This repository was archived by the owner on Nov 23, 2017. It is now read-only.
Option to create Ubuntu 14.04 clusters using spark-ec2#49
Open
manubansal wants to merge 69 commits into
Open
Conversation
added 30 commits
August 24, 2016 20:03
|
Thanks for doing this! I could really use this! |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Here's a beta version of Ubuntu 14.04 addition to spark-ec2. There are some simplifications made for the Ubuntu create/setup sequence where Rstudio, ganglia, and persistent-hdfs have not been ported to include Ubuntu. All necessary setup is functional and users can run spark jobs on Ubuntu clusters. No functional changes have been made to the default spark AMI.
This PR should be treated as a trial before declaring stable. We have been running tests to create, start, stop, destroy Ubuntu clusters, and using those clusters for running spark jobs. However, tests are not yet exhaustive across different instance types or input options, so the coverage is limited. We consider this version usable at large with the understanding that minor bugs could show up.