#!/usr/bin/python
"""
Postprocessing module for IOzone. It is capable to pick results from an
IOzone run, calculate the geometric mean for all throughput results for
a given file size or record size, and then generate a series of 2D and 3D
graphs. The graph generation functionality depends on gnuplot, and if it
is not present, functionality degrates gracefully.
:copyright: Red Hat 2010
"""
import os
import sys
import optparse
import logging
import math
import time
import common
from autotest.client.shared import logging_config, logging_manager
from autotest.client.shared import error
from autotest.client import utils, os_dep
import utils_misc
_LABELS = ['file_size', 'record_size', 'write', 'rewrite', 'read', 'reread',
'randread', 'randwrite', 'bkwdread', 'recordrewrite', 'strideread',
'fwrite', 'frewrite', 'fread', 'freread']
[docs]def geometric_mean(values):
"""
Evaluates the geometric mean for a list of numeric values.
:param values: List with values.
:return: Single value representing the geometric mean for the list values.
:see: `Geometric mean definition <http://en.wikipedia.org/wiki/Geometric_mean>`__
"""
try:
values = [int(value) for value in values]
except ValueError:
return None
n = len(values)
if n == 0:
return None
return math.exp(sum([math.log(x) for x in values]) / n)
[docs]def compare_matrices(matrix1, matrix2, treshold=0.05):
"""
Compare 2 matrices nxm and return a matrix nxm with comparison data
:param matrix1: Reference Matrix with numeric data
:param matrix2: Matrix that will be compared
:param treshold: Any difference bigger than this percent treshold will be
reported.
"""
improvements = 0
regressions = 0
same = 0
new_matrix = []
for line1, line2 in zip(matrix1, matrix2):
new_line = []
for element1, element2 in zip(line1, line2):
ratio = float(element2) / float(element1)
if ratio < (1 - treshold):
regressions += 1
new_line.append((100 * ratio - 1) - 100)
elif ratio > (1 + treshold):
improvements += 1
new_line.append("+" + str((100 * ratio - 1) - 100))
else:
same + 1
if line1.index(element1) == 0:
new_line.append(element1)
else:
new_line.append(".")
new_matrix.append(new_line)
total = improvements + regressions + same
return (new_matrix, improvements, regressions, total)
[docs]class IOzoneAnalyzer(object):
"""
Analyze an unprocessed IOzone file, and generate the following types of
report:
* Summary of throughput for all file and record sizes combined
* Summary of throughput for all file sizes
* Summary of throughput for all record sizes
If more than one file is provided to the analyzer object, a comparison
between the two runs is made, searching for regressions in performance.
"""
def __init__(self, list_files, output_dir):
self.list_files = list_files
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
self.output_dir = output_dir
logging.info("Results will be stored in %s", output_dir)
[docs] def process_results(self, results, label=None):
"""
Process a list of IOzone results according to label.
:param label: IOzone column label that we'll use to filter and compute
geometric mean results, in practical term either 'file_size'
or 'record_size'.
:param result: A list of n x m columns with original iozone results.
:return: A list of n-? x (m-1) columns with geometric averages for
values of each label (ex, average for all file_sizes).
"""
performance = []
if label is not None:
index = _LABELS.index(label)
sizes = utils_misc.unique([line[index] for line in results])
sizes.sort()
for size in sizes:
r_results = [line for line in results if line[index] == size]
performance.append(self.average_performance(r_results, size))
else:
performance.append(self.average_performance(results))
return performance
[docs] def parse_file(self, fileobj):
"""
Parse an IOzone results file.
:param file: File object that will be parsed.
:return: Matrix containing IOzone results extracted from the file.
"""
lines = []
for line in fileobj.readlines():
fields = line.split()
if len(fields) != 15:
continue
try:
lines.append([int(i) for i in fields])
except ValueError:
continue
return lines
[docs] def report(self, overall_results, record_size_results, file_size_results):
"""
Generates analysis data for IOZone run.
Generates a report to both logs (where it goes with nice headers) and
output files for further processing (graph generation).
:param overall_results: 1x15 Matrix containing IOzone results for all
file sizes
:param record_size_results: nx15 Matrix containing IOzone results for
each record size tested.
:param file_size_results: nx15 Matrix containing file size results
for each file size tested.
"""
# Here we'll use the logging system to put the output of our analysis
# to files
logger = logging.getLogger()
formatter = logging.Formatter("")
logging.info("")
logging.info(
"TABLE: SUMMARY of ALL FILE and RECORD SIZES Results in MB/sec")
logging.info("")
logging.info(
"FILE & RECORD INIT RE RE RANDOM RANDOM BACKWD RECRE STRIDE F FRE F FRE")
logging.info(
"SIZES (KB) WRITE WRITE READ READ READ WRITE READ WRITE READ WRITE WRITE READ READ")
logging.info(
"-------------------------------------------------------------------------------------------------------------------")
for result_line in overall_results:
logging.info(
"ALL %-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s" %
tuple(result_line))
logging.info("")
logging.info("DRILLED DATA:")
logging.info("")
logging.info(
"TABLE: RECORD Size against all FILE Sizes Results in MB/sec")
logging.info("")
logging.info(
"RECORD INIT RE RE RANDOM RANDOM BACKWD RECRE STRIDE F FRE F FRE ")
logging.info(
"SIZE (KB) WRITE WRITE READ READ READ WRITE READ WRITE READ WRITE WRITE READ READ")
logging.info(
"--------------------------------------------------------------------------------------------------------------")
foutput_path = os.path.join(self.output_dir, '2d-datasource-file')
if os.path.isfile(foutput_path):
os.unlink(foutput_path)
foutput = logging.FileHandler(foutput_path)
foutput.setFormatter(formatter)
logger.addHandler(foutput)
for result_line in record_size_results:
logging.info(
"%-10s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s" %
tuple(result_line))
logger.removeHandler(foutput)
logging.info("")
logging.info("")
logging.info(
"TABLE: FILE Size against all RECORD Sizes Results in MB/sec")
logging.info("")
logging.info(
"RECORD INIT RE RE RANDOM RANDOM BACKWD RECRE STRIDE F FRE F FRE ")
logging.info(
"SIZE (KB) WRITE WRITE READ READ READ WRITE READ WRITE READ WRITE WRITE READ READ")
logging.info(
"--------------------------------------------------------------------------------------------------------------")
routput_path = os.path.join(self.output_dir, '2d-datasource-record')
if os.path.isfile(routput_path):
os.unlink(routput_path)
routput = logging.FileHandler(routput_path)
routput.setFormatter(formatter)
logger.addHandler(routput)
for result_line in file_size_results:
logging.info(
"%-10s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s%-8s" %
tuple(result_line))
logger.removeHandler(routput)
logging.info("")
[docs] def report_comparison(self, record, file_size_results):
"""
Generates comparison data for 2 IOZone runs.
It compares 2 sets of nxm results and outputs a table with differences.
If a difference higher or smaller than 5% is found, a warning is
triggered.
:param record: Tuple with 4 elements containing results for record size.
:param file_size_results: Tuple with 4 elements containing results for file size.
"""
(record_size, record_improvements, record_regressions,
record_total) = record
(file_size, file_improvements, file_regressions,
file_total) = file_size_results
logging.info("ANALYSIS of DRILLED DATA:")
logging.info("")
logging.info(
"TABLE: RECsize Difference between runs Results are % DIFF")
logging.info("")
logging.info(
"RECORD INIT RE RE RANDOM RANDOM BACKWD RECRE STRIDE F FRE F FRE ")
logging.info(
"SIZE (KB) WRITE WRITE READ READ READ WRITE READ WRITE READ WRITE WRITE READ READ")
logging.info(
"--------------------------------------------------------------------------------------------------------------")
for result_line in record_size:
logging.info(
"%-10s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s" %
tuple(result_line))
logging.info("REGRESSIONS: %d (%.2f%%) Improvements: %d (%.2f%%)",
record_regressions,
(100 * record_regressions / float(record_total)),
record_improvements,
(100 * record_improvements / float(record_total)))
logging.info("")
logging.info("")
logging.info(
"TABLE: FILEsize Difference between runs Results are % DIFF")
logging.info("")
logging.info(
"RECORD INIT RE RE RANDOM RANDOM BACKWD RECRE STRIDE F FRE F FRE ")
logging.info(
"SIZE (KB) WRITE WRITE READ READ READ WRITE READ WRITE READ WRITE WRITE READ READ")
logging.info(
"--------------------------------------------------------------------------------------------------------------")
for result_line in file_size:
logging.info(
"%-10s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s%-8.6s" %
tuple(result_line))
logging.info("REGRESSIONS: %d (%.2f%%) Improvements: %d (%.2f%%)",
file_regressions,
(100 * file_regressions / float(file_total)),
file_improvements,
(100 * file_improvements / float(file_total)))
logging.info("")
[docs] def analyze(self):
"""
Analyzes and eventually compares sets of IOzone data.
"""
overall = []
record_size = []
file_size = []
for path in self.list_files:
fileobj = open(path, 'r')
logging.info('FILE: %s', path)
results = self.parse_file(fileobj)
overall_results = self.process_results(results)
record_size_results = self.process_results(results, 'record_size')
file_size_results = self.process_results(results, 'file_size')
self.report(
overall_results, record_size_results, file_size_results)
if len(self.list_files) == 2:
overall.append(overall_results)
record_size.append(record_size_results)
file_size.append(file_size_results)
if len(self.list_files) == 2:
record_comparison = compare_matrices(*record_size)
file_comparison = compare_matrices(*file_size)
self.report_comparison(record_comparison, file_comparison)
[docs]class IOzonePlotter(object):
"""
Plots graphs based on the results of an IOzone run.
Plots graphs based on the results of an IOzone run. Uses gnuplot to
generate the graphs.
"""
def __init__(self, results_file, output_dir):
self.active = True
try:
self.gnuplot = os_dep.command("gnuplot")
except Exception:
logging.error("Command gnuplot not found, disabling graph "
"generation")
self.active = False
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
self.output_dir = output_dir
if not os.path.isfile(results_file):
logging.error("Invalid file %s provided, disabling graph "
"generation", results_file)
self.active = False
self.results_file = None
else:
self.results_file = results_file
self.generate_data_source()
[docs] def generate_data_source(self):
"""
Creates data file without headers for gnuplot consumption.
"""
results_file = open(self.results_file, 'r')
self.datasource = os.path.join(self.output_dir, '3d-datasource')
datasource = open(self.datasource, 'w')
for line in results_file.readlines():
fields = line.split()
if len(fields) != 15:
continue
try:
for i in fields:
int(i)
datasource.write(line)
except ValueError:
continue
datasource.close()
[docs] def plot_2d_graphs(self):
"""
For each one of the throughput parameters, generate a set of gnuplot
commands that will create a parametric surface with file size vs.
record size vs. throughput.
"""
datasource_2d = os.path.join(self.output_dir, '2d-datasource-file')
for index, label in zip(range(2, 15), _LABELS[2:]):
commands_path = os.path.join(self.output_dir, '2d-%s.do' % label)
commands = ""
commands += "set title 'Iozone performance: %s'\n" % label
commands += "set logscale x\n"
commands += "set xlabel 'File size (KB)'\n"
commands += "set ylabel 'Througput (MB/s)'\n"
commands += "set terminal png small size 450 350\n"
commands += "set output '%s'\n" % os.path.join(self.output_dir,
'2d-%s.png' % label)
commands += ("plot '%s' using 1:%s title '%s' with lines \n" %
(datasource_2d, index, label))
commands_file = open(commands_path, 'w')
commands_file.write(commands)
commands_file.close()
try:
utils.system("%s %s" % (self.gnuplot, commands_path))
except error.CmdError:
logging.error("Problem plotting from commands file %s",
commands_path)
[docs] def plot_3d_graphs(self):
"""
For each one of the throughput parameters, generate a set of gnuplot
commands that will create a parametric surface with file size vs.
record size vs. throughput.
"""
for index, label in zip(range(1, 14), _LABELS[2:]):
commands_path = os.path.join(self.output_dir, '%s.do' % label)
commands = ""
commands += "set title 'Iozone performance: %s'\n" % label
commands += "set grid lt 2 lw 1\n"
commands += "set surface\n"
commands += "set parametric\n"
commands += "set xtics\n"
commands += "set ytics\n"
commands += "set logscale x 2\n"
commands += "set logscale y 2\n"
commands += "set logscale z\n"
commands += "set xrange [2.**5:2.**24]\n"
commands += "set xlabel 'File size (KB)'\n"
commands += "set ylabel 'Record size (KB)'\n"
commands += "set zlabel 'Througput (KB/s)'\n"
commands += "set style data lines\n"
commands += "set dgrid3d 80,80, 3\n"
commands += "set terminal png small size 900 700\n"
commands += "set output '%s'\n" % os.path.join(self.output_dir,
'%s.png' % label)
commands += ("splot '%s' using 1:2:%s title '%s'\n" %
(self.datasource, index, label))
commands_file = open(commands_path, 'w')
commands_file.write(commands)
commands_file.close()
try:
utils.system("%s %s" % (self.gnuplot, commands_path))
except error.CmdError:
logging.error("Problem plotting from commands file %s",
commands_path)
[docs] def plot_all(self):
"""
Plot all graphs that are to be plotted, provided that we have gnuplot.
"""
if self.active:
self.plot_2d_graphs()
self.plot_3d_graphs()
[docs]class AnalyzerLoggingConfig(logging_config.LoggingConfig):
if __name__ == "__main__":
parser = optparse.OptionParser("usage: %prog [options] [filenames]")
options, args = parser.parse_args()
logging_manager.configure_logging(AnalyzerLoggingConfig())
if args:
filenames = args
else:
parser.print_help()
sys.exit(1)
if len(args) > 2:
parser.print_help()
sys.exit(1)
o = os.path.join(os.getcwd(),
"iozone-graphs-%s" % time.strftime('%Y-%m-%d-%H.%M.%S'))
if not os.path.isdir(o):
os.makedirs(o)
a = IOzoneAnalyzer(list_files=filenames, output_dir=o)
a.analyze()
p = IOzonePlotter(results_file=filenames[0], output_dir=o)
p.plot_all()