ClickHouse/benchmark/greenplum/result_parser.py

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3.7 KiB
Python
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2020-10-02 16:54:07 +00:00
#!/usr/bin/env python3
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),')
2020-10-02 16:54:07 +00:00
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()