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Bodo 2023.9 Release (Date: 09/01/2023)

New Features and Improvements

Compilation / Performance improvements:

  • BodoSQL generated plans have been further optimized to reduce runtime, compile time, and memory usage.
  • Performance and compilation time improvements to several window functions:
    • LEAD
    • LAG
    • AVG
    • VARIANCE_POP and equivalent functions
    • VARIANCE_SAMP and equivalent functions
    • STDDEV_POP and equivalent functions
    • STDDEV_SAMP and equivalent functions
    • FIRST_VALUE
    • LAST_VALUE
    • RATIO_TO_REPORT

Python coverage:

  • Partial support for the np.matrix type with the following functionality (non-distributed):

    • np.asmatrix to convert a scalar, 1D array, 2D array, list of scalars, or list of 1D arrays to a matrix
    • np.asarray to convert a matrix to a 2D array
    • Addition and subtraction with + and -
    • Matrix multiplication with *, @ or np.dot
    • Calling len() on a Matrix
    • Using .ndim, .shape and .T (non-distributed) on a Matrix

  • Support for the following Numpy functions:

    • np.interp non-distributed (added support for keyword arguments left and right)
    • np.tile (added support for specific patterns, see Numpy docs)
    • np.linalg.norm (added support for keyword argument axis=1 when the input is a 2D array)
    • np.nan_to_num
    • np.dot (added support for heterogeneous typing between integer & float array inputs)
    • scipy.fftpack.fftshift (non-distributed)
    • scipy.fftpack.fft2 (non-distributed)

BodoSQL:

  • Added support for HASH(*)
  • Added support for PERCENTILE_CONT and PERCENTILE_DISC (non-window support)

2023.9.5 New Features and Improvements

Compilation / Performance improvements:

  • BodoSQL generated plans have been further optimized to reduce runtime and memory usage.
  • Support for executing UNION in vectorized mode
  • Support for executing ARRAY_AGG on numeric types in a GROUP BY

2023.9.6 New Features and Improvements

Fix critical bugs in vectorized execution mode.

  • BodoSQL generated plans have been further optimized to reduce runtime and memory usage.
  • GET_PATH and JSON field accesses via : are supported in some usages.