70-475日本語 無料問題集「Microsoft Design and Implement Big Data Analytics Solutions (70-475日本語版)」
正解：
Explanation
Box 1: Every three days at 10.00
anchorDateTime defines the absolute position in time used by the scheduler to compute dataset slice boundaries.
"frequency": "<Specifies the time unit for data slice production. Supported frequency: Minute, Hour, Day, Week, Month>",
"interval": "<Specifies the interval within the defined frequency. For example, frequency set to 'Hour' and interval set to 1 indicates that new data slices should be produced hourly> Box 2: Every minute up to three times.
retryInterval is the wait time between a failure and the next attempt. This setting applies to present time. If the previous try failed, the next try is after the retryInterval period.
Example: 00:01:00 (1 minute)
Example: If it is 1:00 PM right now, we begin the first try. If the duration to complete the first validation check is 1 minute and the operation failed, the next retry is at 1:00 + 1min (duration) + 1min (retry interval) =
1:02 PM.
For slices in the past, there is no delay. The retry happens immediately.
retryTimeout is the timeout for each retry attempt.
maximumRetry is the number of times to check for the availability of the external data.
正解：
Explanation
Perform these operations in the following order:
* Create a data factory.
* Create linked services.
* Create datasets.
* Create a pipeline.
Step 1: New-AzureRMDataFactory
Create a data factory
The New-AzureRmDataFactory cmdlet creates a data factory with the specified resource group name and location.
Step 2: New-AzureRMDataFactoryLinkedService
Create linked services in a data factory to link your data stores and compute services to the data factory.
The New-AzureRmDataFactoryLinkedService cmdlet links a data store or a cloud service to Azure Data Factory.
Step 3: New-AzureRMDataFactoryDataset
You define a dataset that represents the data to copy from a source to a sink. It refers to the Azure Storage linked service you created in the previous step.
The New-AzureRmDataFactoryDataset cmdlet creates a dataset in Azure Data Factory.
Step 4: New-AzureRMDataFactoryPipeline
You create a pipeline.
The New-AzureRmDataFactoryPipeline cmdlet creates a pipeline in Azure Data Factory.
References:
https://docs.microsoft.com/en-us/azure/data-factory/quickstart-create-data-factory-powershell
https://docs.microsoft.com/en-us/powershell/module/azurerm.datafactories/new-azurermdatafactory
