Skip to main content

Minimalistic utility library to manage conda environments for pyspark jobs on yarn clusters

Project description

Minimalistic utility library to manage conda environments for PySpark jobs on yarn clusters.

Features

  • Manage conda environments on PySpark executors to use specific packages on the remote workers without involving admins to install needed software on hadoop cluster.

Docs

http://sparkonda.readthedocs.org

History

0.2.2 (2016-02)

Fix bug when number of cores per executor is larger than 1

Fix list_cwd to include hostname in output

Fix tests to use pack files naming instead of zip files

Fix usage docs to include new config for number of cores

Add tests for correct prun to num partition mapping

0.2.1 (2016-01)

Fix documentation, setup and usage methods

Fix travis and setup.py configs

Move zip to pack as an action

Replace zip with tar to better preserve acls on conda env files

Add configuration of error level for untar

0.2.0 (2016-01)

Additional tests for the distributed version of remote package delivery

Changed os files management to python based support (zip, rm)

Use SparkFiles to detect files distributed to the workers.

0.1.0 (2015-11)

Initial version to manage the conda environments on pyspark cluster workers without involving your cluster admins too heavily.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sparkonda-0.2.2.tar.gz (16.3 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page