道的名称（如果有）。
pipelineRunId	string	触发运行的管道的运行 ID（如果有）。

PipelineRunsQueryResponse

列表管道运行。

名称	类型	说明
continuationToken	string	如果存在任何剩余结果，则为获取下一页结果的延续标记，否则为 null。
value	PipelineRun[]	管道运行列表。

RunFilterParameters

用于列出运行的查询参数。

名称	类型	说明
continuationToken	string	用于获取下一页结果的延续标记。 第一页为 Null。
filters	RunQueryFilter[]	筛选器列表。
lastUpdatedAfter	string	以“ISO 8601”格式更新运行事件的时间。
lastUpdatedBefore	string	以“ISO 8601”格式更新运行事件的时间或之前的时间。
orderBy	RunQueryOrderBy[]	OrderBy 选项的列表。

RunQueryFilter

用于列出运行的查询筛选器选项。

名称	类型	说明
operand	RunQueryFilterOperand	要用于筛选的参数名称。 允许用于查询管道运行的操作数为 PipelineName、RunStart、RunEnd 和 Status;查询活动运行为 ActivityName、ActivityRunStart、ActivityRunEnd、ActivityType 和 Status，查询触发器运行为 TriggerName、TriggerRunTimestamp 和 Status。
operator	RunQueryFilterOperator	要用于筛选的运算符。
values	string[]	筛选器值的列表。

RunQueryFilterOperand

要用于筛选的参数名称。 允许用于查询管道运行的操作数为 PipelineName、RunStart、RunEnd 和 Status;查询活动运行为 ActivityName、ActivityRunStart、ActivityRunEnd、ActivityType 和 Status，查询触发器运行为 TriggerName、TriggerRunTimestamp 和 Status。

名称	类型	说明
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

要用于筛选的运算符。

名称	类型	说明
Equals	string
In	string
NotEquals	string
NotIn	string

RunQueryOrder

参数的排序顺序。

名称	类型	说明
ASC	string
DESC	string

RunQueryOrderBy

一个 对象，用于按列表运行的选项提供顺序。

名称	类型	说明
order	RunQueryOrder	参数的排序顺序。
orderBy	RunQueryOrderByField	要用于排序依据的参数名称。 允许按 管道运行排序的参数为 PipelineName、RunStart、RunEnd 和 Status;对于活动运行，为 ActivityName、ActivityRunStart、ActivityRunEnd 和 Status;的触发器运行为 TriggerName、TriggerRunTimestamp 和 Status。

RunQueryOrderByField

要用于排序依据的参数名称。 允许按 管道运行排序的参数为 PipelineName、RunStart、RunEnd 和 Status;对于活动运行，为 ActivityName、ActivityRunStart、ActivityRunEnd 和 Status;的触发器运行为 TriggerName、TriggerRunTimestamp 和 Status。

名称	类型	说明
ActivityName	string
ActivityRunEnd	string
ActivityRunStart	string
PipelineName	string
RunEnd	string
RunStart	string
Status	string
TriggerName	string
TriggerRunTimestamp	string