Continuum Analytics: Documentation

# Anaconda for cluster management

NOTE: Anaconda for cluster management has been replaced by Anaconda Scale. This documentation is made available for existing installations only.

To use Anaconda with a cluster, please use Anaconda Scale and refer to the Anaconda Scale documentation.

Anaconda for cluster management provides resource management tools to easily deploy Anaconda across a cluster. It helps you manage multiple conda environments and packages (including Python and R) on bare-metal or cloud-based clusters. Supported platforms include Amazon EC2, bare-metal clusters, or even a collection of virtual machines.

Anaconda for cluster management can be used with distributed computation frameworks such as Spark or Dask and works alongside enterprise Hadoop distributions such as Cloudera CDH or Hortonworks HDP.

Anaconda for cluster management is freely available via Anaconda Cloud for unlicensed, unsupported use with up to 4 cluster nodes. Anaconda Workgroup and Enterprise include licenses for 8 and 16 nodes, respectively. If you would like to use Anaconda for cluster management with additional nodes on a bare-metal, on-premises, or cloud-based cluster, please contact sales@continuum.io.

Features of Anaconda for cluster management:

- Easily install Python and R packages across multiple cluster nodes
- Manage multiple conda environments across a cluster
- Push local conda environments to all cluster nodes
- Manage both cloud-based and bare-metal clusters
- Remotely SSH and upload/download files to and from cluster nodes

Typical configuration of Anaconda for cluster management:

Table of contents:

- Quickstart
  - Installation
  - Create a provider
  - Create a profile
  - Create the cluster
  - Install conda packages
  - Install plugins
  - Destroy the cluster
  - Further information
- Creating a cluster
  - Cloud-based Cluster Setup
  - Bare-metal Cluster Setup
- Configuration
  - Profile settings
  - Provider settings
- Plugins
  - List of available plugins
  - Installing Plugins
  - Plugin Settings
  - Managing Plugins
  - Plugin Notes and Network Ports
- Cluster management
  - Overview
  - SSH access
  - Executing commands
  - Upload/download files
  - Command history
  - Centralized logging
  - Anaconda for cluster management client information
  - Advanced: Running Salt modules
  - Advanced: Syncing Salt formulas
- Conda management
  - Overview
  - Installing packages from channels
  - List of remote conda commands
  - Example remote conda commands
- Python with Spark How-tos
  - Overview of Spark, YARN and HDFS
  - How to Run a Spark Standalone Job
  - How to Run with the YARN resource manager
  - How to perform a word count on text data in HDFS
  - How to do Natural Language Processing
  - How to do Image Processing with GPUs
- Cluster cheat sheet
- Using Anaconda with Cloudera CDH
  - Uninstalling the Anaconda parcel
  - Using Anaconda for cluster management
- Support
  - Priority support
  - Report a bug
  - Additional nodes
  - Training and consulting
- FAQ / Known issues
  - Product FAQ
  - Technical FAQ
  - Troubleshooting FAQ
  - Known Issues
- Release notes
- Glossary