Continuum Analytics: Documentation

# Anaconda Scale

Distributed Computing

Anaconda Scale provides functionality to easily deploy Anaconda packages and a distributed computation framework across a cluster. It helps you manage multiple conda environments and packages (including Python and R) on cluster nodes.

Anaconda Scale provides different options for deploying Anaconda on a cluster, including:

- Centrally managed installation of Anaconda, including multiple environments (Python and R)
- Anaconda parcel for Cloudera CDH, including custom-generated parcels
- Deploying conda packages and environments with Spark jobs

Features

- Easily install Anaconda (including Anaconda Accelerate) across multiple cluster nodes
- Provision distributed compute services with Dask
- Single-user Jupyter Notebook for interactive, distributed computations
- Easily launch and configure a cloud-based cluster on Amazon EC2

Compatibility

Anaconda Scale 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 Scale has been tested with the following Hadoop distributions and Spark versions:

- Cloudera CDH 5.3.x through 5.9.x
- Hortonworks HDP 2.2.x through 2.5.x (with Apache Ambari 2.2.x and 2.4.x)
- Spark 1.3.x through 2.0.x

License

Anaconda Scale is freely available for unlicensed, unsupported use with up to 4 cluster nodes. Anaconda Workgroup and Enterprise include licenses for 8 and 16 nodes, respectively, and support for additional nodes can be purchased.

If you would like to use Anaconda Scale with additional nodes on a bare-metal, on-premises, or cloud-based cluster, please contact us.