ClickHouse/benchmark/greenplum/result_parser.py
2022-03-22 17:39:58 +01:00

151 lines
4.0 KiB
Python
Executable File

#!/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),')
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()