def __match_index(self, file):
"""获取unixbench屏幕输出
"""
result_dic = {}.fromkeys(unixbench_keys, 0)
result_lines = lutils.read_all_lines(file)
# flag_dic = {}
for parallel in self.parallels:
re_match = "\d+ CPU\S in system; running %d parallel cop\S+ of tests" % parallel
parallel_result_dic = result_dic.copy()
for line in result_lines:
if re.search(re_match, line, re.I):
parallel_index = result_lines.index(line)
paralell_result_list = [
self.__get_value(result_lines, parallel_index + index)
for index in (16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29)
]
for l, v in zip(
tuple(unixbench_keys), tuple([lutils.change_type(i) for i in paralell_result_list])
):
parallel_result_dic[l] = "%.1f" % v
parallel_result_attrib = self.create_result_node_attrib(
"Average", self.times, parallel, self.parallels
)
self.result_list.append([parallel_result_attrib, parallel_result_dic])
def create_result(self):
'''创建result_list
'''
key_dic = {}
sum_dic = {}
file = os.path.join(self.tmp_dir, "bonnie.out")
lptlog.debug("读取 %s 文件" % file)
if not os.path.isfile(file):
raise IOError, "open %s Error" % file
else:
results_lines = utils.read_all_lines(file)
labels = ["name","file_size","putc","putc_cpu","put_block","put_block_cpu","rewrite","rewrite_cpu",
"getc","getc_cpu","get_block","get_block_cpu","seeks","seeks_cpu","num_files","seq_create",
"seq_create_cpu","seq_stat","seq_stat_cpu","seq_del","seq_del_cpu","ran_create","ran_create_cpu",
"ran_stat","ran_stat_cpu","ran_del","ran_del_cpu" ]
keys = labels
keys.pop(0)
keys.pop(0)
keys.pop(12)
keys = tuple(keys)
iter=0
for line in results_lines:
fields = line.split(',')
if len(fields) != 27:
continue
if fields[0] == "name":
continue
else:
iter += 1
lptlog.debug("line.split==27: %s" % line)
#attrib_dic = {'iter':str(iter), 'times':str(self.times), 'parallel':'1', 'parallels':'1' ,
#"name":fields[0], "filesize":fields[1], "num_files":fields[14]}
attrib_dic = self.create_result_node_attrib(iter, self.times, 1, [1])
#remove 多余项
fields.pop(0)
fields.pop(0)
fields.pop(12)
fields = tuple([utils.change_type(i) for i in fields])
for l, v in zip(keys, fields):
key_dic[l] = "%d" % v
if not sum_dic:
sum_dic = key_dic.copy()
else:
sum_dic = method.append_sum_dict(sum_dic, key_dic)
self.result_list.append([attrib_dic, key_dic])
if sum_dic:
parallel_average_dic = method.append_average_dict(sum_dic, self.times)
lptlog.debug("1 并行求平均值:PASS" )
sum_attrib_dic = self.create_result_node_attrib("Average", self.times, 1, [1])
self.result_list.append([sum_attrib_dic, parallel_average_dic])
def __match_index(self, file):
'''获取unixbench屏幕输出
'''
result_dic = {}.fromkeys(unixbench_keys, 0)
result_lines = lutils.read_all_lines(file)
# flag_dic = {}
for parallel in self.parallels:
re_match = "\d+ CPU\S in system; running %d parallel cop\S+ of tests" % parallel
parallel_result_dic = result_dic.copy()
for line in result_lines:
if re.search(re_match, line, re.I):
parallel_index = result_lines.index(line)
paralell_result_list = [
self.__get_value(result_lines, parallel_index + index)
for index in (16, 17, 18, 19, 20, 21, 22, 23, 24, 25,
26, 27, 29)
]
for l, v in zip(
tuple(unixbench_keys),
tuple([
lutils.change_type(i)
for i in paralell_result_list
])):
parallel_result_dic[l] = "%.1f" % v
parallel_result_attrib = self.create_result_node_attrib(
"Average", self.times, parallel, self.parallels)
self.result_list.append(
[parallel_result_attrib, parallel_result_dic])
def __match_index(self, file):
'''获取unixbench屏幕输出
'''
self.parallels = [1]
self.times = 3
result_dic = {}.fromkeys(x11perf_keys, 0)
result_lines = utils.read_all_lines(file)
for parallel in self.parallels:
re_match = "[\d]+ CPUs in system; running %d parallel copy of tests" % parallel
parallel_result_dic = result_dic.copy()
for line in result_lines:
if re.search(re_match, line, re.I):
parallel_index = result_lines.index(line)
paralell_result_list = [
self.__get_value(result_lines, parallel_index + index)
for index in (10, 11, 12, 13, 14, 15)
]
for l, v in zip(
tuple(x11perf_keys),
tuple([
utils.change_type(i)
for i in paralell_result_list
])):
parallel_result_dic[l] = "%.1f" % v
parallel_result_attrib = self.create_result_node_attrib(
"Average", self.times, parallel, self.parallels)
self.result_list.append(
[parallel_result_attrib, parallel_result_dic])
def __match_index(self, file):
if not os.path.isfile(file):
return []
lptlog.debug("在%s中搜索测试指标" % file)
results_lines = utils.read_all_lines(file)
result_list = []
labels = ('TCP_STREAM','UDP_STREAM', 'TCP_RR', 'UDP_RR', 'TCP_CRR')
parallel_template = {'parallels': '1', 'parallel': '1', 'iter': '1', 'times': '2'}
result1 = (results_lines[6].split()[4],results_lines[13].split()[3],results_lines[21].split()[5],results_lines[29].split()[5],results_lines[37].split()[5])
result2 = (results_lines[45].split()[4],results_lines[52].split()[3],results_lines[60].split()[5],results_lines[68].split()[5],results_lines[76].split()[5])
tmp_list = []
parallel_dict = copy.deepcopy(parallel_template)
tmp_list.append(parallel_dict)
tmp_list.append(self.dict_generator(labels,result1))
result_list.append(tmp_list)
tmp_list = []
parallel_dict = copy.deepcopy(parallel_template)
parallel_dict['iter'] = '2'
tmp_list.append(parallel_dict)
tmp_list.append(self.dict_generator(labels,result2))
result_list.append(tmp_list)
tmp_list = []
parallel_dict = copy.deepcopy(parallel_template)
parallel_dict['iter'] = 'Average'
tmp_list.append(parallel_dict)
tmp_list.append(self.dict_average(result_list[0][1],result_list[1][1]))
result_list.append(tmp_list)
return result_list
def __match_index(self, file):
'''
@return: 测试指标，dict
@attention: 采用autotest中部分代码
'''
keylist = {}
if not os.path.isfile(file):
return []
lptlog.debug("在%s中搜索测试指标" % file)
results_lines = utils.read_all_lines(file)
if self.testmode == "speed":
#labels = ('write', 'rewrite', 'read', 'reread', 'randread','randwrite',
# 'bkwdread', 'recordrewrite', 'strideread', 'fwrite',
# 'frewrite', 'fread', 'freread')
labels = ('write', 'rewrite', 'read', 'reread', 'randread',
'randwrite')
for line in results_lines:
fields = line.split()
if len(fields) != 8:
continue
lptlog.debug("line.split==8: %s" % line)
try:
fields = tuple([int(i) for i in fields])
except Exception:
continue
for l, v in zip(labels, fields[2:]):
key_name = "%s" % l
keylist[key_name] = "%d" % v
else:
child_regexp = re.compile(
r'Children see throughput for[\s]+([\d]+)[\s]+([\S]+|[\S]+[\s][\S]+)[\s]+=[\s]+([\w]+)*'
)
section = None
w_count = 0
for line in results_lines:
line = line.strip()
# Check for the beginning of a new result section
match = child_regexp.search(line)
if match:
# Extract the section name and the worker count
w_count = int(match.group(1))
lptlog.debug("w_count:%s" % w_count)
section = self.__get_section_name(match.group(2))
lptlog.debug("section:%s" % section)
# Output the appropriate keyval pair
#key_name = '%s-kids' % section
#keylist[key_name] = match.group(3)
keylist[section] = match.group(3)
return keylist
def __match_index(self, file):
'''
@return: 测试指标，dict
@attention: 采用autotest中部分代码
'''
keylist = {}
if not os.path.isfile(file):
return []
lptlog.debug("在%s中搜索测试指标" % file)
results_lines = lutils.read_all_lines(file)
if self.testmode == "speed":
#labels = ('write', 'rewrite', 'read', 'reread', 'randread','randwrite',
# 'bkwdread', 'recordrewrite', 'strideread', 'fwrite',
# 'frewrite', 'fread', 'freread')
labels = ('write', 'rewrite', 'read', 'reread', 'randread','randwrite')
for line in results_lines:
fields = line.split()
if len(fields) != 8:
continue
lptlog.debug("line.split==8: %s" % line)
try:
fields = tuple([int(i) for i in fields])
except Exception:
continue
for l, v in zip(labels, fields[2:]):
key_name = "%s" % l
keylist[key_name] = "%d" % v
else:
child_regexp = re.compile(r'Children see throughput for[\s]+([\d]+)[\s]+([\S]+|[\S]+[\s][\S]+)[\s]+=[\s]+([\w]+)*')
section = None
w_count = 0
for line in results_lines:
#line = line.strip()
# Check for the beginning of a new result section
match = child_regexp.search(line)
if match:
# Extract the section name and the worker count
w_count = int(match.group(1))
lptlog.debug("w_count:%s" % w_count)
section = self.__get_section_name(match.group(2))
lptlog.debug("section:%s" % section)
# Output the appropriate keyval pair
#key_name = '%s-kids' % section
#keylist[key_name] = match.group(3)
keylist[section] = match.group(3)
return keylist
def __search_result(self, file):
r= re.compile(r'Copy*',re.I)
lines = lutils.read_all_lines(file)
for line in lines:
if r.match(line):
copy = line.split()[1]
index = lines.index(line)
scale = lines[index+1].split()[1]
add = lines[index+2].split()[1]
triad = lines[index+3].split()[1]
return tuple(map(lutils.change_type, [copy, scale, add, triad]))
return (0, 0, 0, 0)
def __search_result(self, file):
r= re.compile(r'Copy*',re.I)
lines = utils.read_all_lines(file)
for line in lines:
if r.match(line):
copy = line.split()[1]
index = lines.index(line)
scale = lines[index+1].split()[1]
add = lines[index+2].split()[1]
triad = lines[index+3].split()[1]
return tuple(map(utils.change_type, [copy, scale, add, triad]))
return (0, 0, 0, 0)
def create_result(self):
'''创建result_list
'''
#labels = ("Throughtput", "clients", "max_latency")
labels = ("Throughtput", "max_latency")
parallelstring = ",".join(map(str, self.parallels))
r = re.compile(
r"Throughput\s+(\d+.\d+)\s+MB/sec\s+(\d+)\s+clients\s+\d+\s+procs\s+max_latency=(\d+.\d+)\s",
re.I)
for parallel in self.parallels:
sum_dic = {}
for iter in range(self.times):
tmp_result_file = os.path.join(
self.tmp_dir,
"%s_%s_%s.out" % (self.tool, parallel, iter + 1))
if not os.path.isfile(tmp_result_file):
lptlog.warning("%s 不存在" % tmp_result_file)
continue
result_lines = utils.read_all_lines(tmp_result_file)
for line in result_lines:
key_dic = {}
if r.match(line):
m = r.match(line)
#result_list = [m.group(1), m.group(2), m.group(3)]
result_list = [m.group(1), m.group(3)]
result_tuple = tuple(
[utils.change_type(i) for i in result_list])
for l, v in zip(labels, result_tuple):
key_dic[l] = "%d" % v
if not sum_dic:
sum_dic = key_dic.copy()
else:
sum_dic = method.append_sum_dict(sum_dic, key_dic)
self.result_list.append([
self.create_result_node_attrib(
iter + 1, self.times, parallel,
self.parallels), key_dic
])
if sum_dic:
parallel_average_dic = method.append_average_dict(
sum_dic, self.times)
lptlog.debug("%d 并行求平均值:PASS" % parallel)
self.result_list.append([
self.create_result_node_attrib("Average", self.times,
parallel, self.parallels),
parallel_average_dic
])
def __match_index(self, game, file):
'''搜索index
@return: 返回指定game的result_list,平均值,
'''
labels = ('initialised', 'completed', 'total')
result_list = []
result_dict = {}
if not os.path.isfile(file):
lptlog.debug("%s 不存在")
return result_list
r_init_time = re.compile(
r'(?P<thread>\d+) threads initialised in (?P<initialised>\d+) usec'
)
r_complete_time = re.compile(
r"(?P<games>\d+) games completed in (?P<completed>\d+) usec")
results_lines = lutils.read_all_lines(file)
init_time_list = []
complete_time_list = []
#获取初始化时间和完成时间，返回两个list
for line in results_lines:
if r_init_time.match(line):
init_time = r_init_time.match(line).group("initialised")
init_time_list.append(init_time)
if r_complete_time.match(line):
complete_time = r_complete_time.match(line).group("completed")
complete_time_list.append(complete_time)
#初始化时间求平均值
init_time_average = lutils.average_list(
lutils.string_to_float(init_time_list), bits=0)
#完成时间求平均值
complete_time_average = lutils.average_list(
lutils.string_to_float(complete_time_list), bits=0)
sum_time = init_time_average + complete_time_average
#定义result字典
for l, v in zip(labels,
(init_time_average, complete_time_average, sum_time)):
result_dict[l] = "%d" % v
#定义result属性
result_node_attrib = self.create_result_node_attrib(
"Average", self.times, game * 2, [i * 2 for i in self.games])
result_list.append(result_dict)
result_list.insert(0, result_node_attrib)
return result_list
def __match_index(self, file):
if not os.path.isfile(file):
return []
lptlog.debug("在%s中搜索测试指标" % file)
results_lines = utils.read_all_lines(file)
labels = ('io', 'aggrb', 'minb', 'maxb', 'mint','maxt')
parallel_template = {'parallels': '1,2,3,4', 'parallel': '1', 'iter': '1', 'times': '2'}
result_list = []
count = 0
for line in results_lines:
if 'READ:' in line:
tmp_list = []
parallel_dict = copy.deepcopy(parallel_template)
parallel_dict['parallel'] = str(count / 2 + 1)
parallel_dict['iter'] = 'READ'
tmp_list.append(parallel_dict)
tmp_list.append(self.dict_generator(labels,line))
result_list.append(tmp_list)
count = count + 1
elif 'WRITE:' in line:
tmp_list = []
parallel_dict = copy.deepcopy(parallel_template)
parallel_dict['parallel'] = str(count / 2 + 1)
parallel_dict['iter'] = 'WRITE'
tmp_list.append(parallel_dict)
tmp_list.append(self.dict_generator(labels,line))
result_list.append(tmp_list)
count = count + 1
if count in [2,4,6,8]:
tmp_list = []
dict2 = result_list[-1][1]
dict1 = result_list[-2][1]
parallel_dict = copy.deepcopy(parallel_template)
parallel_dict['parallel'] = str(count / 2)
parallel_dict['iter'] = 'Average'
tmp_list.append(parallel_dict)
tmp_list.append(self.dict_average(dict1, dict2))
result_list.append(tmp_list)
return result_list
def __match_index(self, file):
'''获取unixbench屏幕输出
'''
self.parallels = [1]
self.times = 3
result_dic = {}.fromkeys(x11perf_keys, 0)
result_lines = utils.read_all_lines(file)
for parallel in self.parallels:
re_match = "[\d]+ CPUs in system; running %d parallel copy of tests" % parallel
parallel_result_dic = result_dic.copy()
for line in result_lines:
if re.search(re_match, line, re.I):
parallel_index = result_lines.index(line)
paralell_result_list = [ self.__get_value(result_lines, parallel_index+index) for index in (10, 11, 12, 13, 14, 15) ]
for l,v in zip(tuple(x11perf_keys), tuple([utils.change_type(i) for i in paralell_result_list])):
parallel_result_dic[l] = "%.1f" % v
parallel_result_attrib = self.create_result_node_attrib("Average", self.times, parallel, self.parallels)
self.result_list.append([parallel_result_attrib, parallel_result_dic])
def __match_index(self, game, file):
'''搜索index
@return: 返回指定game的result_list,平均值,
'''
labels = ('initialised', 'completed', 'total')
result_list = []
result_dict = {}
if not os.path.isfile(file):
lptlog.debug("%s 不存在")
return result_list
r_init_time = re.compile(r'(?P<thread>\d+) threads initialised in (?P<initialised>\d+) usec')
r_complete_time = re.compile(r"(?P<games>\d+) games completed in (?P<completed>\d+) usec")
results_lines = utils.read_all_lines(file)
init_time_list = []
complete_time_list = []
#获取初始化时间和完成时间，返回两个list
for line in results_lines:
if r_init_time.match(line):
init_time = r_init_time.match(line).group("initialised")
init_time_list.append(init_time)
if r_complete_time.match(line):
complete_time = r_complete_time.match(line).group("completed")
complete_time_list.append(complete_time)
#初始化时间求平均值
init_time_average = utils.average_list(utils.string_to_float(init_time_list), bits=0)
#完成时间求平均值
complete_time_average = utils.average_list(utils.string_to_float(complete_time_list), bits=0)
sum_time = init_time_average + complete_time_average
#定义result字典
for l,v in zip(labels, (init_time_average, complete_time_average, sum_time)):
result_dict[l] = "%d" % v
#定义result属性
result_node_attrib = self.create_result_node_attrib("Average", self.times, game*2, [i*2 for i in self.games])
result_list.append(result_dict)
result_list.insert(0, result_node_attrib)
return result_list
def create_result(self):
'''创建result_list
'''
#labels = ("Throughtput", "clients", "max_latency")
labels = ("Throughtput", "max_latency")
parallelstring = ",".join(map(str, self.parallels))
r = re.compile(r"Throughput\s+(\d+.\d+)\s+MB/sec\s+(\d+)\s+clients\s+\d+\s+procs\s+max_latency=(\d+.\d+)\s", re.I)
for parallel in self.parallels:
sum_dic = {}
for iter in range(self.times):
tmp_result_file = os.path.join(self.tmp_dir, "%s_%s_%s.out" % (self.tool, parallel, iter+1))
if not os.path.isfile(tmp_result_file):
lptlog.warning("%s 不存在" % tmp_result_file)
continue
result_lines = utils.read_all_lines(tmp_result_file)
for line in result_lines:
key_dic = {}
if r.match(line):
m = r.match(line)
#result_list = [m.group(1), m.group(2), m.group(3)]
result_list = [m.group(1), m.group(3)]
result_tuple = tuple([utils.change_type(i)for i in result_list])
for l, v in zip(labels, result_tuple):
key_dic[l] = "%d" % v
if not sum_dic:
sum_dic = key_dic.copy()
else:
sum_dic = method.append_sum_dict(sum_dic, key_dic)
self.result_list.append([self.create_result_node_attrib(iter+1, self.times, parallel, self.parallels), key_dic])
if sum_dic:
parallel_average_dic = method.append_average_dict(sum_dic, self.times)
lptlog.debug("%d 并行求平均值:PASS" % parallel)
self.result_list.append([self.create_result_node_attrib("Average", self.times, parallel, self.parallels), parallel_average_dic])
