ClickHouse/benchmark/greenplum/result_parser.py

#!/usr/bin/env python

from __future__ import print_function
import sys
import json

def parse_block(block=[], options=[]):

    #print('block is here', block)
    #show_query = False
    #show_query = options.show_query
    result = []
    query = block[0].strip()
    if len(block) > 4:
        timing1 = block[1].strip().split()[1]
        timing2 = block[3].strip().split()[1]
        timing3 = block[5].strip().split()[1]
    else:
        timing1 = block[1].strip().split()[1]
        timing2 = block[2].strip().split()[1]
        timing3 = block[3].strip().split()[1]
    if options.show_queries:
        result.append( query )
    if not options.show_first_timings:
        result += [ timing1 , timing2, timing3 ]
    else:
        result.append(timing1)
    return result


def read_stats_file(options, fname):
    result = []
    int_result = []
    block = []
    time_count = 1
    with open(fname) as f:

        for line in f.readlines():

            if 'SELECT' in line:
                if len(block) > 1:
                    result.append( parse_block(block, options) )
                block = [ line ]
            elif 'Time:' in line:
                block.append( line )

    return result


def compare_stats_files(options, arguments):
    result = []
    file_output = []
    pyplot_colors = ['y', 'b', 'g', 'r']
    for fname in arguments[1:]:
        file_output.append((read_stats_file(options, fname)))
    if len(file_output[0]) > 0:
        timings_count = len(file_output[0])
    for idx, data_set in enumerate(file_output):
        int_result = []
        for timing in data_set:
           int_result.append(float(timing[0])) #y values
        result.append([[x for x in range(0, len(int_result)) ], int_result,
pyplot_colors[idx] + '^' ] )
#        result.append([x for x in range(1, len(int_result)) ]) #x values
#        result.append( pyplot_colors[idx] + '^' )

    return result

def parse_args():
    from optparse import OptionParser
    parser = OptionParser(usage='usage: %prog [options] [result_file_path]..')
    parser.add_option("-q", "--show-queries", help="Show statements along with timings", action="store_true", dest="show_queries")
    parser.add_option("-f", "--show-first-timings", help="Show only first tries timings", action="store_true", dest="show_first_timings")
    parser.add_option("-c", "--compare-mode", help="Prepare output for pyplot comparing result files.", action="store", dest="compare_mode")
    (options, arguments) = parser.parse_args(sys.argv)
    if len(arguments) < 2:
        parser.print_usage()
        sys.exit(1)
    return ( options, arguments )

def gen_pyplot_code(options, arguments):
    result = ''
    data_sets = compare_stats_files(options, arguments)
    for idx, data_set in enumerate(data_sets, start=0):
        x_values, y_values, line_style = data_set
        result += '\nplt.plot('
        result += '%s, %s, \'%s\'' % ( x_values, y_values, line_style )
        result += ', label=\'%s try\')' % idx
    print('import matplotlib.pyplot as plt')
    print(result)
    print( 'plt.xlabel(\'Try number\')' )
    print( 'plt.ylabel(\'Timing\')' )
    print( 'plt.title(\'Benchmark query timings\')' )
    print('plt.legend()')
    print('plt.show()')


def gen_html_json(options, arguments):
    tuples = read_stats_file(options, arguments[1])
    print('{')
    print('"system:       GreenPlum(x2),')
    print('"version":      "%s",' % '4.3.9.1')
    print('"data_size":    10000000,')
    print('"time":         "",')
    print('"comments":     "",')
    print('"result":')
    print('[')
    for s in tuples:
        print(s)
    print(']')
    print('}')


def main():
    ( options, arguments ) = parse_args()
    if len(arguments) > 2:
        gen_pyplot_code(options, arguments)
    else:
        gen_html_json(options, arguments)

if __name__ == '__main__':
    main()