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123 lines
3.8 KiB
Python
Executable File
123 lines
3.8 KiB
Python
Executable File
#!/usr/bin/env python
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from __future__ import print_function
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import sys
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import json
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def parse_block(block=[], options=[]):
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#print('block is here', block)
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#show_query = False
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#show_query = options.show_query
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result = []
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query = block[0].strip()
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if len(block) > 4:
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timing1 = block[1].strip().split()[1]
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timing2 = block[3].strip().split()[1]
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timing3 = block[5].strip().split()[1]
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else:
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timing1 = block[1].strip().split()[1]
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timing2 = block[2].strip().split()[1]
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timing3 = block[3].strip().split()[1]
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if options.show_queries:
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result.append( query )
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if not options.show_first_timings:
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result += [ timing1 , timing2, timing3 ]
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else:
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result.append(timing1)
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return result
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def read_stats_file(options, fname):
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result = []
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int_result = []
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block = []
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time_count = 1
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with open(fname) as f:
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for line in f.readlines():
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if 'SELECT' in line:
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if len(block) > 1:
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result.append( parse_block(block, options) )
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block = [ line ]
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elif 'Time:' in line:
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block.append( line )
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return result
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def compare_stats_files(options, arguments):
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result = []
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file_output = []
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pyplot_colors = ['y', 'b', 'g', 'r']
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for fname in arguments[1:]:
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file_output.append((read_stats_file(options, fname)))
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if len(file_output[0]) > 0:
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timings_count = len(file_output[0])
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for idx, data_set in enumerate(file_output):
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int_result = []
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for timing in data_set:
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int_result.append(float(timing[0])) #y values
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result.append([[x for x in range(0, len(int_result)) ], int_result,
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pyplot_colors[idx] + '^' ] )
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# result.append([x for x in range(1, len(int_result)) ]) #x values
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# result.append( pyplot_colors[idx] + '^' )
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return result
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def parse_args():
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from optparse import OptionParser
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parser = OptionParser(usage='usage: %prog [options] [result_file_path]..')
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parser.add_option("-q", "--show-queries", help="Show statements along with timings", action="store_true", dest="show_queries")
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parser.add_option("-f", "--show-first-timings", help="Show only first tries timings", action="store_true", dest="show_first_timings")
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parser.add_option("-c", "--compare-mode", help="Prepare output for pyplot comparing result files.", action="store", dest="compare_mode")
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(options, arguments) = parser.parse_args(sys.argv)
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if len(arguments) < 2:
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parser.print_usage()
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sys.exit(1)
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return ( options, arguments )
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def gen_pyplot_code(options, arguments):
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result = ''
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data_sets = compare_stats_files(options, arguments)
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for idx, data_set in enumerate(data_sets, start=0):
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x_values, y_values, line_style = data_set
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result += '\nplt.plot('
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result += '%s, %s, \'%s\'' % ( x_values, y_values, line_style )
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result += ', label=\'%s try\')' % idx
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print('import matplotlib.pyplot as plt')
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print(result)
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print( 'plt.xlabel(\'Try number\')' )
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print( 'plt.ylabel(\'Timing\')' )
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print( 'plt.title(\'Benchmark query timings\')' )
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print('plt.legend()')
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print('plt.show()')
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def gen_html_json(options, arguments):
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tuples = read_stats_file(options, arguments[1])
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print('{')
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print('"system: GreenPlum(x2),')
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print('"version": "%s",' % '4.3.9.1')
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print('"data_size": 10000000,')
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print('"time": "",')
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print('"comments": "",')
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print('"result":')
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print('[')
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for s in tuples:
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print(s)
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print(']')
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print('}')
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def main():
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( options, arguments ) = parse_args()
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if len(arguments) > 2:
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gen_pyplot_code(options, arguments)
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else:
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gen_html_json(options, arguments)
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if __name__ == '__main__':
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main()
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