def get_all(self, limit=None, options: dict = None):
if options is None:
options = {}
if limit is not None and not isinstance(limit, int) and limit <= 0:
raise ValueError(f"limit:{limit} must be positive int")
job_id = generate_job_id(self.__session_id, RollPair.GET_ALL)
er_pair = ErPair(key=create_serdes(self.__store._store_locator._serdes)
.serialize(limit) if limit is not None else None,
value=None)
def send_command():
job = ErJob(id=job_id,
name=RollPair.GET_ALL,
inputs=[self.__store],
outputs=[self.__store],
functors=[ErFunctor(name=RollPair.GET_ALL, body=cloudpickle.dumps(er_pair))])
task_results = self._run_job(job=job)
er_store = self.__get_output_from_result(task_results)
return er_store
send_command()
populated_store = self.ctx.populate_processor(self.__store)
transfer_pair = TransferPair(transfer_id=job_id)
done_cnt = 0
for k, v in transfer_pair.gather(populated_store):
done_cnt += 1
yield self.key_serdes.deserialize(k), self.value_serdes.deserialize(v)
L.trace(f"get_all: namespace={self.get_namespace()} name={self.get_name()}, count={done_cnt}")
def get_all(self, options: dict = None):
if options is None:
options = {}
L.info('get all functor')
job_id = generate_job_id(self.__session_id, RollPair.GET_ALL)
def send_command():
job = ErJob(id=job_id,
name=RollPair.GET_ALL,
inputs=[self.__store],
outputs=[self.__store],
functors=[])
result = self.__command_client.simple_sync_send(
input=job,
output_type=ErJob,
endpoint=self.ctx.get_roll()._command_endpoint,
command_uri=CommandURI(
f'{RollPair.ROLL_PAIR_URI_PREFIX}/{RollPair.RUN_JOB}'),
serdes_type=SerdesTypes.PROTOBUF)
return result
send_command()
populated_store = self.ctx.populate_processor(self.__store)
transfer_pair = TransferPair(transfer_id=job_id)
done_cnt = 0
for k, v in transfer_pair.gather(populated_store):
done_cnt += 1
yield self.key_serdes.deserialize(
k), self.value_serdes.deserialize(v)
L.debug(f"get_all count:{done_cnt}")
def put_all(self, items, output=None, options: dict = None):
if options is None:
options = {}
include_key = options.get("include_key", True)
job_id = generate_job_id(self.__session_id, RollPair.PUT_ALL)
# TODO:1: consider multiprocessing scenario. parallel size should be sent to egg_pair to set write signal count
def send_command():
job = ErJob(id=job_id,
name=RollPair.PUT_ALL,
inputs=[self.__store],
outputs=[self.__store],
functors=[])
result = self.__command_client.simple_sync_send(
input=job,
output_type=ErJob,
endpoint=self.ctx.get_roll()._command_endpoint,
command_uri=CommandURI(
f'{RollPair.ROLL_PAIR_URI_PREFIX}/{RollPair.RUN_JOB}'),
serdes_type=SerdesTypes.PROTOBUF)
return result
th = Thread(target=send_command,
name=f'roll_pair-send_command-{job_id}')
th.start()
populated_store = self.ctx.populate_processor(self.__store)
shuffler = TransferPair(job_id)
broker = FifoBroker()
bb = BatchBroker(broker)
scatter_future = shuffler.scatter(broker, self.partitioner,
populated_store)
key_serdes = self.key_serdes
value_serdes = self.value_serdes
try:
if include_key:
for k, v in items:
bb.put(item=(key_serdes.serialize(k),
value_serdes.serialize(v)))
else:
k = 0
for v in items:
bb.put(item=(key_serdes.serialize(k),
value_serdes.serialize(v)))
k += 1
finally:
bb.signal_write_finish()
scatter_results = scatter_future.result()
L.debug(f"scatter_results: {scatter_results}")
th.join()
return RollPair(populated_store, self.ctx)
def generate_broker():
with create_adapter(task._inputs[0]) as db, db.iteritems() as rb:
limit = None if er_pair._key is None else key_serdes.deserialize(er_pair._key)
try:
yield from TransferPair.pair_to_bin_batch(rb, limit=limit)
finally:
TransferService.remove_broker(tag)
def _generate_batch_streams(self, pair_iter, batches_per_stream,
body_bytes):
batches = TransferPair.pair_to_bin_batch(pair_iter,
sendbuf_size=body_bytes)
try:
peek = next(batches)
except StopIteration as e:
self._finish_partition = True
def chunk_batch_stream():
nonlocal self
nonlocal peek
cur_batch = peek
try:
for i in range(batches_per_stream - 1):
next_batch = next(batches)
yield cur_batch
cur_batch = next_batch
peek = next(batches)
except StopIteration as e:
self._finish_partition = True
finally:
yield cur_batch
try:
while not self._finish_partition:
self._rs_header._stream_seq += 1
yield chunk_batch_stream()
except Exception as e:
L.exception(
f'error in generating stream, rs_key={self._rs_header.get_rs_key()}, rs_header={self._rs_header}'
)
def put_all(self, items, output=None, options: dict = None):
if options is None:
options = {}
include_key = options.get("include_key", True)
job_id = generate_job_id(self.__session_id, RollPair.PUT_ALL)
# TODO:1: consider multiprocessing scenario. parallel size should be sent to egg_pair to set write signal count
def send_command():
job = ErJob(id=job_id,
name=RollPair.PUT_ALL,
inputs=[self.__store],
outputs=[self.__store],
functors=[])
task_results = self._run_job(job)
return self.__get_output_from_result(task_results)
th = Thread(target=send_command,
name=f'roll_pair-send_command-{job_id}')
th.start()
populated_store = self.ctx.populate_processor(self.__store)
shuffler = TransferPair(job_id)
fifo_broker = FifoBroker()
bb = BatchBroker(fifo_broker)
scatter_future = shuffler.scatter(fifo_broker, self.partitioner,
populated_store)
key_serdes = self.key_serdes
value_serdes = self.value_serdes
try:
if include_key:
for k, v in items:
bb.put(item=(key_serdes.serialize(k),
value_serdes.serialize(v)))
else:
k = 0
for v in items:
bb.put(item=(key_serdes.serialize(k),
value_serdes.serialize(v)))
k += 1
finally:
bb.signal_write_finish()
scatter_results = scatter_future.result()
th.join()
return RollPair(populated_store, self.ctx)
def _run_unary(self, func, task, shuffle=False):
key_serdes = create_serdes(task._inputs[0]._store_locator._serdes)
value_serdes = create_serdes(task._inputs[0]._store_locator._serdes)
with create_adapter(task._inputs[0]) as input_db:
L.debug(f"create_store_adatper: {task._inputs[0]}")
with input_db.iteritems() as rb:
L.debug(f"create_store_adatper_iter: {task._inputs[0]}")
from eggroll.roll_pair.transfer_pair import TransferPair, BatchBroker
if shuffle:
total_partitions = task._inputs[
0]._store_locator._total_partitions
output_store = task._job._outputs[0]
shuffle_broker = FifoBroker()
write_bb = BatchBroker(shuffle_broker)
try:
shuffler = TransferPair(transfer_id=task._job._id)
store_future = shuffler.store_broker(
task._outputs[0], True, total_partitions)
scatter_future = shuffler.scatter(
shuffle_broker,
partitioner(hash_func=hash_code,
total_partitions=total_partitions),
output_store)
func(rb, key_serdes, value_serdes, write_bb)
finally:
write_bb.signal_write_finish()
scatter_results = scatter_future.result()
store_result = store_future.result()
L.debug(f"scatter_result:{scatter_results}")
L.debug(f"gather_result:{store_result}")
else:
# TODO: modification may be needed when store options finished
with create_adapter(task._outputs[0],
options=task._job._options
) as db, db.new_batch() as wb:
func(rb, key_serdes, value_serdes, wb)
L.debug(f"close_store_adatper:{task._inputs[0]}")
def write(self):
L.info("RemoteRollPairWriteBatch write calling")
if len(self.manual_merger) == 0:
L.info(f"self.manual_merger={self.manual_merger}")
return
self.has_write_op = True
batches = TransferPair.pair_to_bin_batch(
sorted(self.manual_merger.items(), key=lambda kv: kv[0]))
task_id = f"{self.adapter._replicate_job_id}-partition-{self.adapter._partition_id}"
L.info(f"task_id={task_id}")
tasks = [
ErTask(id=task_id,
name=RollPair.PUT_BATCH,
inputs=[self.adapter._er_partition],
outputs=[self.adapter._er_partition],
job=ErJob(id=self.adapter._replicate_job_id,
name=RollPair.PUT_BATCH))
]
def send_command(tasks, remote_cmd_endpoint):
cmd_client = CommandClient()
return cmd_client.sync_send(
inputs=tasks,
output_types=[ErTask],
endpoint=remote_cmd_endpoint,
command_uri=CommandURI(f'v1/egg-pair/runTask'))
L.info(f"start to send cmd")
t = Thread(target=send_command,
name=task_id,
args=[tasks, self.adapter.remote_cmd_endpoint])
t.start()
transfer_client = TransferClient()
f = transfer_client.send(
batches,
endpoint=self.adapter.remote_transfer_endpoint,
tag=task_id)
f.result()
t.join()
self.manual_merger.clear()
L.info("RemoteRollPairWriteBatch write called")
def _run_unary(self, func, task, shuffle=False, reduce_op=None):
input_store_head = task._job._inputs[0]
output_store_head = task._job._outputs[0]
input_key_serdes = create_serdes(
input_store_head._store_locator._serdes)
input_value_serdes = create_serdes(
input_store_head._store_locator._serdes)
output_key_serdes = create_serdes(
output_store_head._store_locator._serdes)
output_value_serdes = create_serdes(
output_store_head._store_locator._serdes)
if input_key_serdes != output_key_serdes or \
input_value_serdes != output_value_serdes:
raise ValueError(
f"input key-value serdes:{(input_key_serdes, input_value_serdes)}"
f"differ from output key-value serdes:{(output_key_serdes, output_value_serdes)}"
)
if shuffle:
from eggroll.roll_pair.transfer_pair import TransferPair
input_total_partitions = input_store_head._store_locator._total_partitions
output_total_partitions = output_store_head._store_locator._total_partitions
output_store = output_store_head
my_server_node_id = get_static_er_conf().get(
'server_node_id', None)
shuffler = TransferPair(transfer_id=task._job._id)
if not task._outputs or \
(my_server_node_id is not None
and my_server_node_id != task._outputs[0]._processor._server_node_id):
store_future = None
else:
store_future = shuffler.store_broker(
store_partition=task._outputs[0],
is_shuffle=True,
total_writers=input_total_partitions,
reduce_op=reduce_op)
if not task._inputs or \
(my_server_node_id is not None
and my_server_node_id != task._inputs[0]._processor._server_node_id):
scatter_future = None
else:
shuffle_broker = FifoBroker()
write_bb = BatchBroker(shuffle_broker)
try:
scatter_future = shuffler.scatter(
input_broker=shuffle_broker,
partition_function=partitioner(
hash_func=hash_code,
total_partitions=output_total_partitions),
output_store=output_store)
with create_adapter(task._inputs[0]) as input_db, \
input_db.iteritems() as rb:
func(rb, input_key_serdes, input_value_serdes,
write_bb)
finally:
write_bb.signal_write_finish()
if scatter_future:
scatter_results = scatter_future.result()
else:
scatter_results = 'no scatter for this partition'
if store_future:
store_results = store_future.result()
else:
store_results = 'no store for this partition'
else: # no shuffle
with create_adapter(task._inputs[0]) as input_db, \
input_db.iteritems() as rb, \
create_adapter(task._outputs[0], options=task._job._options) as db, \
db.new_batch() as wb:
func(rb, input_key_serdes, input_value_serdes, wb)
L.trace(f"close_store_adatper:{task._inputs[0]}")
def run_task(self, task: ErTask):
if L.isEnabledFor(logging.TRACE):
L.trace(
f'[RUNTASK] start. task_name={task._name}, inputs={task._inputs}, outputs={task._outputs}, task_id={task._id}'
)
else:
L.debug(
f'[RUNTASK] start. task_name={task._name}, task_id={task._id}')
functors = task._job._functors
result = task
if task._name == 'get':
# TODO:1: move to create_serdes
f = create_functor(functors[0]._body)
with create_adapter(task._inputs[0]) as input_adapter:
L.trace(
f"get: key: {self.functor_serdes.deserialize(f._key)}, path: {input_adapter.path}"
)
value = input_adapter.get(f._key)
result = ErPair(key=f._key, value=value)
elif task._name == 'getAll':
tag = f'{task._id}'
er_pair = create_functor(functors[0]._body)
input_store_head = task._job._inputs[0]
key_serdes = create_serdes(input_store_head._store_locator._serdes)
def generate_broker():
with create_adapter(
task._inputs[0]) as db, db.iteritems() as rb:
limit = None if er_pair._key is None else key_serdes.deserialize(
er_pair._key)
try:
yield from TransferPair.pair_to_bin_batch(rb,
limit=limit)
finally:
TransferService.remove_broker(tag)
TransferService.set_broker(tag, generate_broker())
elif task._name == 'count':
with create_adapter(task._inputs[0]) as input_adapter:
result = ErPair(key=self.functor_serdes.serialize('result'),
value=self.functor_serdes.serialize(
input_adapter.count()))
elif task._name == 'putBatch':
partition = task._outputs[0]
tag = f'{task._id}'
PutBatchTask(tag, partition).run()
elif task._name == 'putAll':
output_partition = task._outputs[0]
tag = f'{task._id}'
L.trace(f'egg_pair putAll: transfer service tag={tag}')
tf = TransferPair(tag)
store_broker_result = tf.store_broker(output_partition,
False).result()
# TODO:2: should wait complete?, command timeout?
elif task._name == 'put':
f = create_functor(functors[0]._body)
with create_adapter(task._inputs[0]) as input_adapter:
value = input_adapter.put(f._key, f._value)
#result = ErPair(key=f._key, value=bytes(value))
elif task._name == 'destroy':
input_store_locator = task._inputs[0]._store_locator
namespace = input_store_locator._namespace
name = input_store_locator._name
store_type = input_store_locator._store_type
L.debug(
f'destroying store_type={store_type}, namespace={namespace}, name={name}'
)
if name == '*':
from eggroll.roll_pair.utils.pair_utils import get_db_path, get_data_dir
target_paths = list()
if store_type == '*':
data_dir = get_data_dir()
store_types = os.listdir(data_dir)
for store_type in store_types:
target_paths.append('/'.join(
[data_dir, store_type, namespace]))
else:
db_path = get_db_path(task._inputs[0])
target_paths.append(db_path[:db_path.rfind('*')])
real_data_dir = os.path.realpath(get_data_dir())
for path in target_paths:
realpath = os.path.realpath(path)
if os.path.exists(path):
if realpath == "/" \
or realpath == real_data_dir \
or not realpath.startswith(real_data_dir):
raise ValueError(
f'trying to delete a dangerous path: {realpath}'
)
else:
shutil.rmtree(path)
else:
options = task._job._options
with create_adapter(task._inputs[0],
options=options) as input_adapter:
input_adapter.destroy(options=options)
elif task._name == 'delete':
f = create_functor(functors[0]._body)
with create_adapter(task._inputs[0]) as input_adapter:
if input_adapter.delete(f._key):
L.trace("delete k success")
elif task._name == 'mapValues':
f = create_functor(functors[0]._body)
def map_values_wrapper(input_iterator, key_serdes, value_serdes,
output_writebatch):
for k_bytes, v_bytes in input_iterator:
v = value_serdes.deserialize(v_bytes)
output_writebatch.put(k_bytes,
value_serdes.serialize(f(v)))
self._run_unary(map_values_wrapper, task)
elif task._name == 'map':
f = create_functor(functors[0]._body)
def map_wrapper(input_iterator, key_serdes, value_serdes,
shuffle_broker):
for k_bytes, v_bytes in input_iterator:
k1, v1 = f(key_serdes.deserialize(k_bytes),
value_serdes.deserialize(v_bytes))
shuffle_broker.put(
(key_serdes.serialize(k1), value_serdes.serialize(v1)))
self._run_unary(map_wrapper, task, shuffle=True)
elif task._name == 'reduce':
seq_op_result = self.aggregate_seq(task=task)
result = ErPair(key=self.functor_serdes.serialize(
task._inputs[0]._id),
value=self.functor_serdes.serialize(seq_op_result))
elif task._name == 'aggregate':
seq_op_result = self.aggregate_seq(task=task)
result = ErPair(key=self.functor_serdes.serialize(
task._inputs[0]._id),
value=self.functor_serdes.serialize(seq_op_result))
elif task._name == 'mapPartitions':
reduce_op = create_functor(functors[1]._body)
shuffle = create_functor(functors[2]._body)
def map_partitions_wrapper(input_iterator, key_serdes,
value_serdes, output_writebatch):
f = create_functor(functors[0]._body)
value = f(generator(key_serdes, value_serdes, input_iterator))
if isinstance(value, Iterable):
for k1, v1 in value:
if shuffle:
output_writebatch.put((key_serdes.serialize(k1),
value_serdes.serialize(v1)))
else:
output_writebatch.put(key_serdes.serialize(k1),
value_serdes.serialize(v1))
else:
key = input_iterator.key()
output_writebatch.put((key, value_serdes.serialize(value)))
self._run_unary(map_partitions_wrapper,
task,
shuffle=shuffle,
reduce_op=reduce_op)
elif task._name == 'collapsePartitions':
def collapse_partitions_wrapper(input_iterator, key_serdes,
value_serdes, output_writebatch):
f = create_functor(functors[0]._body)
value = f(generator(key_serdes, value_serdes, input_iterator))
if input_iterator.last():
key = input_iterator.key()
output_writebatch.put(key, value_serdes.serialize(value))
self._run_unary(collapse_partitions_wrapper, task)
elif task._name == 'flatMap':
shuffle = create_functor(functors[1]._body)
def flat_map_wraaper(input_iterator, key_serdes, value_serdes,
output_writebatch):
f = create_functor(functors[0]._body)
for k1, v1 in input_iterator:
for k2, v2 in f(key_serdes.deserialize(k1),
value_serdes.deserialize(v1)):
if shuffle:
output_writebatch.put((key_serdes.serialize(k2),
value_serdes.serialize(v2)))
else:
output_writebatch.put(key_serdes.serialize(k2),
value_serdes.serialize(v2))
self._run_unary(flat_map_wraaper, task, shuffle=shuffle)
elif task._name == 'glom':
def glom_wrapper(input_iterator, key_serdes, value_serdes,
output_writebatch):
k_tmp = None
v_list = []
for k, v in input_iterator:
v_list.append((key_serdes.deserialize(k),
value_serdes.deserialize(v)))
k_tmp = k
if k_tmp is not None:
output_writebatch.put(k_tmp,
value_serdes.serialize(v_list))
self._run_unary(glom_wrapper, task)
elif task._name == 'sample':
def sample_wrapper(input_iterator, key_serdes, value_serdes,
output_writebatch):
fraction = create_functor(functors[0]._body)
seed = create_functor(functors[1]._body)
input_iterator.first()
random_state = np.random.RandomState(seed)
for k, v in input_iterator:
if random_state.rand() < fraction:
output_writebatch.put(k, v)
self._run_unary(sample_wrapper, task)
elif task._name == 'filter':
def filter_wrapper(input_iterator, key_serdes, value_serdes,
output_writebatch):
f = create_functor(functors[0]._body)
for k, v in input_iterator:
if f(key_serdes.deserialize(k),
value_serdes.deserialize(v)):
output_writebatch.put(k, v)
self._run_unary(filter_wrapper, task)
elif task._name == 'join':
def merge_join_wrapper(left_iterator, left_key_serdes,
left_value_serdes, right_iterator,
right_key_serdes, right_value_serdes,
output_writebatch):
if not left_iterator.adapter.is_sorted(
) or not right_iterator.adapter.is_sorted():
raise RuntimeError(
f"merge join cannot be applied: not both store types support sorting. "
f"left type: {type(left_iterator.adapter)}, is_sorted: {left_iterator.adapter.is_sorted()}; "
f"right type: {type(right_iterator.adapter)}, is_sorted: {right_iterator.adapter.is_sorted()}"
)
f = create_functor(functors[0]._body)
is_same_serdes = left_key_serdes == right_key_serdes
l_iter = iter(left_iterator)
r_iter = iter(right_iterator)
try:
k_left, v_left_bytes = next(l_iter)
k_right_raw, v_right_bytes = next(r_iter)
if is_same_serdes:
k_right = k_right_raw
else:
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
while True:
while k_right < k_left:
k_right_raw, v_right_bytes = next(r_iter)
if is_same_serdes:
k_right = k_right_raw
else:
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
while k_left < k_right:
k_left, v_left_bytes = next(l_iter)
if k_left == k_right:
output_writebatch.put(
k_left,
left_value_serdes.serialize(
f(
left_value_serdes.deserialize(
v_left_bytes),
right_value_serdes.deserialize(
v_right_bytes))))
k_left, v_left_bytes = next(l_iter)
# skips next(r_iter) to avoid duplicate codes for the 3rd time
except StopIteration as e:
return
def hash_join_wrapper(left_iterator, left_key_serdes,
left_value_serdes, right_iterator,
right_key_serdes, right_value_serdes,
output_writebatch):
f = create_functor(functors[0]._body)
is_diff_serdes = type(left_key_serdes) != type(
right_key_serdes)
for k_left, l_v_bytes in left_iterator:
if is_diff_serdes:
k_left = right_key_serdes.serialize(
left_key_serdes.deserialize(k_left))
r_v_bytes = right_iterator.adapter.get(k_left)
if r_v_bytes:
output_writebatch.put(
k_left,
left_value_serdes.serialize(
f(left_value_serdes.deserialize(l_v_bytes),
right_value_serdes.deserialize(r_v_bytes))))
join_type = task._job._options.get('join_type', 'merge')
if join_type == 'merge':
self._run_binary(merge_join_wrapper, task)
else:
self._run_binary(hash_join_wrapper, task)
elif task._name == 'subtractByKey':
def merge_subtract_by_key_wrapper(left_iterator, left_key_serdes,
left_value_serdes,
right_iterator, right_key_serdes,
right_value_serdes,
output_writebatch):
if not left_iterator.adapter.is_sorted(
) or not right_iterator.adapter.is_sorted():
raise RuntimeError(
f"merge subtract_by_key cannot be applied: not both store types support sorting. "
f"left type: {type(left_iterator.adapter)}, is_sorted: {left_iterator.adapter.is_sorted()}; "
f"right type: {type(right_iterator.adapter)}, is_sorted: {right_iterator.adapter.is_sorted()}"
)
is_same_serdes = left_key_serdes == right_key_serdes
l_iter = iter(left_iterator)
r_iter = iter(right_iterator)
is_left_stopped = False
is_equal = False
try:
k_left, v_left = next(l_iter)
except StopIteration:
is_left_stopped = True
k_left = None
v_left = None
try:
k_right_raw, v_right = next(r_iter)
except StopIteration:
is_left_stopped = False
k_right_raw = None
v_right = None
# left is None, output must be None
if k_left is None:
return
try:
if k_left is None:
raise StopIteration()
if k_right_raw is None:
raise StopIteration()
if is_same_serdes:
k_right = k_right_raw
else:
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
while True:
is_left_stopped = False
if k_left < k_right:
output_writebatch.put(k_left, v_left)
k_left, v_left = next(l_iter)
is_left_stopped = True
elif k_left == k_right:
is_equal = True
is_left_stopped = True
k_left, v_left = next(l_iter)
is_left_stopped = False
is_equal = False
k_right_raw, v_right = next(r_iter)
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
else:
k_right_raw, v_right = next(r_iter)
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
is_left_stopped = True
except StopIteration as e:
pass
if not is_left_stopped and not is_equal:
try:
if k_left is not None and v_left is not None:
output_writebatch.put(k_left, v_left)
while True:
k_left, v_left = next(l_iter)
output_writebatch.put(k_left, v_left)
except StopIteration as e:
pass
elif is_left_stopped and not is_equal and k_left is not None:
output_writebatch.put(k_left, v_left)
return
def hash_subtract_by_key_wrapper(left_iterator, left_key_serdes,
left_value_serdes, right_iterator,
right_key_serdes,
right_value_serdes,
output_writebatch):
is_diff_serdes = type(left_key_serdes) != type(
right_key_serdes)
for k_left, v_left in left_iterator:
if is_diff_serdes:
k_left = right_key_serdes.serialize(
left_key_serdes.deserialize(k_left))
v_right = right_iterator.adapter.get(k_left)
if v_right is None:
output_writebatch.put(k_left, v_left)
subtract_by_key_type = task._job._options.get(
'subtract_by_key_type', 'merge')
if subtract_by_key_type == 'merge':
self._run_binary(merge_subtract_by_key_wrapper, task)
else:
self._run_binary(hash_subtract_by_key_wrapper, task)
elif task._name == 'union':
def merge_union_wrapper(left_iterator, left_key_serdes,
left_value_serdes, right_iterator,
right_key_serdes, right_value_serdes,
output_writebatch):
if not left_iterator.adapter.is_sorted(
) or not right_iterator.adapter.is_sorted():
raise RuntimeError(
f"merge union cannot be applied: not both store types support sorting. "
f"left type: {type(left_iterator.adapter)}, is_sorted: {left_iterator.adapter.is_sorted()}; "
f"right type: {type(right_iterator.adapter)}, is_sorted: {right_iterator.adapter.is_sorted()}"
)
f = create_functor(functors[0]._body)
is_same_serdes = left_key_serdes == right_key_serdes
l_iter = iter(left_iterator)
r_iter = iter(right_iterator)
k_left = None
v_left_bytes = None
k_right = None
v_right_bytes = None
none_none = (None, None)
is_left_stopped = False
is_equal = False
try:
k_left, v_left_bytes = next(l_iter, none_none)
k_right_raw, v_right_bytes = next(r_iter, none_none)
if k_left is None and k_right_raw is None:
return
elif k_left is None:
is_left_stopped = True
raise StopIteration()
elif k_right_raw is None:
is_left_stopped = False
raise StopIteration()
if is_same_serdes:
k_right = k_right_raw
else:
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
while True:
is_left_stopped = False
while k_right < k_left:
if is_same_serdes:
output_writebatch.put(k_right, v_right_bytes)
else:
output_writebatch.put(
k_right,
left_value_serdes.serialize(
right_value_serdes.deserialize(
v_right_bytes)))
k_right_raw, v_right_bytes = next(r_iter)
if is_same_serdes:
k_right = k_right_raw
else:
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
is_left_stopped = True
while k_left < k_right:
output_writebatch.put(k_left, v_left_bytes)
k_left, v_left_bytes = next(l_iter)
if k_left == k_right:
is_equal = True
output_writebatch.put(
k_left,
left_value_serdes.serialize(
f(
left_value_serdes.deserialize(
v_left_bytes),
right_value_serdes.deserialize(
v_right_bytes))))
is_left_stopped = True
k_left, v_left_bytes = next(l_iter)
is_left_stopped = False
k_right_raw, v_right_bytes = next(r_iter)
if is_same_serdes:
k_right = k_right_raw
else:
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
is_equal = False
except StopIteration as e:
pass
if not is_left_stopped:
try:
output_writebatch.put(k_left, v_left_bytes)
while True:
k_left, v_left_bytes = next(l_iter)
output_writebatch.put(k_left, v_left_bytes)
except StopIteration as e:
pass
else:
try:
if not is_equal:
if is_same_serdes:
output_writebatch.put(k_right_raw,
v_right_bytes)
else:
output_writebatch.put(
left_key_serdes.serialize(
right_key_serdes.deserialize(
k_right_raw)),
left_value_serdes.serialize(
right_value_serdes.deserialize(
v_right_bytes)))
while True:
k_right_raw, v_right_bytes = next(r_iter)
if is_same_serdes:
output_writebatch.put(k_right_raw,
v_right_bytes)
else:
output_writebatch.put(
left_key_serdes.serialize(
right_key_serdes.deserialize(
k_right_raw)),
left_value_serdes.serialize(
right_value_serdes.deserialize(
v_right_bytes)))
except StopIteration as e:
pass
# end of merge union wrapper
return
def hash_union_wrapper(left_iterator, left_key_serdes,
left_value_serdes, right_iterator,
right_key_serdes, right_value_serdes,
output_writebatch):
f = create_functor(functors[0]._body)
is_diff_serdes = type(left_key_serdes) != type(
right_key_serdes)
for k_left, v_left in left_iterator:
if is_diff_serdes:
k_left = right_key_serdes.serialize(
left_key_serdes.deserialize(k_left))
v_right = right_iterator.adapter.get(k_left)
if v_right is None:
output_writebatch.put(k_left, v_left)
else:
v_final = f(left_value_serdes.deserialize(v_left),
right_value_serdes.deserialize(v_right))
output_writebatch.put(
k_left, left_value_serdes.serialize(v_final))
right_iterator.first()
for k_right, v_right in right_iterator:
if is_diff_serdes:
final_v_bytes = output_writebatch.get(
left_key_serdes.serialize(
right_key_serdes.deserialize(k_right)))
else:
final_v_bytes = output_writebatch.get(k_right)
if final_v_bytes is None:
output_writebatch.put(k_right, v_right)
union_type = task._job._options.get('union_type', 'merge')
if union_type == 'merge':
self._run_binary(merge_union_wrapper, task)
else:
self._run_binary(hash_union_wrapper, task)
elif task._name == 'withStores':
f = create_functor(functors[0]._body)
result = ErPair(key=self.functor_serdes.serialize(
task._inputs[0]._id),
value=self.functor_serdes.serialize(f(task)))
if L.isEnabledFor(logging.TRACE):
L.trace(
f'[RUNTASK] end. task_name={task._name}, inputs={task._inputs}, outputs={task._outputs}, task_id={task._id}'
)
else:
L.debug(
f'[RUNTASK] end. task_name={task._name}, task_id={task._id}')
return result
def generate_broker():
with create_adapter(
task._inputs[0]) as db, db.iteritems() as rb:
yield from TransferPair.pair_to_bin_batch(rb)
def run_task(self, task: ErTask):
L.info("start run task")
L.debug("start run task")
functors = task._job._functors
result = task
if task._name == 'get':
L.info("egg_pair get call")
# TODO:1: move to create_serdes
f = create_functor(functors[0]._body)
with create_adapter(task._inputs[0]) as input_adapter:
print("get key:{} and path is:{}".format(
self.functor_serdes.deserialize(f._key),
input_adapter.path))
value = input_adapter.get(f._key)
result = ErPair(key=f._key, value=value)
elif task._name == 'getAll':
L.info("egg_pair getAll call")
tag = f'{task._id}'
def generate_broker():
with create_adapter(
task._inputs[0]) as db, db.iteritems() as rb:
yield from TransferPair.pair_to_bin_batch(rb)
# TODO:0 how to remove?
# TransferService.remove_broker(tag)
TransferService.set_broker(tag, generate_broker())
elif task._name == 'count':
L.info('egg_pair count call')
with create_adapter(task._inputs[0]) as input_adapter:
result = ErPair(key=self.functor_serdes.serialize('result'),
value=self.functor_serdes.serialize(
input_adapter.count()))
# TODO:1: multiprocessor scenario
elif task._name == 'putAll':
L.info("egg_pair putAll call")
output_partition = task._outputs[0]
tag = f'{task._id}'
L.info(f'egg_pair transfer service tag:{tag}')
tf = TransferPair(tag)
store_broker_result = tf.store_broker(output_partition,
False).result()
# TODO:2: should wait complete?, command timeout?
L.debug(f"putAll result:{store_broker_result}")
if task._name == 'put':
L.info("egg_pair put call")
f = create_functor(functors[0]._body)
with create_adapter(task._inputs[0]) as input_adapter:
value = input_adapter.put(f._key, f._value)
#result = ErPair(key=f._key, value=bytes(value))
if task._name == 'destroy':
with create_adapter(task._inputs[0]) as input_adapter:
input_adapter.destroy()
L.info("finish destroy")
if task._name == 'delete':
f = create_functor(functors[0]._body)
with create_adapter(task._inputs[0]) as input_adapter:
L.info("delete k:{}, its value:{}".format(
f._key, input_adapter.get(f._key)))
if input_adapter.delete(f._key):
L.info("delete k success")
if task._name == 'mapValues':
f = create_functor(functors[0]._body)
def map_values_wrapper(input_iterator, key_serdes, value_serdes,
output_writebatch):
for k_bytes, v_bytes in input_iterator:
v = value_serdes.deserialize(v_bytes)
output_writebatch.put(k_bytes,
value_serdes.serialize(f(v)))
self._run_unary(map_values_wrapper, task)
elif task._name == 'map':
f = create_functor(functors[0]._body)
def map_wrapper(input_iterator, key_serdes, value_serdes,
shuffle_broker):
for k_bytes, v_bytes in input_iterator:
k1, v1 = f(key_serdes.deserialize(k_bytes),
value_serdes.deserialize(v_bytes))
shuffle_broker.put(
(key_serdes.serialize(k1), value_serdes.serialize(v1)))
L.info('finish calculating')
self._run_unary(map_wrapper, task, shuffle=True)
L.info('map finished')
elif task._name == 'reduce':
seq_op_result = self.aggregate_seq(task=task)
L.info('reduce finished')
result = ErPair(key=self.functor_serdes.serialize(
task._inputs[0]._id),
value=self.functor_serdes.serialize(seq_op_result))
elif task._name == 'aggregate':
L.info('ready to aggregate')
seq_op_result = self.aggregate_seq(task=task)
L.info('aggregate finished')
result = ErPair(key=self.functor_serdes.serialize(
task._inputs[0]._id),
value=self.functor_serdes.serialize(seq_op_result))
elif task._name == 'mapPartitions':
def map_partitions_wrapper(input_iterator, key_serdes,
value_serdes, shuffle_broker):
f = create_functor(functors[0]._body)
value = f(generator(key_serdes, value_serdes, input_iterator))
if input_iterator.last():
L.info("value of mapPartitions:{}".format(value))
if isinstance(value, Iterable):
for k1, v1 in value:
shuffle_broker.put((key_serdes.serialize(k1),
value_serdes.serialize(v1)))
else:
key = input_iterator.key()
shuffle_broker.put(
(key, value_serdes.serialize(value)))
self._run_unary(map_partitions_wrapper, task, shuffle=True)
elif task._name == 'collapsePartitions':
def collapse_partitions_wrapper(input_iterator, key_serdes,
value_serdes, output_writebatch):
f = create_functor(functors[0]._body)
value = f(generator(key_serdes, value_serdes, input_iterator))
if input_iterator.last():
key = input_iterator.key()
output_writebatch.put(key, value_serdes.serialize(value))
self._run_unary(collapse_partitions_wrapper, task)
elif task._name == 'flatMap':
def flat_map_wraaper(input_iterator, key_serdes, value_serdes,
output_writebatch):
f = create_functor(functors[0]._body)
for k1, v1 in input_iterator:
for k2, v2 in f(key_serdes.deserialize(k1),
value_serdes.deserialize(v1)):
output_writebatch.put(key_serdes.serialize(k2),
value_serdes.serialize(v2))
self._run_unary(flat_map_wraaper, task)
elif task._name == 'glom':
def glom_wrapper(input_iterator, key_serdes, value_serdes,
output_writebatch):
k_tmp = None
v_list = []
for k, v in input_iterator:
v_list.append((key_serdes.deserialize(k),
value_serdes.deserialize(v)))
k_tmp = k
if k_tmp is not None:
output_writebatch.put(k_tmp,
value_serdes.serialize(v_list))
self._run_unary(glom_wrapper, task)
elif task._name == 'sample':
def sample_wrapper(input_iterator, key_serdes, value_serdes,
output_writebatch):
fraction = create_functor(functors[0]._body)
seed = create_functor(functors[1]._body)
input_iterator.first()
random_state = np.random.RandomState(seed)
for k, v in input_iterator:
if random_state.rand() < fraction:
output_writebatch.put(k, v)
self._run_unary(sample_wrapper, task)
elif task._name == 'filter':
def filter_wrapper(input_iterator, key_serdes, value_serdes,
output_writebatch):
f = create_functor(functors[0]._body)
for k, v in input_iterator:
if f(key_serdes.deserialize(k),
value_serdes.deserialize(v)):
output_writebatch.put(k, v)
self._run_unary(filter_wrapper, task)
elif task._name == 'join':
def merge_join_wrapper(left_iterator, left_key_serdes,
left_value_serdes, right_iterator,
right_key_serdes, right_value_serdes,
output_writebatch):
if not left_iterator.adapter.is_sorted(
) or not right_iterator.adapter.is_sorted():
raise RuntimeError(
f"merge join cannot be applied: not both store types support sorting. "
f"left type: {type(left_iterator.adapter)}, is_sorted: {left_iterator.adapter.is_sorted()}; "
f"right type: {type(right_iterator.adapter)}, is_sorted: {right_iterator.adapter.is_sorted()}"
)
f = create_functor(functors[0]._body)
is_same_serdes = type(left_key_serdes) == type(
right_key_serdes)
l_iter = iter(left_iterator)
r_iter = iter(right_iterator)
try:
k_left, v_left_bytes = next(l_iter)
k_right_raw, v_right_bytes = next(r_iter)
if is_same_serdes:
k_right = k_right_raw
else:
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
while True:
while k_right < k_left:
k_right_raw, v_right_bytes = next(r_iter)
if is_same_serdes:
k_right = k_right_raw
else:
k_right = left_key_serdes.serialize(
right_key_serdes.deserialize(k_right_raw))
while k_left < k_right:
k_left, v_left_bytes = next(l_iter)
if k_left == k_right:
output_writebatch.put(
k_left,
left_value_serdes.serialize(
f(
left_value_serdes.deserialize(
v_left_bytes),
right_value_serdes.deserialize(
v_right_bytes))))
k_left, v_left_bytes = next(l_iter)
# skips next(r_iter) to avoid duplicate codes for the 3rd time
except StopIteration as e:
return
def hash_join_wrapper(left_iterator, left_key_serdes,
left_value_serdes, right_iterator,
right_key_serdes, right_value_serdes,
output_writebatch):
f = create_functor(functors[0]._body)
is_diff_serdes = type(left_key_serdes) != type(
right_key_serdes)
for k_left, l_v_bytes in left_iterator:
if is_diff_serdes:
k_left = right_key_serdes.serialize(
left_key_serdes.deserialize(k_left))
r_v_bytes = right_iterator.adapter.get(k_left)
if r_v_bytes:
#L.info("egg join:{}".format(right_value_serdes.deserialize(r_v_bytes)))
output_writebatch.put(
k_left,
left_value_serdes.serialize(
f(left_value_serdes.deserialize(l_v_bytes),
right_value_serdes.deserialize(r_v_bytes))))
join_type = task._job._options.get('join_type', 'merge')
if join_type == 'merge':
self._run_binary(merge_join_wrapper, task)
else:
self._run_binary(hash_join_wrapper, task)
elif task._name == 'subtractByKey':
def subtract_by_key_wrapper(left_iterator, left_key_serdes,
left_value_serdess, right_iterator,
right_key_serdes, right_value_serdess,
output_writebatch):
L.info("sub wrapper")
is_diff_serdes = type(left_key_serdes) != type(
right_key_serdes)
for k_left, v_left in left_iterator:
if is_diff_serdes:
k_left = right_key_serdes.serialize(
left_key_serdes.deserialize(k_left))
v_right = right_iterator.adapter.get(k_left)
if v_right is None:
output_writebatch.put(k_left, v_left)
self._run_binary(subtract_by_key_wrapper, task)
elif task._name == 'union':
def union_wrapper(left_iterator, left_key_serdes,
left_value_serdess, right_iterator,
right_key_serdes, right_value_serdess,
output_writebatch):
f = create_functor(functors[0]._body)
is_diff_serdes = type(left_key_serdes) != type(
right_key_serdes)
for k_left, v_left in left_iterator:
if is_diff_serdes:
k_left = right_key_serdes.serialize(
left_key_serdes.deserialize(k_left))
v_right = right_iterator.adapter.get(k_left)
if v_right is None:
output_writebatch.put(k_left, v_left)
else:
v_final = f(left_value_serdess.deserialize(v_left),
right_value_serdess.deserialize(v_right))
output_writebatch.put(
k_left, left_value_serdess.serialize(v_final))
right_iterator.first()
for k_right, v_right in right_iterator:
if is_diff_serdes:
final_v_bytes = output_writebatch.get(
left_key_serdes.serialize(
right_key_serdes.deserialize(k_right)))
else:
final_v_bytes = output_writebatch.get(k_right)
if final_v_bytes is None:
output_writebatch.put(k_right, v_right)
self._run_binary(union_wrapper, task)
elif task._name == 'withStores':
f = create_functor(functors[0]._body)
result = ErPair(
key=self.functor_serdes.serialize(task._inputs[0]._id),
value=self.functor_serdes.serialize(f(task._inputs)))
return result