Apache Mahout

About Apache Mahout

An environment for quickly creating scalable, performant machine learning applications. Mahout provides mathematically expressive Scala DSL and supports Apache Spark and Apache Flink backends for distributed linear algebra operations.

Key Features

• 1Distributed linear algebra library for scalable ML on Spark and Hadoop
• 2Samsara DSL for writing distributed math algorithms in Scala and R
• 3Collaborative filtering algorithms for recommendation systems
• 4Dimensionality reduction: PCA, SVD, and Random Projections at scale
• 5Classification and clustering on distributed datasets

How Python Data Engineers Use Apache Mahout

Python data engineers interact with Apache Mahout indirectly — Mahout's distributed linear algebra runs on Spark, which Python engineers invoke via PySpark. Mahout's recommendation and clustering algorithms are used in feature engineering pipelines for ML applications where standard scikit-learn algorithms are too slow for the dataset size.