#!/usr/bin/python2.7 # Note: this script is python2 and python3 compatible. # # fio_jsonplus_clat2csv # # This script converts fio's json+ completion latency data to CSV format. # # For example: # # Run the following fio jobs: # ../fio --output=fio-jsonplus.output --output-format=json+ --name=test1 # --ioengine=null --time_based --runtime=5s --size=1G --rw=randrw # --name=test2 --ioengine=null --time_based --runtime=3s --size=1G # --rw=read --name=test3 --ioengine=null --time_based --runtime=4s # --size=8G --rw=write # # Then run: # fio_jsonplus_clat2csv fio-jsonplus.output fio-latency.csv # # You will end up with the following 3 files # # -rw-r--r-- 1 root root 6467 Jun 27 14:57 fio-latency_job0.csv # -rw-r--r-- 1 root root 3985 Jun 27 14:57 fio-latency_job1.csv # -rw-r--r-- 1 root root 4490 Jun 27 14:57 fio-latency_job2.csv # # fio-latency_job0.csv will look something like: # # clat_nsec, read_count, read_cumulative, read_percentile, write_count, # write_cumulative, write_percentile, trim_count, trim_cumulative, # trim_percentile, # 25, 1, 1, 1.50870705013e-07, , , , , , , # 26, 12, 13, 1.96131916517e-06, 947, 947, 0.000142955890032, , , , # 27, 843677, 843690, 0.127288105112, 838347, 839294, 0.126696959629, , , , # 28, 1877982, 2721672, 0.410620573454, 1870189, 2709483, 0.409014312345, , , , # 29, 4471, 2726143, 0.411295116376, 7718, 2717201, 0.410179395301, , , , # 30, 2142885, 4869028, 0.734593687087, 2138164, 4855365, 0.732949340025, , , , # ... # 2544, , , , 2, 6624404, 0.999997433738, , , , # 2576, 3, 6628178, 0.99999788781, 4, 6624408, 0.999998037564, , , , # 2608, 4, 6628182, 0.999998491293, 4, 6624412, 0.999998641391, , , , # 2640, 3, 6628185, 0.999998943905, 2, 6624414, 0.999998943304, , , , # 2672, 1, 6628186, 0.999999094776, 3, 6624417, 0.999999396174, , , , # 2736, 1, 6628187, 0.999999245646, 1, 6624418, 0.99999954713, , , , # 2768, 2, 6628189, 0.999999547388, 1, 6624419, 0.999999698087, , , , # 2800, , , , 1, 6624420, 0.999999849043, , , , # 2832, 1, 6628190, 0.999999698259, , , , , , , # 4192, 1, 6628191, 0.999999849129, , , , , , , # 5792, , , , 1, 6624421, 1.0, , , , # 10304, 1, 6628192, 1.0, , , , , , , # # The first line says that you had one read IO with 25ns clat, # the cumulative number of read IOs at or below 25ns is 1, and # 25ns is the 0.00001509th percentile for read latency # # The job had 2 write IOs complete in 2544ns, # 6624404 write IOs completed in 2544ns or less, # and this represents the 99.99974th percentile for write latency # # The last line says that one read IO had 10304ns clat, # 6628192 read IOs had 10304ns or shorter clat, and # 10304ns is the 100th percentile for read latency # from __future__ import absolute_import from __future__ import print_function import os import json import argparse import six from six.moves import range def parse_args(): parser = argparse.ArgumentParser() parser.add_argument('source', help='fio json+ output file containing completion ' 'latency data') parser.add_argument('dest', help='destination file stub for latency data in CSV ' 'format. job number will be appended to filename') args = parser.parse_args() return args def percentile(idx, run_total): total = run_total[len(run_total)-1] if total == 0: return 0 return float(run_total[idx]) / total def more_lines(indices, bins): for key, value in six.iteritems(indices): if value < len(bins[key]): return True return False def main(): args = parse_args() with open(args.source, 'r') as source: jsondata = json.loads(source.read()) for jobnum in range(0, len(jsondata['jobs'])): bins = {} run_total = {} ddir_set = set(['read', 'write', 'trim']) prev_ddir = None for ddir in ddir_set: if 'bins' in jsondata['jobs'][jobnum][ddir]['clat_ns']: bins_loc = 'clat_ns' elif 'bins' in jsondata['jobs'][jobnum][ddir]['lat_ns']: bins_loc = 'lat_ns' else: raise RuntimeError("Latency bins not found. " "Are you sure you are using json+ output?") bins[ddir] = [[int(key), value] for key, value in six.iteritems(jsondata['jobs'][jobnum][ddir][bins_loc] ['bins'])] bins[ddir] = sorted(bins[ddir], key=lambda bin: bin[0]) run_total[ddir] = [0 for x in range(0, len(bins[ddir]))] if len(bins[ddir]) > 0: run_total[ddir][0] = bins[ddir][0][1] for x in range(1, len(bins[ddir])): run_total[ddir][x] = run_total[ddir][x-1] + \ bins[ddir][x][1] stub, ext = os.path.splitext(args.dest) outfile = stub + '_job' + str(jobnum) + ext with open(outfile, 'w') as output: output.write("{0}ec, ".format(bins_loc)) ddir_list = list(ddir_set) for ddir in ddir_list: output.write("{0}_count, {0}_cumulative, {0}_percentile, ". format(ddir)) output.write("\n") # # Have a counter for each ddir # In each round, pick the shortest remaining duration # and output a line with any values for that duration # indices = {x: 0 for x in ddir_list} while more_lines(indices, bins): min_lat = 17112760320 for ddir in ddir_list: if indices[ddir] < len(bins[ddir]): min_lat = min(bins[ddir][indices[ddir]][0], min_lat) output.write("{0}, ".format(min_lat)) for ddir in ddir_list: if indices[ddir] < len(bins[ddir]) and \ min_lat == bins[ddir][indices[ddir]][0]: count = bins[ddir][indices[ddir]][1] cumulative = run_total[ddir][indices[ddir]] ptile = percentile(indices[ddir], run_total[ddir]) output.write("{0}, {1}, {2}, ".format(count, cumulative, ptile)) indices[ddir] += 1 else: output.write(", , , ") output.write("\n") print("{0} generated".format(outfile)) if __name__ == '__main__': main()