Can an Apache Beam batch process be restarted from a checkpoint?
Dataflow batch pipelines discard all intermediate results when the pipeline terminates (successfully or fails).
Currently you would need to add points within the pipeline where the intermediate data is materialized and then on failure you could launch a new pipeline which is a subset of your existing pipeline that reads the intermediate results and continues processing.
I have a long-running Apache Beam batch analysis process on Google Cloud Dataflow that failed partway through.  To save time and cost, is it possible to update my code to handle the failure, and re-run from the failure point using cached intermediate checkpoints?