PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch processing systems such as Apache Spark, Apache Beam, and more.
Apache Beam requires that all stage_names were different. pipeline_dp.BeamBackend object ensures the uniqueness of the Beam stage names. But it is required to have the same object BeamBackend for all operations in private_beam.py.
This PR implements does by introducing a module level variable _beam_backend for this.
dvadym
commented
1 year ago
Apache Beam requires that all stage_names were different.
pipeline_dp.BeamBackendobject ensures the uniqueness of the Beam stage names. But it is required to have the same objectBeamBackendfor all operations in private_beam.py.This PR implements does by introducing a module level variable
_beam_backendfor this.