def mapreduce(job_class):
job = job_class()
step_count = len(job._steps)
# if temporary directory root does not exist, create one
tmp_root = job._settings.tmp_dir
if not os.path.exists(tmp_root):
os.makedirs(tmp_root)
tmp_dirs = [mkdtemp(dir=tmp_root, prefix="step%d." % i) for i in range(step_count)]
input_file_lists = [job._settings.input_files]
for step, out_dir in zip(job._steps, tmp_dirs):
n_reducers = step.n_reducers
reduce_format = os.path.join(out_dir, "reduce.out.%d")
ff = [reduce_format % n for n in range(n_reducers)]
input_file_lists.append(ff)
logger.info("Input files: {}".format(input_file_lists))
# if output directory root does not exist, create one
output_dir = job._settings.output_dir
if not os.path.exists(output_dir):
os.makedirs(output_dir)
for i, step in enumerate(job._steps):
cmd_opts = [
EXEC_SCRIPT,
"mrdomino.step",
"--step_idx",
i,
"--total_steps",
step_count,
"--input_files",
" ".join(input_file_lists[i]),
"--work_dir",
tmp_dirs[i],
"--output_dir",
output_dir,
"--job_module",
sys.modules[job.__module__].__file__,
"--job_class",
job.__class__.__name__,
"--use_domino",
int(job._settings.use_domino),
"--n_concurrent_machines",
job._settings.n_concurrent_machines,
"--n_shards_per_machine",
job._settings.n_shards_per_machine,
]
cmd = util.create_cmd(cmd_opts)
logger.info("Starting step %d with command: %s" % (i, cmd))
util.wait_cmd(cmd, logger, "Step %d" % i)
logger.info("All done.")
def main():
args = parse_args()
logger.info('Mapreduce step: %s', args)
logger.info('%d input files.', len(args.input_files))
work_dir = args.work_dir
logger.info('Working directory: %s', work_dir)
job = get_instance(args)
step = job.get_step(args.step_idx)
logger.info('Starting %d mappers.', step.n_mappers)
# create map command
cmd_opts = [
'mrdomino.map_one_machine',
'--step_idx', args.step_idx,
'--shards', '%s',
'--input_files', ' '.join(args.input_files),
'--job_module', args.job_module,
'--job_class', args.job_class,
'--work_dir', work_dir
]
cmd = create_cmd(cmd_opts)
schedule_machines(
args,
command=cmd,
done_file_pattern=os.path.join(work_dir, 'map.done.%d'),
n_shards=step.n_mappers)
counter = combine_counters(
work_dir, step.n_mappers, step.n_reducers)
# shuffle mapper outputs to reducer inputs.
cmd = create_cmd([EXEC_SCRIPT, 'mrdomino.shuffle',
'--work_dir', work_dir,
'--input_prefix', 'map.out',
'--output_prefix', 'reduce.in',
'--job_module', args.job_module,
'--job_class', args.job_class,
'--step_idx', args.step_idx])
wait_cmd(cmd, logger, "Shuffling")
logger.info('Starting %d reducers.', step.n_reducers)
cmd = create_cmd(['mrdomino.reduce_one_machine',
'--step_idx', args.step_idx,
'--shards', '%s',
'--job_module', args.job_module,
'--job_class', args.job_class,
'--input_prefix', 'reduce.in',
'--work_dir', work_dir])
schedule_machines(
args,
command=cmd,
done_file_pattern=os.path.join(work_dir, 'reduce.done.%d'),
n_shards=step.n_reducers)
counter = combine_counters(
work_dir, step.n_mappers, step.n_reducers)
logger.info(('Step %d counters:\n' % args.step_idx) + counter.show())
if args.step_idx == args.total_steps - 1:
logger.info('Joining reduce outputs')
if job.INTERNAL_PROTOCOL == protocol.JSONProtocol and \
job.OUTPUT_PROTOCOL == protocol.JSONValueProtocol:
unpack_tuple = True
elif job.INTERNAL_PROTOCOL == protocol.JSONValueProtocol and \
job.OUTPUT_PROTOCOL == protocol.JSONProtocol:
raise RuntimeError("if internal protocol is value-based, "
"output protocol must also be so")
elif job.INTERNAL_PROTOCOL == protocol.JSONProtocol and \
job.OUTPUT_PROTOCOL == protocol.JSONProtocol:
unpack_tuple = False
elif job.INTERNAL_PROTOCOL == protocol.JSONValueProtocol and \
job.OUTPUT_PROTOCOL == protocol.JSONValueProtocol:
unpack_tuple = False
else:
raise ValueError("unsupported output protocol: {}"
.format(job.OUTPUT_PROTOCOL))
# make sure that files are sorted by shard number
glob_prefix = 'reduce.out'
filenames = glob(path_join(work_dir, glob_prefix + '.[0-9]*'))
prefix_match = re.compile('.*\\b' + glob_prefix + '\\.(\\d+)$')
presorted = []
for filename in filenames:
match = prefix_match.match(filename)
if match is not None:
presorted.append((int(match.group(1)), filename))
filenames = [filename[1] for filename in sorted(presorted)]
out_f = path_join(args.output_dir, 'reduce.out')
with open(out_f, 'w') as out_fh:
for kv in read_lines(filenames):
if unpack_tuple:
_, v = json.loads(kv)
v = json.dumps(v) + "\n"
else:
v = kv
out_fh.write(v)
# done.
logger.info('Mapreduce step done.')
