Overview

Welcome to the H2O Sparkling Water documentation site! This document describes how to install and run Sparkling Water.

Depending on your area of interest, select a learning path from the sidebar, or look at the full content outline below. To view Sparkling Water examples, please visit the Sparkling Water GitHub repository at https://github.com/h2oai/sparkling-water/tree/rel-2.2/examples.

Have questions about Sparkling Water? Post them on Stack Overflow using the sparkling-water tag, or join the chat on Gitter.

Contents

• About Sparkling Water
• Typical Use Case
• Sparkling Water Requirements
• Design
  • Supported Platforms
  • Supported Data Sources
  • Supported Data Formats
  • Provided Primitives
  • Spark - H2O Frame Mapping
  • Data Sharing
• Configuration
  • Sparkling Water Configuration Properties
  • Memory Allocation
  • Sparkling Water Tuning
  • Enforce System-Level Command Line Arguments in External Backend on YARN
• Deployment
  • Sparkling Water Backends
  • Importing H2O Mojo
  • Deploying PySparkling Pipeline Models
• How to…
  • Extending H2O Jar Manually
  • Calling H2O Algorithms
  • Running Sparkling Water
  • Changing the Default Port
  • Use Sparkling Water in Windows Environments
  • Use RSparkling in Windows Environments
  • References
  • Enabling SSL
  • Enabling LDAP
  • Enabling Kerberos Authentication
  • Spark Frame <–> H2O Frame Conversions
  • H2O Frame as Spark’s Data Source
  • Creating H2OFrame from an Existing Key
  • Using Grid Search GBM in Spark Pipelines
  • Change Sparkling Shell Logging Level
  • Change Sparkling Shell Logs Location
  • Obtain Sparkling Water Logs
  • Use Sparkling Water with Amazon EMR
  • Using Sparkling Water with Microsoft Azure HDInsight - Beta
  • Download H2O Logs from Databricks Cloud
  • Running RSparkling on Databricks Azure Cluster
  • Running Sparkling Water on Databricks Azure Cluster
  • Running PySparkling on Databricks Azure Cluster
  • Sparkling Water and Zeppelin
  • Use Sparkling Water via Spark Packages
• Development
  • Build Sparkling Water
  • Integration Tests
  • Running Sparkling Water Examples
  • Running Unit Tests
  • Sparkling Water REST API
• PySparkling
  • What is H2O?
  • What is Spark?
  • What is Sparkling Water?
  • What is PySparkling?
  • PySparkling and Spark Version
  • Setup and Installation
  • Building PySparkling with Non-Default Spark Version
  • The Sparkling Water Python Module
• RSparkling
  • Installation of SparklyR & Spark
  • Install H2O
  • Install rsparkling
  • RSparkling & SparklyR Configuration
• Using RSparkling
  • H2OContext & Flow
  • H2O with Spark DataFrames
  • Obtaining Logs
  • Disconnect from Spark
  • Machine Learning with RSparkling & H2O
  • Additional Resources
• Frequently Asked Questions
• Change Log
  • v2.2.21 (2018-08-01)
  • v2.2.20 (2018-07-16)
  • v2.2.19 (2018-06-18)
  • v2.2.18 (2018-06-18)
  • v2.2.17 (2018-06-13)
  • v2.2.16 (2018-05-23)
  • v2.2.15 (2018-05-18)
  • v2.2.14 (2018-05-15)
  • v2.2.13 (2018-05-02)
  • v2.2.12 (2018-04-19)
  • v2.2.11 (2018-03-29)
  • v2.2.10 (2018-03-08)
  • v2.2.9 (2018-02-26)
  • v2.2.8 (2018-02-14)
  • v2.2.7 (2018-01-18)
  • v2.2.6 (2018-01-03)
  • v2.2.5 (2017-12-11)
  • v2.2.4 (2017-12-01)
  • v2.2.3 (2017-11-25)
  • v2.2.2 (2017-10-23)
  • v2.2.1 (2017-10-10)
  • v2.2.0 (2017-08-23)
  • v2.1.x (2017-03-02)
  • v2.0.x (2016-09-26)
  • v1.6.x (2016-03-15)
  • v1.5.x (2015-09-28)
  • v1.4.x (2015-07-06)
  • v1.3.x (2015-05-25)
  • v1.2.x (2015-05-18) and older