Re: [Autotest] [PATCH 1/2] IOzone test: Introduce postprocessing module

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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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