On Fri, 2010-04-30 at 14:23 -0700, Martin Bligh wrote:
> I'm slightly surprised this isn't called from postprocess
> in the test? Any downside to doing that?
In the second patch I do the change to make the test to use the
postprocessing module.
> On Fri, Apr 30, 2010 at 2:20 PM, Lucas Meneghel Rodrigues
> <lmr@xxxxxxxxxx> wrote:
> > This module contains code to postprocess IOzone data
> > in a convenient way so we can generate performance graphs
> > and condensed data. The graph generation part depends
> > on gnuplot, but if the utility is not present,
> > functionality will gracefully degrade.
> >
> > The reason why this was created as a separate module is:
> > * It doesn't pollute the main test class.
> > * Allows us to use the postprocess module as a stand alone program,
> > that can even do performance comparison between 2 IOzone runs.
> >
> > Signed-off-by: Lucas Meneghel Rodrigues <lmr@xxxxxxxxxx>
> > ---
> > client/tests/iozone/postprocessing.py | 487 +++++++++++++++++++++++++++++++++
> > 1 files changed, 487 insertions(+), 0 deletions(-)
> > create mode 100755 client/tests/iozone/postprocessing.py
> >
> > diff --git a/client/tests/iozone/postprocessing.py b/client/tests/iozone/postprocessing.py
> > new file mode 100755
> > index 0000000..b495502
> > --- /dev/null
> > +++ b/client/tests/iozone/postprocessing.py
> > @@ -0,0 +1,487 @@
> > +#!/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, sys, optparse, logging, math, time
> > +import common
> > +from autotest_lib.client.common_lib import logging_config, logging_manager
> > +from autotest_lib.client.common_lib import error
> > +from autotest_lib.client.bin import utils, os_dep
> > +
> > +
> > +_LABELS = ('file_size', 'record_size', 'write', 'rewrite', 'read', 'reread',
> > + 'randread', 'randwrite', 'bkwdread', 'recordrewrite', 'strideread',
> > + 'fwrite', 'frewrite', 'fread', 'freread')
> > +
> > +
> > +def unique(list):
> > + """
> > + Return a list of the elements in list, but without duplicates.
> > +
> > + @param list: List with values.
> > + @return: List with non duplicate elements.
> > + """
> > + n = len(list)
> > + if n == 0:
> > + return []
> > + u = {}
> > + try:
> > + for x in list:
> > + u[x] = 1
> > + except TypeError:
> > + return None
> > + else:
> > + return u.keys()
> > +
> > +
> > +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: http://en.wikipedia.org/wiki/Geometric_mean
> > + """
> > + try:
> > + values = [int(value) for value in values]
> > + except ValueError:
> > + return None
> > + product = 1
> > + n = len(values)
> > + if n == 0:
> > + return None
> > + return math.exp(sum([math.log(x) for x in values])/n)
> > +
> > +
> > +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
> > + comparison_matrix = []
> > +
> > + 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)
> > +
> > +
> > +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)
> > +
> > +
> > + def average_performance(self, results, size=None):
> > + """
> > + Flattens a list containing performance results.
> > +
> > + @param results: List of n lists containing data from performance runs.
> > + @param size: Numerical value of a size (say, file_size) that was used
> > + to filter the original results list.
> > + @return: List with 1 list containing average data from the performance
> > + run.
> > + """
> > + average_line = []
> > + if size is not None:
> > + average_line.append(size)
> > + for i in range(2, 15):
> > + average = geometric_mean([line[i] for line in results]) / 1024.0
> > + average = int(average)
> > + average_line.append(average)
> > + return average_line
> > +
> > +
> > + def process_results(self, results, label=None):
> > + """
> > + Process a list of IOzone results according to label.
> > +
> > + @label: IOzone column label that we'll use to filter and compute
> > + geometric mean results, in practical term either 'file_size'
> > + or 'record_size'.
> > + @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 = 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
> > +
> > +
> > + def parse_file(self, file):
> > + """
> > + 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 file.readlines():
> > + fields = line.split()
> > + if len(fields) != 15:
> > + continue
> > + try:
> > + lines.append([int(i) for i in fields])
> > + except ValueError:
> > + continue
> > + return lines
> > +
> > +
> > + 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("")
> > +
> > +
> > + def report_comparison(self, record, file):
> > + """
> > + 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: 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
> > + 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("")
> > +
> > +
> > + def analyze(self):
> > + """
> > + Analyzes and eventually compares sets of IOzone data.
> > + """
> > + overall = []
> > + record_size = []
> > + file_size = []
> > + for path in self.list_files:
> > + file = open(path, 'r')
> > + logging.info('FILE: %s', path)
> > +
> > + results = self.parse_file(file)
> > +
> > + 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)
> > +
> > +
> > +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:
> > + 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()
> > +
> > +
> > + 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:
> > + values = [int(i) for i in fields]
> > + datasource.write(line)
> > + except ValueError:
> > + continue
> > + datasource.close()
> > +
> > +
> > + 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(1, 14), _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.run("%s %s" % (self.gnuplot, commands_path))
> > + except error.CmdError, e:
> > + logging.error("Problem plotting from commands file %s: %s",
> > + commands_file, str(e))
> > +
> > +
> > + 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 data style 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.run("%s %s" % (self.gnuplot, commands_path))
> > + except error.CmdError, e:
> > + logging.error("Problem plotting from commands file %s: %s",
> > + commands_file, str(e))
> > +
> > +
> > + 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()
> > +
> > +
> > +class AnalyzerLoggingConfig(logging_config.LoggingConfig):
> > + def configure_logging(self, results_dir=None, verbose=False):
> > + super(AnalyzerLoggingConfig, self).configure_logging(use_console=True,
> > + verbose=verbose)
> > +
> > +
> > +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()
> > --
> > 1.7.0.1
> >
> > _______________________________________________
> > Autotest mailing list
> > Autotest@xxxxxxxxxxxxxxx
> > http://test.kernel.org/cgi-bin/mailman/listinfo/autotest
> >
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