Note
This documentation is for a prior release of Kinetica. For the latest documentation, click here.
The following are complete examples of the implementation & execution of User-Defined Functions (UDFs) in the Python UDF API.
- Example UDF (CUDA) - cuBLAS
- Example of various computations, making use of the scikit-CUDA interface for making CUDA calls from Python. This UDF uses CUDA libraries and must be run on a CUDA build of Kinetica. It also involves a Python package that must be installed before the UDF is run.
- Example UDF (Non-CUDA) - Sum of Squares
- Example of the computation of the sum of squares, summing the squares of input table columns and storing the result in an output table. This UDF does not use CUDA libraries and can be run on an Intel build of Kinetica.
- Example UDF (Non-CUDA) - Distributed Model
- Example of how to build multiple models based on distributed data and combine them into an ensemble. This UDF does not use CUDA libraries and can be run on an Intel build of Kinetica.
- Example UDF (Non-CUDA) - Pandas
- Example of how to utilize pandas dataframes in UDFs and how to insert the dataframes into Kinetica. This UDF does not use CUDA libraries and can be run on an Intel build of Kinetica.