How to…

General

• 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

Security

• Enabling SSL
• Enabling LDAP
  • Configuring LDAP in Scala
  • Configuring LDAP in Python (PySparkling)
• Enabling Kerberos Authentication
  • Configuring Kerberos Auth in Scala
  • Configuring Kerberos Auth in Python (PySparkling)

Frames Conversions and Creation

• Spark Frame <–> H2O Frame Conversions
  • Converting an H2OFrame into an RDD[T]
  • Converting an H2OFrame into a DataFrame
  • Converting an RDD[T] into an H2OFrame
  • Converting a DataFrame into an H2OFrame
• H2O Frame as Spark’s Data Source
  • Usage in Python - PySparkling
  • Usage in Scala
  • Specifying Saving Mode
• Creating H2OFrame from an Existing Key

Spark Pipelines

• Using Grid Search GBM in Spark Pipelines
  • Prepare the environment
  • Define the Pipeline Stages
  • Create and Train the Pipeline
  • Run Predictions

Logging

• Change Sparkling Shell Logging Level
• Change Sparkling Shell Logs Location
  • Client
  • Worker Nodes
• Obtain Sparkling Water Logs
  • Logs for Sparkling Water on YARN
  • Logs for Standalone Sparkling Water

Amazon EMR

• Use Sparkling Water with Amazon EMR

HD Insight

• Using Sparkling Water with Microsoft Azure HDInsight - Beta
  • H2O Artificial Intelligence for Azure HDInsight

Databricks

• 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

Zeppelin

• Sparkling Water and Zeppelin
  • Launch Zeppelin with Sparkling Water
  • Using Zeppelin

As Spark Package

• Use Sparkling Water via Spark Packages