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Bodo 2021.12 Release (Date: 12/29/2021)

This release includes many new features and usability improvements. Overall, 67 code patches were merged since the last release.

New Features and Improvements

  • Significantly upgrades to the Bodo documentation to improve the developer experience

  • Improvements to documentation and unsupported attribute handling for Pandas APIs

  • Significant enhancements to objmode user experience and robustness, such as automatic output data type checking and automatic conversion if possible

  • Improved support for re package, such as support for re flags, better support for returning None when necessary, and better catching of unsupported corner cases

  • Support caching functions that take a string as input and create a file path using concatenation. For example:

    def f(folder):
      return pd.read_parquet(folder + "/example.pq")
  • Connectors:

    • Improved read_parquet runtime performance when reading from S3
    • Decreased compilation time for read_csv on DataFrames with large number of columns (100)
  • Improved compilation time for dataframes with large number of columns (>10,000)

  • Improved NA handling in User Defined Functions with df.apply when functions are not inlined

  • Support for using when passing the logger as an argument to a JIT function

  • Support for

  • Simpler bodo.scatterv usage from regular Python. Other ranks are ignored but not required to have None as their data

  • Improved support for map arrays in various operations

  • Support feature_importances_ of XGBoost

  • Support predict_proba and predict_log_proba in Scikit-learn classifier algorithms

  • Pandas:

    • Support for Bodo specific argument _bodo_upcast_to_float64 in pd.read_csv. This can be used when all data is numeric but schema inference cannot accurate predict data types.
    • Support for using DataFrame.to_parquet with "wide" DataFrames with large number of columns
    • Support for storing a DateTimeIndex with DataFrame.to_parquet
    • Support for the 'method' argument in DataFrame.fillna and Series.fillna
    • Support for Series.bfill, Series.ffill, Series.pad, and Series.backfill
    • Support for Series.keys
    • Support for Series.infer_objects and DataFrame.infer_objects
    • Decreased runtime when calling .astype("categorical") on Series with large numbers of categories