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H2O Sparkling Water Integration

H2O Sparkling Water Integration

1
posts
2026

H2O Sparkling Water enables users to combine H2O's machine learning algorithms with Apache Spark's data processing capabilities. It allows for seamless integration of Spark SQL queries, H2O model building and prediction, and subsequent use of results within Spark. The system supports driving computation from Scala, R, and Python, and offers easy deployment of H2O models (POJOs/MOJOs) for scoring within any environment. It is designed to run as a regular Spark application, initializing H2O services and accessing data from both Spark and H2O data structures. The product is available for various Spark versions and cloud platforms like Azure, AWS, and Google Cloud.

2026

H2O Sparkling Water

6/24/2026

This post introduces H2O Sparkling Water, a product that integrates H2O's machine learning algorithms with Apache Spark. It details how Sparkling Water allows users to leverage H2O's distributed ML algorithms (Random Forest, GLM, GBM, XGBoost, GLRM, Word2Vec, etc.) within a Spark environment. Key features include driving computation from Scala, R, and Python, using the H2O Flow UI, and easy deployment of POJOs/MOJOs for scoring. The architecture is described as a regular Spark application that initializes H2O services and accesses data from Spark and H2O structures. Download options for various Spark versions and cloud integrations are provided.