def wait_for_config():
'''
Waits for the master to set the Job config
'''
logging.info("{0} waiting for config".format(job_id))
while True:
config = kv.read_store(kv_conn, job_id + '_config')
if config != '\r':
return config
else:
continue
def consolidate_output(reducer_jobids: list, output_file_path: str):
'''
Consolidate reducer results and write to output file
'''
reducer_output = [
kv.read_store(kv_conn, job_id + '_result').replace('\r,', '\n')
for job_id in reducer_jobids
]
with open(output_file_path, 'w', encoding="utf8",
errors='ignore') as output:
output.writelines(reducer_output)
def wait_for_reducers(reducer_jobids: list):
'''
Poll and waits for Reducer Jobs to complete
'''
while True:
statuses = [
kv.read_store(kv_conn, job_id + '_status')
for job_id in reducer_jobids
]
if all(status == "DONE\r" for status in statuses):
logging.debug("Reducers Completed - status\n{0}".format(statuses))
break
else:
continue
def get_job_status():
'''
This API route is used to get the current Job status given a Job ID
Returns Job output if the Job has completed
'''
try:
job_id = request.args.get('jobid')
logging.info("Getting status for job : {0}".format(job_id))
conn = kv.get_store_connection()
status = kv.read_store(conn, "{0}_status".format(job_id))
if status == "COMPLETED\r":
kv.close_store_connection(conn)
return send_from_directory('output',
filename='output_{}.txt'.format(job_id))
else:
kv.close_store_connection(conn)
return status
except Exception as e:
logging.error("Job status check failed : %s", e)
kv.close_store_connection(conn)
return "ERROR : Job status check failed"
def main():
'''
The driver function that runs the Map job
'''
try:
if job_id == None:
logging.critical("Job Initialization Error! ABORTING")
exit()
# Step 1 : Wait for Map Job config
config = json.loads(wait_for_config())
reducer_node = config['reducer_node']
# Step 2 : Update status as started
res = kv.set_command(kv_conn, job_id + '_status',
len("STARTED".encode()), "STARTED")
if res != "STORED\r\n":
logging.error("Status set failure : %s", res)
logging.critical("ABORTING")
exit()
# Step 3 : Read Mapper Input
message = kv.read_store(kv_conn, job_id + '_input')
message_list = message.split('#\r#')[1:]
map_result = []
# Step 4 : Run map job based on input file
for i in range(0, len(message_list), 2):
map_result = map_result + run_map(bytes(
config['map_fn']), message_list[i], message_list[i + 1])
# Step 5 : Partition Map results
partition_map = partition_intermediate_results(map_result,
len(reducer_node),
reducer_node)
# Step 6 : Store Map results
store_intermediate_results(partition_map)
except Exception as e:
logging.critical("JOB FAILED : %s", e)
res = kv.set_command(kv_conn, job_id + '_status',
len("FAILED".encode()), "FAILED")
finally:
kv.close_store_connection(kv_conn)
def main():
'''
The driver function that runs the Reduce job
'''
try:
if job_id == None:
logging.critical("Job Initialization Error! ABORTING")
exit()
# Step 1 : Wait for Reduce Job config
config = json.loads(wait_for_config())
partition_key = config['partition_key']
# Step 2 : Update status as started
res = kv.set_command(kv_conn, job_id + '_status',
len("STARTED".encode()), "STARTED")
if res != "STORED\r\n":
logging.error("Status set failure : %s", res)
logging.critical("ABORTING")
exit()
# Step 3 : Read partition data from mapper
message = kv.read_store(kv_conn, partition_key)
# Step 4 : Sort intermediate data
sorted_results = sort_intermediate_results(message)
reduce_output = []
# Step 5 : Run Reduce on the sorted data
reduce_fn_serialized = bytes(config['reduce_fn'])
for key in sorted_results:
output = run_reduce(reduce_fn_serialized, key, sorted_results[key])
reduce_output.append(output)
# Step 6 : Store reduce results
store_reduce_output(reduce_output)
except Exception as e:
logging.critical("JOB FAILED : %s", e)
res = kv.set_command(kv_conn, job_id + '_status',
len("FAILED".encode()), "FAILED")
finally:
kv.close_store_connection(kv_conn)
