108 lines
4.3 KiB
Python
Executable File
108 lines
4.3 KiB
Python
Executable File
#
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# plot.py
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#
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# This source file is part of the FoundationDB open source project
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#
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# Copyright 2013-2020 Apple Inc. and the FoundationDB project authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import matplotlib.pyplot as plt
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class Plotter:
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def __init__(self, results):
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self.results = results
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def add_plot(data, time_resolution, label, use_avg=False):
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out_data = {}
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counts = {}
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for t in data.keys():
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out_data.setdefault(t//time_resolution*time_resolution, 0)
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counts.setdefault(t//time_resolution*time_resolution, 0)
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out_data[t//time_resolution*time_resolution] += data[t]
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counts[t//time_resolution*time_resolution] += 1
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if use_avg:
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out_data = { t: v/counts[t] for t,v in out_data.items() }
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plt.plot(list(out_data.keys()), list(out_data.values()), label=label)
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def add_plot_with_times(data, label):
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plt.plot(list(data.keys()), list(data.values()), label=label)
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def display(self, time_resolution=0.1):
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plt.figure(figsize=(40,9))
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plt.subplot(3, 3, 1)
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for priority in self.results.started.keys():
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Plotter.add_plot(self.results.started[priority], time_resolution, priority)
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plt.xlabel('Time (s)')
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plt.ylabel('Released/s')
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plt.legend()
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plt.subplot(3, 3, 2)
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for priority in self.results.queued.keys():
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Plotter.add_plot(self.results.queued[priority], time_resolution, priority)
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plt.xlabel('Time (s)')
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plt.ylabel('Requests/s')
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plt.legend()
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plt.subplot(3, 3, 3)
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for priority in self.results.unprocessed_queue_sizes.keys():
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data = {k: max(v) for (k,v) in self.results.unprocessed_queue_sizes[priority].items()}
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Plotter.add_plot(data, time_resolution, priority)
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plt.xlabel('Time (s)')
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plt.ylabel('Max queue size')
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plt.legend()
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num = 4
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for priority in self.results.latencies.keys():
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plt.subplot(3, 3, num)
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median_latencies = {k: v[int(0.5*len(v))] if len(v) > 0 else 0 for (k,v) in self.results.latencies[priority].items()}
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percentile90_latencies = {k: v[int(0.9*len(v))] if len(v) > 0 else 0 for (k,v) in self.results.latencies[priority].items()}
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max_latencies = {k: max(v) if len(v) > 0 else 0 for (k,v) in self.results.latencies[priority].items()}
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Plotter.add_plot(median_latencies, time_resolution, 'median')
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Plotter.add_plot(percentile90_latencies, time_resolution, '90th percentile')
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Plotter.add_plot(max_latencies, time_resolution, 'max')
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plt.xlabel('Time (s)')
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plt.ylabel(str(priority) + ' Latency (s)')
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plt.yscale('log')
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plt.legend()
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num += 1
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for priority in self.results.rate.keys():
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plt.subplot(3, 3, num)
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if len(self.results.rate[priority]) > 0:
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Plotter.add_plot(self.results.rate[priority], time_resolution, 'Rate', use_avg=True)
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if len(self.results.released[priority]) > 0:
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Plotter.add_plot(self.results.released[priority], time_resolution, 'Released', use_avg=True)
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if len(self.results.limit[priority]) > 0:
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Plotter.add_plot(self.results.limit[priority], time_resolution, 'Limit', use_avg=True)
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if len(self.results.limit_and_budget[priority]) > 0:
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Plotter.add_plot(self.results.limit_and_budget[priority], time_resolution, 'Limit and budget', use_avg=True)
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if len(self.results.budget[priority]) > 0:
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Plotter.add_plot(self.results.budget[priority], time_resolution, 'Budget', use_avg=True)
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plt.xlabel('Time (s)')
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plt.ylabel('Value (' + str(priority) + ')')
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plt.legend()
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num += 1
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plt.show()
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