As described in https://issues.apache.org/jira/browse/SPARK-6188 and discovered in https://issues.apache.org/jira/browse/SPARK-5838.

When re-starting a cluster, if the user does not provide the instance types, which is the recommended behavior in the docs currently, the instance will be assigned the default type m1.large. This then affects the setup of the machines.

This solves this by getting the instance types from the existing instances, and overwriting the default options.

EDIT: Further clarification of the issue:

In short, while the instances themselves are the same as launched, their setup is done assuming the default instance type, m1.large.

This means that the machines are assumed to have 2 disks, and that leads to problems that are described in in issue [5838](https://issues.apache.org/jira/browse/SPARK-5838), where machines that have one disk end up having shuffle spills in the in the small (8GB) snapshot partitions that quickly fills up and results in failing jobs due to "No space left on device" errors.

Other instance specific settings that are set in the spark_ec2.py script are likely to be wrong as well.

Author: Theodore Vasiloudis <thvasilo@users.noreply.github.com>
Author: Theodore Vasiloudis <tvas@sics.se>

Closes #4916 from thvasilo/SPARK-6188]-Instance-types-can-be-mislabeled-when-re-starting-cluster-with-default-arguments and squashes the following commits:

6705b98 [Theodore Vasiloudis] Added comment to clarify setting master instance type to the empty string.
a3d29fe [Theodore Vasiloudis] More trailing whitespace
7b32429 [Theodore Vasiloudis] Removed trailing whitespace
3ebd52a [Theodore Vasiloudis] Make sure that the instance type is correct when relaunching a cluster.