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.
Partition selection strategy (which is enum of TruncatedGeometric, LaplaceThresholding and GaussianThresholding) is a part of utility analysis parameters. So it should be part of the output as well. But before this PR it was set incorectly, namely configuration_index is used for finding what is partition selection for a fixed configuration of parameters. But configuration_index was not yet available in that moment. This PR fixes that by moving setting partition_selection_strategy later in the pipeline, when configuration_index is available
Partition selection strategy (which is enum of TruncatedGeometric, LaplaceThresholding and GaussianThresholding) is a part of utility analysis parameters. So it should be part of the output as well. But before this PR it was set incorectly, namely
configuration_indexis used for finding what is partition selection for a fixed configuration of parameters. Butconfiguration_indexwas not yet available in that moment. This PR fixes that by moving settingpartition_selection_strategylater in the pipeline, whenconfiguration_indexis available