ApacheCon Europe 2019

Apache Hivemall Meets PySpark: Scalable Machine Learning with Hive, Spark, and Python @ ApacheCon Europe 2019

Abstract

Apache Hivemall is a collection of Hive user-defined functions for machine learning (ML). The tool enables us to solve a wide variety of ML-related problems through the scalable SQL-like interface to Hive. To give a motivating example, simple regression and classification model can be efficiently trained by just executing 10 lines of a query.

This session demonstrates such Hivemall functionality with a special focus on integration with Apache Spark; the Hivemall contributors have been actively working on Spark integration since the project has entered the Apache Incubator. In particular, we deep-dive into how it works in PySpark.

In PySpark, SparkSession with Hive support enabled gives direct access to the Hivemall capabilities at each of preprocessing, training, prediction, and evaluation phases. That is, we can simultaneously leverage the scalability of Hive/Spark and flexibility of Python ecosystem. We will eventually see how the combination can be a deeply satisfying way to implement a practical end-to-end ML solution.

Slides

Video

  書いた人: たくち

たくちです。長野県出身、カナダ・バンクーバー在住のソフトウェアエンジニア。これまでB2B/B2Cの各領域で、Web技術・データサイエンス・機械学習のプロダクト化および顧客への導入支援・コンサルティング、そして関連分野のエバンジェリズムに携わってきました。現在はフリーランスとして活動を続けつつ、アフリカ・マラウイにて1年間の国際ボランティアに従事中。詳しい経歴はレジュメ を参照ください。いろいろなまちを走って、時に自然と戯れながら、その時間その場所の「日常」を生きています。ご意見・ご感想およびお仕事のご相談は [email protected] まで。