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Bodo 2020.02 Release (Date: 02/14/2020)

New Features and Improvements

  • Bodo now utilizes the following packages:

    -   pandas >= 1.0.0
    -   numba 0.48.0
    -   Apache Arrow 0.16.0
    
  • Custom S3 endpoint is supported as well as S3-like object storage systems such as MinIO

  • Reading and writing of parquet files with S3 is more robust

  • Parquet read now supports reading columns where elements are list of strings

  • pandas.read_csv() now also accepts a list of column names for the parse_date parameter

  • pandas groupby.agg() supports list of functions for a column:

    df = pd.DataFrame(
        {"A": [2, 1, 1, 1, 2, 2, 1], "B": ["a", "b", "c", "c", "b", "c", "a"]}
    )
    gb = df.groupby("B").agg({"A": ["sum", "mean"]})
    
  • pandas groupby.agg() now supports a tuple of built-in functions:

    gb = df.groupby("B")["A"].agg(("sum", "median"))
    
  • User-defined functions can now be used with groupby.agg() and constant dict:

    gb = df.groupby("B").agg({"A": my_function})
    
  • The compilation time and run time have been improved for pandas groupby with median, cumsum, and cumprod.

  • pandas groupby now supports cumsum, max, min, prod, sum functions for string columns.

  • pandas groupby.agg() now supports mixing median and nunique with other functions, and use of multiple "cumulative" operations in the same groupby (example: cumsum, cumprod, etc).

  • Selecting groupby columns using attribute is now possible:

    df = pd.DataFrame(
        {"A": [2, 1, 1, 1, 2, 2, 1], "B": [3, 5, 6, 5, 4, 4, 3]}
    )
    df.groupby('A').B.sum()
    
  • pandas Series.str.extractall, Series.all() and Series.any() are supported

  • Support for returning MultiIndex in groupby operations

  • Various forms of UDFs in df.apply and Series.map are supported

  • Comparison of datetime fields with datetime constants is now possible

  • Converting date and datetime of Python datetime module to pandas Timestamp is now supported

  • Conversion to float using float class as dtype for pandas Series.astype() is now supported:

    S = pd.Series(['1', '2', '3'])
    S.astype(float)
    

Bug Fix

  • Fixed a memory leak issue when returning a dataframe from a Bodo function
  • pandas DataFrame.sort_values() now returns correct output for input cases that contain NA
  • Groupby.agg: explicit column selection when using constant dictionary is no longer required
  • Fixed an issue that Bodo always dropped the index in reset_index()
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