s3DataDistributionType property
If you want Amazon SageMaker to replicate the entire dataset on each ML
compute instance that is launched for model training, specify
FullyReplicated.
If you want Amazon SageMaker to replicate a subset of data on each ML
compute instance that is launched for model training, specify
ShardedByS3Key. If there are n ML compute instances
launched for a training job, each instance gets approximately 1/n of
the number of S3 objects. In this case, model training on each machine uses
only the subset of training data.
Don't choose more ML compute instances for training than available S3 objects. If you do, some nodes won't get any data and you will pay for nodes that aren't getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms.
In distributed training, where you use multiple ML compute EC2 instances,
you might choose ShardedByS3Key. If the algorithm requires
copying training data to the ML storage volume (when
TrainingInputMode is set to File), this copies
1/n of the number of objects.
Implementation
final S3DataDistribution? s3DataDistributionType;