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collect all data to dicts

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This commit is contained in:
Alexey Lavrenuke (load testing) 2014-02-28 17:13:58 +04:00
parent 46f96debc9
commit 2807d34cba
1 changed files with 31 additions and 48 deletions
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79
Tank/Plugins/Report.py
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@ -23,9 +23,20 @@ class ReportPlugin(AbstractPlugin, AggregateResultListener, MonitoringDataListen
def __init__(self, core): def __init__(self, core):
AbstractPlugin.__init__(self, core) AbstractPlugin.__init__(self, core)
self.decoder = MonitoringDataDecoder() self.decoder = MonitoringDataDecoder()
self.overall_quantiles = defaultdict(list)
self.overall_rps = []
self.mon_data = {} self.mon_data = {}
def create_storage():
return {
'avg': defaultdict(list),
'quantiles': defaultdict(list),
'threads': {
'active_threads': []
},
'rps': {
'RPS': []
},
}
self.overall = create_storage()
self.cases = defaultdict(create_storage)
def monitoring_data(self, data_string): def monitoring_data(self, data_string):
self.log.debug("Mon report data: %s", data_string) self.log.debug("Mon report data: %s", data_string)
@ -83,51 +94,23 @@ class ReportPlugin(AbstractPlugin, AggregateResultListener, MonitoringDataListen
@data: SecondAggregateData @data: SecondAggregateData
""" """
ts = int(time.mktime(data.time.timetuple())) ts = int(time.mktime(data.time.timetuple()))
print ts def add_aggreagted_second(data_item, storage):
print data.overall data_dict = data_item.__dict__
print data.cumulative avg = storage['avg']
print data.cases for key in ["avg_connect_time", "avg_send_time", "avg_latency", "avg_receive_time"]:
self.overall_rps.append((ts, data.overall.RPS)) avg[key].append((ts, data_dict.get(key, None)))
for key in data.overall.quantiles.keys(): quantiles = storage['quantiles']
self.overall_quantiles[key].append((ts, data.overall.quantiles[key])) for key, value in data_item.quantiles.iteritems():
quantiles[key].append((ts, value))
add_aggreagted_second(data.overall, self.overall)
for case, case_data in data.cases.iteritems():
add_aggreagted_second(case_data, self.cases[case])
def post_process(self, retcode): def post_process(self, retcode):
print json.dumps(self.overall_quantiles) results = {
print json.dumps(self.overall_rps) 'overall': self.overall,
print json.dumps(self.mon_data) 'cases': self.cases,
# colors = { 'monitoring': self.mon_data,
# 25.0: "#DD0000", }
# 50.0: "#DD3800", print json.dumps(results)
# 75.0: "#DD6E00",
# 80.0: "#DDAA00",
# 90.0: "#DDDC00",
# 95.0: "#A6DD00",
# 98.0: "#70DD00",
# 99.0: "#38DD00",
# 100.0: "#18BB00",
# }
# overall_rps = np.array(self.overall_rps)
# fig = plt.figure()
# oq_plot = fig.add_subplot(111)
# oq_plot.grid(True)
# oq_keys = sorted(self.overall_quantiles)
# legend = ["RPS"] + map(lambda x: str(int(x)), oq_keys)
# oq_plot.plot(overall_rps[:, 0], overall_rps[:, 1], '--')
# for key in reversed(oq_keys):
# quantile = np.array(self.overall_quantiles[key])
# oq_plot.fill_between(quantile[:, 0], quantile[:, 1], color=colors[key])
# # workaround: pyplot can not build a legend for fill_between
# # so we just draw a bunch of lines here:
# for key in oq_keys:
# quantile = np.array(self.overall_quantiles[key])
# oq_plot.plot(quantile[:, 0], quantile[:, 1], color=colors[key])
# plt.xlabel("Time")
# plt.ylabel("Quantiles, ms")
# plt.title("RPS and overall quantiles")
# oq_plot.legend(legend, loc='upper left')
# graph_png = self.core.mkstemp(".png", "overall_")
# self.core.add_artifact_file(graph_png)
# plt.savefig(graph_png)
# if self.show_graph:
# plt.show()
# plt.close()