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.
This PR implements computing sensitivity from max_contributions contribtion bounding parameter, for COUNT, PRIVACY_ID_COUNT, SUM, MEAN. Other DP aggregations are not yet supported. It finishes support of applying DP noise according to max_contributions contribution bounding.
This PR implements computing sensitivity from
max_contributions
contribtion bounding parameter, forCOUNT, PRIVACY_ID_COUNT, SUM, MEAN
. Other DP aggregations are not yet supported. It finishes support of applying DP noise according tomax_contributions
contribution bounding.