Vadym Doroshenko

It's made based on [PR](https://github.com/OpenMined/PyDP/commit/eadd992310a9606a5772bc99d570f52fafc8ba22)

This PR implements wrapper for [QuantileTree](https://github.com/google/differential-privacy/blob/main/cc/algorithms/quantile-tree.h) algorithm from Google C++ DP building block library.

Support max_contribution_per_user contribution bounding

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# Context ## Definitions _Contribution bounding_ is a process of limiting contributions by a single individual (or an entity represented by a privacy key) to the output dataset or its...

Absolute budget per aggregation

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# Context The workflow for computing DP aggregations with PipelineDP is the following (not important here steps are missing, [the full example](https://github.com/OpenMined/PipelineDP/blob/41b70a3c7e19b82024e2d0f44842aaab570440bd/examples/quickstart.ipynb)): ``` # Define the total budget. budget_accountant =...

# Context [DPEngine.aggregate](https://github.com/OpenMined/PipelineDP/blob/66012f04a94720ba2e5499c1c96edb3399b83287/pipeline_dp/dp_engine.py#L53) is an API function that performs DP aggregations. It takes [AggregateParams](https://github.com/OpenMined/PipelineDP/blob/66012f04a94720ba2e5499c1c96edb3399b83287/pipeline_dp/aggregate_params.py#L57) as an argument. `AggregateParams` is dataclass and specifies details of the computation which is performed. It...

# Context PipleineDP supports anonymzation with Beam RDD API ([example](https://github.com/OpenMined/PipelineDP/blob/main/examples/movie_view_ratings/run_on_spark.py)). It seems interesting to have the support of [Beam SQL API](https://beam.apache.org/documentation/dsls/sql/overview/). # Goal To investigate and to design BeamSQL API...

# Context PipleineDP supports anonymzation with Spark RDD API ([example](https://github.com/OpenMined/PipelineDP/blob/main/examples/movie_view_ratings/run_on_spark.py)). It seems interesting to have the support of [Spark SQL API](https://spark.apache.org/sql/). # Goal To investigate and to design SparkSQL API...

Create code examples for different tasks

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# Context Terminology can be found [here](https://pipelinedp.io/key-definitions/). There are 2 APIs: 1. **Core APIs** - which represent by public functions of DPEngine ([example of usage](https://github.com/OpenMined/PipelineDP/blob/main/examples/movie_view_ratings/run_all_frameworks.py)) 3. **High-level APIs**: `PrivatePCollection` (Beam),...