Arvados

h1. Pipeline Optimization

h2. Crunchstat Summary

Crunchstat-summary is an arvados tool to help choose optimal configurations for arvados jobs and pipeline instances. It helps you choose "runtime_constraints":http://doc.arvados.org/api/schema/Job.html specified in the pipeline template under each job, as well as graph general statistics for the job, for example, CPU usage, RAM, and Keep network traffic across the duration of a job.

h3. How to install crunchstat-summary

<pre>

$ git clone https://github.com/curoverse/arvados.git

$ cd arvados/tools/crunchstat-summary/

$ python setup.py build

$ python setup.py install --user

</pre>

h3. How to use crunchstat-summary

<pre>

$ ./bin/crunchstat-summary --help

usage: crunchstat-summary [-h]

                          [--job UUID | --pipeline-instance UUID | --log-file LOG_FILE]

                          [--skip-child-jobs] [--format {html,text}]

                          [--verbose]

Summarize resource usage of an Arvados Crunch job

optional arguments:

  -h, --help            show this help message and exit

  --job UUID            Look up the specified job and read its log data from

                        Keep (or from the Arvados event log, if the job is

                        still running)

  --pipeline-instance UUID

                        Summarize each component of the given pipeline

                        instance

  --log-file LOG_FILE   Read log data from a regular file

  --skip-child-jobs     Do not include stats from child jobs

  --format {html,text}  Report format

  --verbose, -v         Log more information (once for progress, twice for

                        debug)

</pre>

--text mode

using node recommendations, keep cache size

--html mode

check if you're cpu/io bound

check if tasks are being weird, i.e. gatk queue case

when to pipe and when to write to keep

in general writing straight to keep will reap benefits. If you run crunchstat-summary --html and you see keep io stopping once in a while, then youre cpu bound. If you're seeing cpu level off and keep-read or keep-write taking too long, then you're io bound.

h3. choosing the right number of jobs

each job must output a collection, so if you don't want to output a file, then 

h2. Job Optimization

h3. How to optimize the number when you don't have native multithreading

tools like gatk, blah blah have native multithreading where you pass a -t.

tools like varscan/freebayes blah blah don't have native multithreading so you need to find a workaround. generally, some tools have a -L --intervals to pass in certain loci to work on. If you have a bed file you can split on, then you can create a new task per interval.

example here

h3. piping between tools or writing to a tmpdir.