def invoke(executor_id, job_id, call_id, func_key, invoke_metadata,
data_key, data_byte_range):
output_key = create_output_key(self.storage_config['prefix'],
executor_id, job_id, call_id)
status_key = create_status_key(self.storage_config['prefix'],
executor_id, job_id, call_id)
payload = {
'config': self.config,
'log_level': self.log_level,
'func_key': func_key,
'data_key': data_key,
'output_key': output_key,
'status_key': status_key,
'task_execution_timeout': job.task_execution_timeout,
'data_byte_range': data_byte_range,
'executor_id': executor_id,
'job_id': job_id,
'call_id': call_id,
'pywren_version': __version__
}
if job.extra_env is not None:
logger.debug("Extra environment vars {}".format(job.extra_env))
payload['extra_env'] = job.extra_env
if job.extra_meta is not None:
# sanity
for k, v in job.extra_meta.items():
if k in payload:
raise ValueError("Key {} already in dict".format(k))
payload[k] = v
# overwrite explicit args, mostly used for testing via injection
if job.overwrite_invoke_args is not None:
payload.update(job.overwrite_invoke_args)
host_submit_time = time.time()
payload['host_submit_time'] = host_submit_time
# do the invocation
activation_id = self.internal_compute.invoke(
job.runtime_name, job.runtime_memory, payload)
if not activation_id:
raise Exception(
"ExecutorID {} - Activation {} failed, therefore job is failed"
.format(executor_id, call_id))
invoke_metadata['activation_id'] = activation_id
invoke_metadata['invoke_time'] = time.time() - host_submit_time
invoke_metadata.update(payload)
del invoke_metadata['config']
fut = ResponseFuture(call_id, job_id, executor_id, activation_id,
self.storage_config, invoke_metadata)
fut._set_state(JobState.invoked)
return fut
def get_call_output(self, executor_id, job_id, call_id):
"""
Get the output of a call.
:param executor_id: executor ID of the call
:param call_id: call ID of the call
:return: Output of the call.
"""
output_key = create_output_key(JOBS_PREFIX, executor_id, job_id, call_id)
try:
return self.storage_handler.get_object(self.bucket, output_key)
except StorageNoSuchKeyError:
return None
def invoke(executor_id, job_id, call_id, func_key, invoke_metadata,
data_key, data_byte_range):
output_key = create_output_key(self.storage_config['prefix'],
executor_id, job_id, call_id)
status_key = create_status_key(self.storage_config['prefix'],
executor_id, job_id, call_id)
payload = {
'config': self.config,
'log_level': self.log_level,
'func_key': func_key,
'data_key': data_key,
'output_key': output_key,
'status_key': status_key,
'execution_timeout': job.execution_timeout,
'data_byte_range': data_byte_range,
'executor_id': executor_id,
'job_id': job_id,
'call_id': call_id,
'pywren_version': __version__
}
if job.extra_env is not None:
logger.debug("Extra environment vars {}".format(job.extra_env))
payload['extra_env'] = job.extra_env
host_submit_time = time.time()
payload['host_submit_time'] = host_submit_time
# do the invocation
activation_id = self.compute.invoke(job.runtime_name,
job.runtime_memory, payload)
if not activation_id:
raise Exception(
"ExecutorID {} | JobID {} - Retrying mechanism finished with no success. "
"Failed to invoke the job".format(executor_id, job_id))
invoke_metadata['activation_id'] = activation_id
invoke_metadata['invoke_time'] = time.time() - host_submit_time
invoke_metadata.update(payload)
del invoke_metadata['config']
fut = ResponseFuture(call_id, job_id, executor_id, activation_id,
self.storage_config, invoke_metadata)
fut._set_state(CallState.invoked)
return fut
def _invoke(self, job, call_id):
"""
Method used to perform the actual invocation against the Compute Backend
"""
output_key = create_output_key(JOBS_PREFIX, job.executor_id,
job.job_id, call_id)
status_key = create_status_key(JOBS_PREFIX, job.executor_id,
job.job_id, call_id)
payload = {
'config': self.config,
'log_level': self.log_level,
'func_key': job.func_key,
'data_key': job.data_key,
'output_key': output_key,
'status_key': status_key,
'extra_env': job.extra_env,
'execution_timeout': job.execution_timeout,
'data_byte_range': job.data_ranges[int(call_id)],
'executor_id': job.executor_id,
'job_id': job.job_id,
'call_id': call_id,
'host_submit_time': time.time(),
'pywren_version': __version__
}
# do the invocation
start = time.time()
compute_handler = random.choice(self.compute_handlers)
activation_id = compute_handler.invoke(job.runtime_name,
job.runtime_memory, payload)
roundtrip = time.time() - start
resp_time = format(round(roundtrip, 3), '.3f')
if not activation_id:
self.pending_calls_q.put((job, call_id))
return
logger.debug(
'ExecutorID {} | JobID {} - Function invocation {} done! ({}s) - Activation'
' ID: {}'.format(job.executor_id, job.job_id, call_id, resp_time,
activation_id))
return call_id
def invoke(executor_id, job_id, call_id, func_key, job_metadata,
data_key, data_byte_range):
output_key = create_output_key(self.storage_config['prefix'],
executor_id, job_id, call_id)
status_key = create_status_key(self.storage_config['prefix'],
executor_id, job_id, call_id)
payload = {
'config': self.pywren_config,
'log_level': self.log_level,
'func_key': func_key,
'data_key': data_key,
'output_key': output_key,
'status_key': status_key,
'extra_env': job.extra_env,
'execution_timeout': job.execution_timeout,
'data_byte_range': data_byte_range,
'executor_id': executor_id,
'job_id': job_id,
'call_id': call_id,
'host_submit_time': time.time(),
'pywren_version': __version__
}
# do the invocation
compute_handler = random.choice(self.compute_handlers)
activation_id = compute_handler.invoke(job.runtime_name,
job.runtime_memory, payload)
if not activation_id:
raise Exception(
"ExecutorID {} | JobID {} - Retrying mechanism finished with no success. "
"Failed to invoke the job".format(executor_id, job_id))
job_metadata['activation_id'] = activation_id
fut = ResponseFuture(executor_id, job_id, call_id,
self.storage_config, job_metadata)
fut._set_state(ResponseFuture.State.Invoked)
return fut
def function_handler(event):
start_tstamp = time.time()
log_level = event['log_level']
cloud_logging_config(log_level)
logger.debug("Action handler started")
extra_env = event.get('extra_env', {})
os.environ.update(extra_env)
os.environ.update({'PYWREN_FUNCTION': 'True', 'PYTHONUNBUFFERED': 'True'})
config = event['config']
call_id = event['call_id']
job_id = event['job_id']
executor_id = event['executor_id']
exec_id = "{}/{}/{}".format(executor_id, job_id, call_id)
logger.info("Execution-ID: {}".format(exec_id))
runtime_name = event['runtime_name']
runtime_memory = event['runtime_memory']
execution_timeout = event['execution_timeout']
logger.debug("Runtime name: {}".format(runtime_name))
logger.debug("Runtime memory: {}MB".format(runtime_memory))
logger.debug("Function timeout: {}s".format(execution_timeout))
func_key = event['func_key']
data_key = event['data_key']
data_byte_range = event['data_byte_range']
storage_config = extract_storage_config(config)
internal_storage = InternalStorage(storage_config)
call_status = CallStatus(config, internal_storage)
call_status.response['host_submit_tstamp'] = event['host_submit_tstamp']
call_status.response['start_tstamp'] = start_tstamp
context_dict = {
'python_version': os.environ.get("PYTHON_VERSION"),
'call_id': call_id,
'job_id': job_id,
'executor_id': executor_id,
'activation_id': os.environ.get('__PW_ACTIVATION_ID')
}
call_status.response.update(context_dict)
show_memory_peak = strtobool(os.environ.get('SHOW_MEMORY_PEAK', 'False'))
try:
if version.__version__ != event['pywren_version']:
msg = (
"PyWren version mismatch. Host version: {} - Runtime version: {}"
.format(event['pywren_version'], version.__version__))
raise RuntimeError('HANDLER', msg)
# send init status event
call_status.send('__init__')
# call_status.response['free_disk_bytes'] = free_disk_space("/tmp")
custom_env = {
'PYWREN_CONFIG': json.dumps(config),
'PYWREN_EXECUTION_ID': exec_id,
'PYTHONPATH': "{}:{}".format(os.getcwd(), PYWREN_LIBS_PATH)
}
os.environ.update(custom_env)
jobrunner_stats_dir = os.path.join(STORAGE_FOLDER,
storage_config['bucket'],
JOBS_PREFIX, executor_id, job_id,
call_id)
os.makedirs(jobrunner_stats_dir, exist_ok=True)
jobrunner_stats_filename = os.path.join(jobrunner_stats_dir,
'jobrunner.stats.txt')
jobrunner_config = {
'pywren_config':
config,
'call_id':
call_id,
'job_id':
job_id,
'executor_id':
executor_id,
'func_key':
func_key,
'data_key':
data_key,
'log_level':
log_level,
'data_byte_range':
data_byte_range,
'output_key':
create_output_key(JOBS_PREFIX, executor_id, job_id, call_id),
'stats_filename':
jobrunner_stats_filename
}
if show_memory_peak:
mm_handler_conn, mm_conn = Pipe()
memory_monitor = Thread(target=memory_monitor_worker,
args=(mm_conn, ))
memory_monitor.start()
handler_conn, jobrunner_conn = Pipe()
jobrunner = JobRunner(jobrunner_config, jobrunner_conn,
internal_storage)
logger.debug('Starting JobRunner process')
local_execution = strtobool(
os.environ.get('__PW_LOCAL_EXECUTION', 'False'))
jrp = Thread(target=jobrunner.run) if local_execution else Process(
target=jobrunner.run)
jrp.start()
jrp.join(execution_timeout)
logger.debug('JobRunner process finished')
if jrp.is_alive():
# If process is still alive after jr.join(job_max_runtime), kill it
try:
jrp.terminate()
except Exception:
# thread does not have terminate method
pass
msg = ('Function exceeded maximum time of {} seconds and was '
'killed'.format(execution_timeout))
raise TimeoutError('HANDLER', msg)
if show_memory_peak:
mm_handler_conn.send('STOP')
memory_monitor.join()
peak_memory_usage = int(mm_handler_conn.recv())
logger.info("Peak memory usage: {}".format(
sizeof_fmt(peak_memory_usage)))
call_status.response['peak_memory_usage'] = peak_memory_usage
if not handler_conn.poll():
logger.error(
'No completion message received from JobRunner process')
logger.debug('Assuming memory overflow...')
# Only 1 message is returned by jobrunner when it finishes.
# If no message, this means that the jobrunner process was killed.
# 99% of times the jobrunner is killed due an OOM, so we assume here an OOM.
msg = 'Function exceeded maximum memory and was killed'
raise MemoryError('HANDLER', msg)
if os.path.exists(jobrunner_stats_filename):
with open(jobrunner_stats_filename, 'r') as fid:
for l in fid.readlines():
key, value = l.strip().split(" ", 1)
try:
call_status.response[key] = float(value)
except Exception:
call_status.response[key] = value
if key in [
'exception', 'exc_pickle_fail', 'result',
'new_futures'
]:
call_status.response[key] = eval(value)
except Exception:
# internal runtime exceptions
print('----------------------- EXCEPTION !-----------------------',
flush=True)
traceback.print_exc(file=sys.stdout)
print('----------------------------------------------------------',
flush=True)
call_status.response['exception'] = True
pickled_exc = pickle.dumps(sys.exc_info())
pickle.loads(
pickled_exc) # this is just to make sure they can be unpickled
call_status.response['exc_info'] = str(pickled_exc)
finally:
call_status.response['end_tstamp'] = time.time()
call_status.send('__end__')
for key in extra_env:
os.environ.pop(key)
logger.info("Finished")
def function_handler(event):
start_time = time.time()
log_level = event['log_level']
cloud_logging_config(log_level)
logger.debug("Action handler started")
extra_env = event.get('extra_env', {})
os.environ.update(extra_env)
config = event['config']
call_status = CallStatus(config)
call_status.response['host_submit_time'] = event['host_submit_time']
call_status.response['start_time'] = start_time
context_dict = {
'python_version': os.environ.get("PYTHON_VERSION"),
}
call_id = event['call_id']
job_id = event['job_id']
executor_id = event['executor_id']
exec_id = "{}/{}/{}".format(executor_id, job_id, call_id)
logger.info("Execution ID: {}".format(exec_id))
execution_timeout = event['execution_timeout']
logger.debug("Set function execution timeout to {}s".format(execution_timeout))
func_key = event['func_key']
data_key = event['data_key']
data_byte_range = event['data_byte_range']
call_status.response['call_id'] = call_id
call_status.response['job_id'] = job_id
call_status.response['executor_id'] = executor_id
call_status.response['activation_id'] = os.environ.get('__OW_ACTIVATION_ID')
try:
if version.__version__ != event['pywren_version']:
raise Exception("WRONGVERSION", "PyWren version mismatch",
version.__version__, event['pywren_version'])
# send init status event
call_status.send('__init__')
# call_status.response['free_disk_bytes'] = free_disk_space("/tmp")
custom_env = {'PYWREN_CONFIG': json.dumps(config),
'PYWREN_FUNCTION': 'True',
'PYWREN_EXECUTION_ID': exec_id,
'PYWREN_STORAGE_BUCKET': config['pywren']['storage_bucket'],
'PYTHONPATH': "{}:{}".format(os.getcwd(), PYWREN_LIBS_PATH),
'PYTHONUNBUFFERED': 'True'}
os.environ.update(custom_env)
# if os.path.exists(JOBRUNNER_STATS_BASE_DIR):
# shutil.rmtree(JOBRUNNER_STATS_BASE_DIR, True)
jobrunner_stats_dir = os.path.join(STORAGE_BASE_DIR, executor_id, job_id, call_id)
os.makedirs(jobrunner_stats_dir, exist_ok=True)
jobrunner_stats_filename = os.path.join(jobrunner_stats_dir, 'jobrunner.stats.txt')
jobrunner_config = {'pywren_config': config,
'call_id': call_id,
'job_id': job_id,
'executor_id': executor_id,
'func_key': func_key,
'data_key': data_key,
'log_level': log_level,
'data_byte_range': data_byte_range,
'output_key': create_output_key(JOBS_PREFIX, executor_id, job_id, call_id),
'stats_filename': jobrunner_stats_filename}
setup_time = time.time()
call_status.response['setup_time'] = round(setup_time - start_time, 8)
handler_conn, jobrunner_conn = Pipe()
jobrunner = JobRunner(jobrunner_config, jobrunner_conn)
logger.debug('Starting JobRunner process')
local_execution = strtobool(os.environ.get('LOCAL_EXECUTION', 'False'))
if local_execution:
jrp = Thread(target=jobrunner.run)
else:
jrp = Process(target=jobrunner.run)
jrp.daemon = True
jrp.start()
jrp.join(execution_timeout)
logger.debug('JobRunner process finished')
call_status.response['exec_time'] = round(time.time() - setup_time, 8)
if jrp.is_alive():
# If process is still alive after jr.join(job_max_runtime), kill it
try:
jrp.terminate()
except Exception:
# thread does not have terminate method
pass
msg = ('Jobrunner process exceeded maximum time of {} '
'seconds and was killed'.format(execution_timeout))
raise Exception('OUTATIME', msg)
try:
handler_conn.recv()
except EOFError:
logger.error('No completion message received from JobRunner process')
logger.debug('Assuming memory overflow...')
# Only 1 message is returned by jobrunner when it finishes.
# If no message, this means that the jobrunner process was killed.
# 99% of times the jobrunner is killed due an OOM, so we assume here an OOM.
msg = 'Jobrunner process exceeded maximum memory and was killed'
raise Exception('OUTOFMEMORY', msg)
# print(subprocess.check_output("find {}".format(PYTHON_MODULE_PATH), shell=True))
# print(subprocess.check_output("find {}".format(os.getcwd()), shell=True))
if os.path.exists(jobrunner_stats_filename):
with open(jobrunner_stats_filename, 'r') as fid:
for l in fid.readlines():
key, value = l.strip().split(" ", 1)
try:
call_status.response[key] = float(value)
except Exception:
call_status.response[key] = value
if key in ['exception', 'exc_pickle_fail', 'result', 'new_futures']:
call_status.response[key] = eval(value)
# call_status.response['server_info'] = get_server_info()
call_status.response.update(context_dict)
call_status.response['end_time'] = time.time()
except Exception:
# internal runtime exceptions
print('----------------------- EXCEPTION !-----------------------', flush=True)
traceback.print_exc(file=sys.stdout)
print('----------------------------------------------------------', flush=True)
call_status.response['end_time'] = time.time()
call_status.response['exception'] = True
pickled_exc = pickle.dumps(sys.exc_info())
pickle.loads(pickled_exc) # this is just to make sure they can be unpickled
call_status.response['exc_info'] = str(pickled_exc)
finally:
call_status.send('__end__')
logger.info("Finished")