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Benchmarks python graphs
========================
This page documents an example of how to query elasticsearch and plot the
results with python. We are currently using ``kibana`` to plot and show graphs,
but in the future we might want/need the flexibility of python for that.
Generated image
---------------
.. image:: benchmarks-python-graphs.png
:alt: Example of image generated with the code above.
Code example
------------
Some notes about the code example:
* Depends on ``elasticsearch`` for querying and ``matplotlib`` for plotting.
* Searches need to be scrolled to get all results using a ``scroll_id``.
* Commit datetime ranges (`1 <https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-range-query.html>`_, `2 <https://www.elastic.co/guide/en/elasticsearch/reference/current/common-options.html#date-math>`_, `3 <https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-daterange-aggregation.html#date-format-pattern>`_) can be put in place to limit results.
.. code:: python
#!/usr/bin/env python
import os
from math import sqrt
from dateutil.parser import parse
from elasticsearch import Elasticsearch
from elasticsearch.exceptions import NotFoundError
import matplotlib.pyplot as plt
def sort_commits(a, b):
ta = parse(a['_source']['commit_info']['author_time'])
tb = parse(b['_source']['commit_info']['author_time'])
return -1 if ta < tb else 1
def _query_elasticsearch():
http_auth = os.environ.get('ES_CREDS').split(':')
es = Elasticsearch([{
'host': 'moose.leap.se',
'port': 9200,
'use_ssl': True,
'http_auth': http_auth,
}])
q = "commit_info.project:soledad " \
"AND machine_info.host='weasel' " \
"AND name='test_async_create_1000_10k' " \
"AND commit_info.time:[\"now-1d\" TO \"now\"]"
res = es.search(index='benchmark', q=q, scroll='1m', size=50)
total = res['hits']['total']
scroll_size = total
scroll_id = res['_scroll_id']
hits = res['hits']['hits'][:]
print("There are %d hits to get." % total)
print("(got %d...)" % len(hits))
# scroll to get all results
print("(started scrolling...)")
while scroll_size > 0:
try:
res = es.scroll(scroll_id=scroll_id, scroll='1m')
scroll_size = len(res['hits']['hits'])
scroll_id = res['_scroll_id']
print("(got %d more...)" % scroll_size)
hits += res['hits']['hits'][:]
except NotFoundError:
print("(finished scrolling.)")
pass
break
print("Found %d hits." % len(hits))
hits.sort(sort_commits)
stats = []
means = []
for hit in hits:
st = hit['_source']['stats']
commit_id = hit['_source']['commit_info']['id'][:7]
item = {}
item["label"] = commit_id
item["mean"] = st['mean']
item["med"] = st['median']
item["q1"] = st['q1']
item["q3"] = st['q3']
# item["cilo"] = 5.3 # not required
# item["cihi"] = 5.7 # not required
item["whislo"] = st['mean'] - st['stddev']
item["whishi"] = st['mean'] + st['stddev']
item["fliers"] = [] # required if showfliers=True
stats.append(item)
means.append(st['mean'])
# print(hit['_source']['commit_info'])
return stats, means
def mean(lst):
return sum(lst) / len(lst)
def stddev(lst):
mn = mean(lst)
variance = sum([(e - mn)**2 for e in lst]) / len(lst)
return sqrt(variance)
def _plot_graph(results):
print("Plotting graph...")
stats, means = results
fig, axes = plt.subplots(1, 1)
plt.grid()
axes.bxp(stats)
mmean = mean(means)
mstddev = stddev(means)
plt.axhline(y=mmean + (1.5 * mstddev), color='b', linestyle='--')
plt.axhline(y=mmean - (1.5 * mstddev), color='b', linestyle='--')
plt.axhline(y=mmean, color='b', linestyle='-')
axes.set_title('Time taken for test_async_create_1000_10k')
plt.xticks(rotation=45, ha='right', size='small')
plt.ylim(ymin=0)
plt.tight_layout()
# boxplot
filename = '/tmp/test.png'
print("Saving to %s" % filename)
plt.savefig(filename)
# plt.figure()
# plt.show()
if __name__ == '__main__':
results = _query_elasticsearch()
_plot_graph(results)
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