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#1. You can create and use JSON template files with Azure CLI to create Batch pools, jobs, and tasks.
See Use Azure Batch CLI templates and file transfer
#2. You can also Process large-scale datasets by using Data Factory and Batch
To process a large JSON file using Azure Batch, Basic workflow will look something like this:
- Split the large JSON file into smaller chunks that can be processed independently, either programmatically or using tools for it. Save the chunks to Azure Storage account/ Blob Storage.
- Create a new Azure Batch account. You'll need to specify a unique name, subscription, resource group, and location for your account.
- In the Azure Batch account, create a new pool of compute nodes that will process the JSON chunks. You can choose the number of nodes, their size, and the operating system.
- Write a script or batch application that will process the JSON chunks. This application should read a JSON chunk from the Azure Blob Storage, process it, and write the results back to storage or another external service.
- Upload the application files that your tasks will run to the Applications section of your Azure Batch account.
- In the Azure Batch account, create a new job that will run your application. You'll need to specify the pool of compute nodes to use, and any other settings required for your specific workload.
- For each JSON chunk in Azure Blob Storage, create a new task in the Batch job. Each task should reference the application package you uploaded earlier, and include any required input data and command-line arguments to process the JSON chunk. As each task completes, it can upload its output to Azure Storage.
- Use the Azure portal or Batch SDKs to monitor the progress of your job and tasks. Once all tasks have completed, retrieve the processed results from Azure Blob Storage or your chosen external service.
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