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Optimize AWS EMR spark settings (spark-config-cheatsheet)

Project description

# Spark-optimizer

[![Build Status](](

Optimize spark settings (for cluster aka yarn run)

Original source:

## Usage


$ virtualenv env
$ env/bin/pip install spark-optimizer

Dev install:

$ virtualenv env
$ env/bin/pip install -e .

Generate settings for `c4.4xlarge` with `4` nodes:

$ env/bin/spark-optimizer c4.4xlarge 4
{'spark.default.parallelism': '108',
'spark.driver.cores': '2',
'spark.driver.maxResultSize': '3481m',
'spark.driver.memory': '3481m',
'spark.driver.memoryOverhead': '614m',
'spark.executor.cores': '2',
'spark.executor.instances': '27',
'spark.executor.memory': '3481m',
'spark.executor.memoryOverhead': '614m'}

Update instance info:

$ env/bin/python spark_optimizer/


0.1.4 (2019-03-10)

- add ec2 and emr cost to yaml

0.1.3 (2019-03-08)

- add emr cost to yaml
- export load yaml file
- make ``memory_overhead_coefficient`` editable

0.1.2 (2019-02-20)

- unpin the versions
- rename cli from _ to -

0.1.1 (2018-09-12)

- fix email

0.1.0 (2018-09-12)

- initial release

Project details

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