def reduce(self, func, output=None, options: dict = None):
total_partitions = self.__store._store_locator._total_partitions
job_id = generate_job_id(self.__session_id, tag=RollPair.REDUCE)
serialized_func = ErFunctor(name=RollPair.REDUCE,
serdes=SerdesTypes.CLOUD_PICKLE,
body=cloudpickle.dumps(func))
job = ErJob(id=job_id,
name=RollPair.REDUCE,
inputs=[self.ctx.populate_processor(self.__store)],
functors=[serialized_func])
args = list()
for i in range(total_partitions):
partition_input = job._inputs[0]._partitions[i]
task = ErTask(id=generate_task_id(job_id, i),
name=job._name,
inputs=[partition_input],
job=job)
args.append(([task], partition_input._processor._command_endpoint))
futures = self.__command_client.async_call(
args=args,
output_types=[ErPair],
command_uri=CommandURI(
f'{RollPair.EGG_PAIR_URI_PREFIX}/{RollPair.RUN_TASK}'))
done = wait(futures, return_when=FIRST_EXCEPTION).done
result = None
first = True
for future in done:
pair = future.result()[0]
seq_op_result = self.functor_serdes.deserialize(pair._value)
if seq_op_result is not None:
if not first:
result = func(result, seq_op_result)
else:
result = seq_op_result
first = False
return result
def glom(self, output=None, options: dict = None):
if options is None:
options = {}
outputs = []
if output:
RollPair.__check_partition(self.get_partitions(), output._store_locator._total_partitions)
outputs.append(output)
functor = ErFunctor(name=RollPair.GLOM, serdes=SerdesTypes.CLOUD_PICKLE)
job = ErJob(id=generate_job_id(self.__session_id, RollPair.GLOM),
name=RollPair.GLOM,
inputs=[self.__store],
outputs=outputs,
functors=[functor])
task_results = self._run_job(job=job)
er_store = self.__get_output_from_result(task_results)
return RollPair(er_store, self.ctx)
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(self, k, options: dict = None):
if options is None:
options = {}
k = create_serdes(self.__store._store_locator._serdes).serialize(k)
er_pair = ErPair(key=k, value=None)
partition_id = self.partitioner(k)
egg = self.ctx.route_to_egg(self.__store._partitions[partition_id])
inputs = [
ErPartition(id=partition_id,
store_locator=self.__store._store_locator)
]
outputs = [
ErPartition(id=partition_id,
store_locator=self.__store._store_locator)
]
job_id = generate_job_id(self.__session_id, RollPair.GET)
job = ErJob(id=job_id,
name=RollPair.GET,
inputs=[self.__store],
outputs=[self.__store],
functors=[
ErFunctor(name=RollPair.GET,
body=cloudpickle.dumps(er_pair))
])
task = ErTask(id=generate_task_id(job_id, partition_id),
name=RollPair.GET,
inputs=inputs,
outputs=outputs,
job=job)
job_resp = self.__command_client.simple_sync_send(
input=task,
output_type=ErPair,
endpoint=egg._command_endpoint,
command_uri=self.RUN_TASK_URI,
serdes_type=self.__command_serdes)
return self.value_serdes.deserialize(
job_resp._value) if job_resp._value != b'' else None
def sample(self, fraction, seed=None, output=None, options: dict = None):
if options is None:
options = {}
outputs = []
if output:
RollPair.__check_partition(self.get_partitions(), output._store_locator._total_partitions)
outputs.append(output)
er_fraction = ErFunctor(name=RollPair.REDUCE, serdes=SerdesTypes.CLOUD_PICKLE, body=cloudpickle.dumps(fraction))
er_seed = ErFunctor(name=RollPair.REDUCE, serdes=SerdesTypes.CLOUD_PICKLE, body=cloudpickle.dumps(seed))
job = ErJob(id=generate_job_id(self.__session_id, RollPair.SAMPLE),
name=RollPair.SAMPLE,
inputs=[self.__store],
outputs=outputs,
functors=[er_fraction, er_seed])
task_results = self._run_job(job=job)
er_store = self.__get_output_from_result(task_results)
return RollPair(er_store, self.ctx)
def union(self, other, func=lambda v1, v2: v1, output=None, options: dict = None):
if options is None:
options = {}
inputs = self.__repartition_with(other)
outputs = []
if output:
RollPair.__check_partition(inputs[0]._store_locator._total_partitions,
output._store_locator._total_partitions)
outputs.append(output)
functor = ErFunctor(name=RollPair.UNION, serdes=SerdesTypes.CLOUD_PICKLE, body=cloudpickle.dumps(func))
job = ErJob(id=generate_job_id(self.__session_id, RollPair.UNION),
name=RollPair.UNION,
inputs=inputs,
outputs=outputs,
functors=[functor])
task_future = self._run_job(job=job)
er_store = self.__get_output_from_result(task_future)
return RollPair(er_store, self.ctx)
def subtract_by_key(self, other, output=None, options: dict = None):
if options is None:
options = {}
inputs = self.__repartition_with(other)
outputs = []
if output:
RollPair.__check_partition(inputs[0]._store_locator._total_partitions,
output._store_locator._total_partitions)
outputs.append(output)
functor = ErFunctor(name=RollPair.SUBTRACT_BY_KEY, serdes=SerdesTypes.CLOUD_PICKLE)
job = ErJob(id=generate_job_id(self.__session_id, RollPair.SUBTRACT_BY_KEY),
name=RollPair.SUBTRACT_BY_KEY,
inputs=inputs,
outputs=outputs,
functors=[functor])
task_future = self._run_job(job=job)
er_store = self.__get_output_from_result(task_future)
return RollPair(er_store, self.ctx)
def delete(self, k, options: dict = None):
if options is None:
options = {}
key = create_serdes(self.__store._store_locator._serdes).serialize(k)
er_pair = ErPair(key=key, value=None)
outputs = []
value = None
partition_id = self.partitioner(key)
egg = self.ctx.route_to_egg(self.__store._partitions[partition_id])
L.info(egg._command_endpoint)
L.info(f"count: {self.__store._store_locator._total_partitions}")
inputs = [
ErPartition(id=partition_id,
store_locator=self.__store._store_locator)
]
output = [
ErPartition(id=partition_id,
store_locator=self.__store._store_locator)
]
job_id = generate_job_id(self.__session_id, RollPair.DELETE)
job = ErJob(id=job_id,
name=RollPair.DELETE,
inputs=[self.__store],
outputs=outputs,
functors=[ErFunctor(body=cloudpickle.dumps(er_pair))])
task = ErTask(id=generate_task_id(job_id, partition_id),
name=RollPair.DELETE,
inputs=inputs,
outputs=output,
job=job)
L.info("start send req")
job_resp = self.__command_client.simple_sync_send(
input=task,
output_type=ErPair,
endpoint=egg._command_endpoint,
command_uri=CommandURI(
f'{RollPair.EGG_PAIR_URI_PREFIX}/{RollPair.RUN_TASK}'),
serdes_type=self.__command_serdes)
def destroy(self, options: dict = None):
if len(self.ctx.get_session()._cluster_manager_client.get_store(
self.get_store())._partitions) == 0:
L.exception(f"store:{self.get_store()} has been destroyed before")
raise ValueError(
f"store:{self.get_store()} has been destroyed before")
if options is None:
options = {}
job = ErJob(id=generate_job_id(self.__session_id, RollPair.DESTROY),
name=RollPair.DESTROY,
inputs=[self.__store],
outputs=[self.__store],
functors=[],
options=options)
task_results = self._run_job(job=job, create_output_if_missing=False)
self.ctx.get_session()._cluster_manager_client.delete_store(
self.__store)
L.debug(f'{RollPair.DESTROY}={self.__store}')
self.destroyed = True
def put(self, k, v, options: dict = None):
if options is None:
options = {}
k, v = create_serdes(self.__store._store_locator._serdes).serialize(k), \
create_serdes(self.__store._store_locator._serdes).serialize(v)
er_pair = ErPair(key=k, value=v)
outputs = []
partition_id = self.partitioner(k)
egg = self.ctx.route_to_egg(self.__store._partitions[partition_id])
inputs = [
ErPartition(id=partition_id,
store_locator=self.__store._store_locator)
]
output = [ErPartition(id=0, store_locator=self.__store._store_locator)]
job_id = generate_job_id(self.__session_id, RollPair.PUT)
job = ErJob(id=job_id,
name=RollPair.PUT,
inputs=[self.__store],
outputs=outputs,
functors=[
ErFunctor(name=RollPair.PUT,
body=cloudpickle.dumps(er_pair))
])
task = ErTask(id=generate_task_id(job_id, partition_id),
name=RollPair.PUT,
inputs=inputs,
outputs=output,
job=job)
job_resp = self.__command_client.simple_sync_send(
input=task,
output_type=ErPair,
endpoint=egg._command_endpoint,
command_uri=CommandURI(
f'{RollPair.EGG_PAIR_URI_PREFIX}/{RollPair.RUN_TASK}'),
serdes_type=self.__command_serdes)
value = job_resp._value
return value
def flat_map(self, func, output=None, options: dict = None):
if options is None:
options = {}
outputs = []
if output:
RollPair.__check_partition(self.get_partitions(), output._store_locator._total_partitions)
outputs.append(output)
shuffle = options.get('shuffle', True)
functor = ErFunctor(name=RollPair.FLAT_MAP, serdes=SerdesTypes.CLOUD_PICKLE, body=cloudpickle.dumps(func))
need_shuffle = ErFunctor(name=RollPair.FLAT_MAP, serdes=SerdesTypes.CLOUD_PICKLE, body=cloudpickle.dumps(shuffle))
job = ErJob(id=generate_job_id(self.__session_id, RollPair.FLAT_MAP),
name=RollPair.FLAT_MAP,
inputs=[self.__store],
outputs=outputs,
functors=[functor, need_shuffle])
task_results = self._run_job(job=job)
er_store = self.__get_output_from_result(task_results)
return RollPair(er_store, self.ctx)
def with_stores(self, func, others=None, options: dict = None):
if options is None:
options = {}
tag = "withStores"
if others is None:
others = []
total_partitions = self.get_partitions()
for other in others:
if other.get_partitions() != total_partitions:
raise ValueError(f"diff partitions: expected:{total_partitions}, actual:{other.get_partitions()}")
job_id = generate_job_id(self.__session_id, tag=tag)
job = ErJob(id=job_id,
name=tag,
inputs=[self.ctx.populate_processor(rp.get_store()) for rp in [self] + others],
functors=[ErFunctor(name=tag, serdes=SerdesTypes.CLOUD_PICKLE, body=cloudpickle.dumps(func))],
options=options)
args = list()
for i in range(total_partitions):
partition_self = job._inputs[0]._partitions[i]
task = ErTask(id=generate_task_id(job_id, i),
name=job._name,
inputs=[store._partitions[i] for store in job._inputs],
job=job)
args.append(([task], partition_self._processor._command_endpoint))
futures = self.__command_client.async_call(
args=args,
output_types=[ErPair],
command_uri=CommandURI(f'{RollPair.EGG_PAIR_URI_PREFIX}/{RollPair.RUN_TASK}'))
result = list()
for future in futures:
ret_pair = future.result()[0]
result.append((self.functor_serdes.deserialize(ret_pair._key),
self.functor_serdes.deserialize(ret_pair._value)))
return result
def map_values(self, func, output=None, options: dict = None):
if options is None:
options = {}
outputs = self._maybe_set_output(output)
functor = ErFunctor(name=RollPair.MAP_VALUES,
serdes=SerdesTypes.CLOUD_PICKLE,
body=cloudpickle.dumps(func))
# todo:1: options issues. refer to line 77
final_options = {}
final_options.update(self.__store._options)
final_options.update(options)
job = ErJob(id=generate_job_id(self.__session_id, RollPair.MAP_VALUES),
name=RollPair.MAP_VALUES,
inputs=[self.__store],
outputs=outputs,
functors=[functor],
options=final_options)
task_results = self._run_job(job=job)
er_store = self.__get_output_from_result(task_results)
return RollPair(er_store, self.ctx)
def cleanup(self, name, namespace, options: dict = None):
if not namespace:
raise ValueError('namespace cannot be blank')
L.debug(f'cleaning up namespace={namespace}, name={name}')
if options is None:
options = {}
total_partitions = options.get('total_partitions', 1)
partitioner = options.get('partitioner', PartitionerTypes.BYTESTRING_HASH)
store_serdes = options.get('serdes', self.default_store_serdes)
if name == '*':
store_type = options.get('store_type', '*')
L.debug(f'cleaning up whole store_type={store_type}, namespace={namespace}, name={name}')
er_store = ErStore(store_locator=ErStoreLocator(namespace=namespace,
name=name,
store_type=store_type))
job_id = generate_job_id(namespace, tag=RollPair.CLEANUP)
job = ErJob(id=job_id,
name=RollPair.DESTROY,
inputs=[er_store],
options=options)
args = list()
cleanup_partitions = [ErPartition(id=-1, store_locator=er_store._store_locator)]
for server_node, eggs in self.__session._eggs.items():
egg = eggs[0]
task = ErTask(id=generate_task_id(job_id, egg._command_endpoint._host),
name=job._name,
inputs=cleanup_partitions,
job=job)
args.append(([task], egg._command_endpoint))
futures = self.__command_client.async_call(
args=args,
output_types=[ErTask],
command_uri=CommandURI(f'{RollPair.EGG_PAIR_URI_PREFIX}/{RollPair.RUN_TASK}'))
for future in futures:
result = future.result()
self.get_session()._cluster_manager_client.delete_store(er_store)
else:
# todo:1: add combine options to pass it through
store_options = self.__session.get_all_options()
store_options.update(options)
final_options = store_options.copy()
store = ErStore(
store_locator=ErStoreLocator(
store_type=StoreTypes.ROLLPAIR_LMDB,
namespace=namespace,
name=name,
total_partitions=total_partitions,
partitioner=partitioner,
serdes=store_serdes),
options=final_options)
task_results = self.__session._cluster_manager_client.get_store_from_namespace(store)
L.trace('res={}'.format(task_results._stores))
if task_results._stores is not None:
L.trace("item count={}".format(len(task_results._stores)))
for item in task_results._stores:
L.trace("item namespace={} name={}".format(item._store_locator._namespace,
item._store_locator._name))
rp = RollPair(er_store=item, rp_ctx=self)
rp.destroy()