3.36.1.4-1-3.1
About Sparkling Water
Typical Use Case
Sparkling Water Requirements
Installing and Starting
Design
Configuration
Deployment
Machine Learning
Metric Classes
Model Details
Algorithm Parameters
How to…
Running Sparkling Water
Changing the Default Port
Hive Support in Sparkling Water
Sparkling Water Logging
Enabling SSL
Enabling LDAP
Enabling Kerberos Authentication
Running Sparkling Water on Kerberized Hadoop Cluster
Using SSL to secure H2O Flow UI
Spark Frame <–> H2O Frame Conversions
H2O Frame as Spark’s Data Source
Import & Export H2O Frames from/to S3
Use Sparkling Water via Spark Packages
Development
PySparkling
RSparkling
Migration Guide
Frequently Asked Questions
Change Log
H2O Sparkling Water
Docs
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General
Running Sparkling Water
Changing the Default Port
Hive Support in Sparkling Water
Sparkling Water Logging
Security
Enabling SSL
Using Automatically Generated Security Files
Using Manually Generated Security Files
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)
Running Sparkling Water on Kerberized Hadoop Cluster
Internal Backend
External Backend
Using SSL to secure H2O Flow UI
Using existing Java Keystore
Generate the files automatically
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
Reading Spark Data Frame from H2O Frame
Saving H2O Frame as Spark Data Frame
Loading & Saving Options
Specifying Saving Mode
Import & Export H2O Frames from/to S3
Specify the AWS Dependencies
Configuring S3A
Configuring S3N
Sparkling Water Example Code
PySparkling Example Code
As Spark Package
Use Sparkling Water via Spark Packages