How does sagmaker batch inference processes individual files?

Question

based on the documentation provided here , https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html, large dataset can be structured as shown below in a csv file. is it possible to have multiple files in this format for batch inference, is there any configuration that can be set , for it to process multiple files. Also, what other formats , beside csv can the batch inference handle?

```
Record1-Attribute1, Record1-Attribute2, Record1-Attribute3, ..., Record1-AttributeM
Record2-Attribute1, Record2-Attribute2, Record2-Attribute3, ..., Record2-AttributeM
...
...
RecordN-Attribute1, RecordN-Attribute2, RecordN-Attribute3, ..., RecordN-AttributeM  
```

Answer

If you have multiple files in S3 bucket for Batch Inference, general guidelines is set the number of workers/instances = multiple of number of files in S3 to process. In addition, you can set the [BatchStrategy](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html#sagemaker-CreateTransformJob-request-BatchStrategy) to MultiLine in order to speed up the processing. 
To enable parallel processing, set the MaxConcurrentTransforms to 0 to start off, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm.

How does sagmaker batch inference processes individual files?

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