Pipeline Runs - Get

Odwołanie

Usługa:: Data Factory

Wersja interfejsu API:: 2018-06-01

Pobierz przebieg potoku według jego identyfikatora przebiegu.

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

Parametry identyfikatora URI

Nazwa	W	Wymagane	Typ	Opis
factoryName	path	True	string minLength: 3 maxLength: 63 pattern: ^[A-Za-z0-9]+(?:-[A-Za-z0-9]+)*$	Nazwa fabryki.
resourceGroupName	path	True	string minLength: 1 maxLength: 90 pattern: ^[-\w\._\(\)]+$	Nazwa grupy zasobów.
runId	path	True	string	Identyfikator przebiegu potoku.
subscriptionId	path	True	string	Identyfikator subskrypcji.
api-version	query	True	string	Wersja interfejsu API.

Odpowiedzi

Nazwa	Typ	Opis
200 OK	PipelineRun	OK.
Other Status Codes	CloudError	Odebrano odpowiedź o błędzie z usługi Azure Data Factory.

Zabezpieczenia

azure_auth

Przepływ protokołu OAuth2 usługi Azure Active Directory.

Typ: oauth2
Flow: implicit
Adres URL autoryzacji: https://login.microsoftonline.com/common/oauth2/authorize

Zakresy

Nazwa	Opis
user_impersonation	personifikacja konta użytkownika

Przykłady

PipelineRuns_Get

Przykładowe żądanie

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


/**
 * Samples for PipelineRuns Get.
 */
public final class Main {
    /*
     * x-ms-original-file:
     * specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/PipelineRuns_Get.json
     */
    /**
     * Sample code: PipelineRuns_Get.
     * 
     * @param manager Entry point to DataFactoryManager.
     */
    public static void pipelineRunsGet(com.azure.resourcemanager.datafactory.DataFactoryManager manager) {
        manager.pipelineRuns().getWithResponse("exampleResourceGroup", "exampleFactoryName",
            "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b", 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 pipeline_runs_get.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.get(
        resource_group_name="exampleResourceGroup",
        factory_name="exampleFactoryName",
        run_id="2f7fdb90-5df1-4b8e-ac2f-064cfa58202b",
    )
    print(response)


# x-ms-original-file: specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/PipelineRuns_Get.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"

	"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_Get.json
func ExamplePipelineRunsClient_Get() {
	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().Get(ctx, "exampleResourceGroup", "exampleFactoryName", "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b", 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.PipelineRun = armdatafactory.PipelineRun{
	// 	AdditionalProperties: map[string]any{
	// 		"annotations": []any{
	// 		},
	// 	},
	// 	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"),
	// }
}

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 Get a pipeline run by its run ID.
 *
 * @summary Get a pipeline run by its run ID.
 * x-ms-original-file: specification/datafactory/resource-manager/Microsoft.DataFactory/stable/2018-06-01/examples/PipelineRuns_Get.json
 */
async function pipelineRunsGet() {
  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 credential = new DefaultAzureCredential();
  const client = new DataFactoryManagementClient(credential, subscriptionId);
  const result = await client.pipelineRuns.get(resourceGroupName, factoryName, runId);
  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/PipelineRuns_Get.json
// this example is just showing the usage of "PipelineRuns_Get" 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
string runId = "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b";
DataFactoryPipelineRunInfo result = await dataFactory.GetPipelineRunAsync(runId);

Console.WriteLine($"Succeeded: {result}");

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 pipeline-run show --factory-name "exampleFactoryName" --resource-group "exampleResourceGroup" --run-id "2f7fdb90-5df1-4b8e-ac2f-064cfa58202b"

Click here to learn more about the Azure CLI command.

Przykładowa odpowiedź

Kod stanu:: 200

Date: Sat, 16 Jun 2018 00:40:02 GMT
X-Content-Type-Options: nosniff
x-ms-ratelimit-remaining-subscription-reads: 14988
x-ms-request-id: 6d9de9bd-a412-4a6f-8b9e-37d369323646
x-ms-correlation-request-id: 6d9de9bd-a412-4a6f-8b9e-37d369323646

{
  "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": []
}

Definicje

Nazwa	Opis
CloudError	Obiekt, który definiuje strukturę odpowiedzi błędu usługi Azure Data Factory.
PipelineRun	Informacje o uruchomieniu potoku.
PipelineRunInvokedBy	Zawiera nazwę i identyfikator jednostki, który uruchomił uruchomienie potoku.

CloudError

Objekt

Obiekt, który definiuje strukturę odpowiedzi błędu usługi Azure Data Factory.

Nazwa	Typ	Opis
error.code	string	Kod błędu.
error.details	CloudError[]	Tablica z dodatkowymi szczegółami błędu.
error.message	string	Komunikat o błędzie.
error.target	string	Nazwa/ścieżka właściwości w żądaniu skojarzonym z błędem.

PipelineRun

Objekt

Informacje o uruchomieniu potoku.

Nazwa	Typ	Opis
durationInMs	integer	Czas trwania uruchomienia potoku.
invokedBy	PipelineRunInvokedBy	Jednostka, która uruchomiła przebieg potoku.
isLatest	boolean	Wskazuje, czy odzyskane uruchomienie potoku jest najnowsze w swojej grupie.
lastUpdated	string (date-time)	Ostatni zaktualizowany znacznik czasu zdarzenia uruchomienia potoku w formacie ISO8601.
message	string	Komunikat z uruchomienia potoku.
parameters	object	Pełna lub częściowa lista nazw parametrów, para wartości używana w przebiegu potoku.
pipelineName	string	Nazwa rurociągu.
runDimensions	object	Uruchom wymiary emitowane przez przebieg potoku.
runEnd	string (date-time)	Godzina zakończenia uruchomienia potoku w formacie ISO8601.
runGroupId	string	Identyfikator, który koreluje wszystkie uruchomienia odzyskiwania przebiegu potoku.
runId	string	Identyfikator przebiegu.
runStart	string (date-time)	Godzina rozpoczęcia uruchomienia potoku w formacie ISO8601.
status	string	Stan uruchomienia potoku. Możliwe wartości: Kolejkowane, InProgress, Powodzenie, Niepowodzenie, Anulowanie, Anulowane

PipelineRunInvokedBy

Objekt

Zawiera nazwę i identyfikator jednostki, który uruchomił uruchomienie potoku.

Nazwa	Typ	Opis
id	string	Identyfikator jednostki, która uruchomiła przebieg.
invokedByType	string	Typ jednostki, która uruchomiła przebieg.
name	string	Nazwa jednostki, która uruchomiła uruchomienie potoku.
pipelineName	string	Nazwa potoku, który wyzwolił przebieg, jeśli istnieje.
pipelineRunId	string	Identyfikator przebiegu potoku, który wyzwolił przebieg, jeśli istnieje.