Hivemall
A scalable machine learning library that runs on Apache Hive, Spark, and Pig for distributed ML directly in SQL.
What is Hivemall?
Apache Hivemall is a scalable machine learning library that runs on big data processing frameworks like Apache Hive, Spark, and Pig. It provides machine learning algorithms as SQL functions, allowing users to train models and make predictions directly within SQL queries on distributed datasets. The library solves the problem of integrating ML workflows into existing SQL-based big data environments without moving data to specialized ML systems.
Data engineers, data scientists, and big data developers who work with Apache Hive, Spark, or Pig and want to perform machine learning tasks directly in SQL without switching contexts or tools.
Developers choose Hivemall for its seamless integration with SQL-based big data platforms, enabling scalable ML without complex data pipelines. Its unique selling point is bringing machine learning capabilities directly to distributed SQL queries, making ML accessible and efficient for large-scale data processing.
Overview
Mirror of Apache Hivemall (incubating)
Use Cases
Best For
- Performing machine learning on massive datasets stored in Hive or Spark
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