Apache Hivemall is a scalable machine learning library that runs on Apache Hive, Apache Spark, and Apache Pig. Hivemall is designed to be scalable to the number of training instances as well as the number of training features.

Find more examples on our user guide and find a brief introduction to Hivemall in this slide.

Support is through [email protected], not by a direct e-mail.

If you are planning to contribute to this repository, we first request you to create an issue at our JIRA page even if the topic is not related to source code itself (e.g., documentation, new idea and proposal).

All Hivemall functions are defined under resources/ddl. In order to update the definition files, the following script helps inserting function name and class path of your new UDF:

$ ./bin/update_ddls.sh

Moreover, don't forget to update function list in the document as well:

$ ./bin/update_func_md.sh

Note that, before creating a pull request including Java code, please make sure your code follows our coding conventions by applying formatter:

$ ./bin/format_code.sh