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author | drebs <drebs@riseup.net> | 2017-09-13 12:09:41 -0300 |
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committer | drebs <drebs@riseup.net> | 2017-09-14 12:14:45 -0300 |
commit | 93250414c6ef77b69a0aca008ef28c778c48afe4 (patch) | |
tree | 1a394394ef1b5c0fae392474e95bc529708cf5eb /scripts/benchmark/sqlite-blobs-backend/gen-graph.py | |
parent | dd7b2e414adf2c84873debcd7b7d526859036bc2 (diff) |
[test] add graph for sqlite blobs backend benchmark test
Diffstat (limited to 'scripts/benchmark/sqlite-blobs-backend/gen-graph.py')
-rwxr-xr-x | scripts/benchmark/sqlite-blobs-backend/gen-graph.py | 81 |
1 files changed, 81 insertions, 0 deletions
diff --git a/scripts/benchmark/sqlite-blobs-backend/gen-graph.py b/scripts/benchmark/sqlite-blobs-backend/gen-graph.py new file mode 100755 index 00000000..2bb948f1 --- /dev/null +++ b/scripts/benchmark/sqlite-blobs-backend/gen-graph.py @@ -0,0 +1,81 @@ +#!/usr/bin/env python + +# Plot bars comparing different implementations of mail pipeline. +# +# This script can be improved to account for arbitrary number of data sets, but +# it is not doing it right now. + +import json +import matplotlib.pyplot as plt +import numpy as np +import re + +# make a prettier graph +from mpltools import style +style.use('ggplot') + +OUTPUT_FILENAME = 'blobs-sqlite-backend.png' + +graphs = [ + '1_10000k', + '10_1000k', + '100_100k', + '1000_10k', +] + + +# the JSON structure returned by the following function is ugly, but the +# original JSONs are even uglier, so this is here just to make the life of the +# script easier. +# +# We want to have something like: +# +# data[get/put][amount_size] = <stats> + +def get_data(): + data = {} + for fname in ['get', 'put']: + data[fname] = {} + with open('data/%s.json' % fname) as f: + d = json.loads(f.read()) + benchmarks = d['benchmarks'] + for item in benchmarks: + name = re.sub('^[^1]+', '', item['name']) + data[fname][name] = item['stats'] + return data + + +def plot_data(data): + + N = 4 + + get_means = tuple([data['get'][graph]['mean'] for graph in graphs]) + put_means = tuple([data['put'][graph]['mean'] for graph in graphs]) + + ind = np.arange(N) # the x locations for the groups + width = 0.40 # the width of the bars + + fig, ax = plt.subplots() + rects1 = ax.bar(ind, get_means, width) + rects2 = ax.bar(ind + width, put_means, width) + + # add some text for labels, title and axes ticks + ax.set_ylabel('Time for operation (s)') + ax.set_xlabel('Amount and size of blobs') + ax.set_title('Blobs storage and retrieval time') + ax.set_xticks(ind + (0.5 * width)) + ax.set_xticklabels( + tuple(map(lambda name: name.replace('_', ' x '), graphs))) + + ax.legend( + (rects1[0], rects2[0]), + ('retrieval time', 'storage time')) + # ax.grid() + + plt.savefig(OUTPUT_FILENAME) + # plt.show() + + +if __name__ == '__main__': + data = get_data() + plot_data(data) |