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We can improve analysing mechanism of HDR file by running build_histograms_summary_with_interval
with shorter interval (in the test we perform summary for 600 sec interval), like:
hdr_file = "/home/juliayakovlev/Downloads/loader-set-8af5fdae/"
start_time = 1743691356.5128493
end_time = 1743696279.4485803
interval_sec = 30
res = make_hdrhistogram_summary_by_interval(hdr_tags=["WRITE-st"], path=hdr_file, stress_operation="WRITE", start_time=start_time, end_time=end_time, interval=interval_sec)
p99 = {}
for num, read in enumerate(res):
dt = datetime.utcfromtimestamp(start_time + num * interval_sec).strftime('%Y-%m-%d %H:%M:%S')
p99[dt] = read['WRITE']['percentile_99']
print(p99)
Possible result:
'2025-04-03 14:42:36': 62.0,
'2025-04-03 14:43:06': 72.48,
'2025-04-03 14:43:36': 77.66,
'2025-04-03 14:44:06': 79.63,
'2025-04-03 14:44:36': 65.7,
'2025-04-03 14:45:06': 63.64,
'2025-04-03 14:45:36': 82.97,
'2025-04-03 14:46:06': 113.51,
According to result we can find in the cluster logs what happened in the time of high latency
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