def test_base_mapreduce_no_parallel():
print '\nWarning: Need run at least one shard...\n'
logging.basicConfig(logging=logging.INFO, format="[%(levelname)s] %(message)s")
logging.getLogger("").setLevel(logging.INFO)
# Task file and count jobs
task_file = 'tasks' + os.sep + 'simple_mapreduce_task.py'
count_jobs = 4
# Make jobs
keys = []
for i in range(count_jobs):
keys.append(str(i))
jobs = dict((key, " ") for key in keys)
# Run
generator = do_customize_server(
task_file,
jobs,
type='simple',
transition_process_duration=1.0)
# Process response
result = 0
for i in generator:
key, (mac, cores) = i
result += cores
assert result == count_jobs
def get_count_cores(task_file, count_core_roughly, transition_process_duration=0):
# Make jobs
keys = []
for i in range(count_core_roughly):
keys.append(str(i))
jobs = dict((key, "") for key in keys)
# Run
generator = do_customize_server(task_file, jobs, type='simple')
# Process response
sum_cores = 0
for i in generator:
key, (mac, cores) = i
sum_cores += cores
return sum_cores
def run_gtests(task_file, count_cores, exe_file_name):
def _file_to_stream(filename):
f = open(filename, 'rb')
try:
return f.read()
finally:
f.close()
stream = _file_to_stream(exe_file_name)
# Create jobs
keys = []
timeout = 0
for i in range(count_cores):
keys.append(str(i)+'@'+str(count_cores)+'@'+str(timeout))
jobs = dict((key, stream) for key in keys)
return do_customize_server(task_file, jobs, type='simple')
