def object_table(self, object_id=None):
"""Fetch and parse the object table info for one or more object IDs.
Args:
object_id: An object ID to fetch information about. If this is
None, then the entire object table is fetched.
Returns:
Information from the object table.
"""
self._check_connected()
if object_id is not None:
# Return information about a single object ID.
return self._object_table(object_id)
else:
# Return the entire object table.
object_info_keys = self._keys(OBJECT_INFO_PREFIX + "*")
object_location_keys = self._keys(OBJECT_LOCATION_PREFIX + "*")
object_ids_binary = set(
[key[len(OBJECT_INFO_PREFIX):] for key in object_info_keys] +
[key[len(OBJECT_LOCATION_PREFIX):]
for key in object_location_keys])
results = {}
for object_id_binary in object_ids_binary:
results[binary_to_object_id(object_id_binary)] = (
self._object_table(binary_to_object_id(object_id_binary)))
return results
def object_table(self, object_id=None):
"""Fetch and parse the object table info for one or more object IDs.
Args:
object_id: An object ID to fetch information about. If this is
None, then the entire object table is fetched.
Returns:
Information from the object table.
"""
self._check_connected()
if object_id is not None:
# Return information about a single object ID.
return self._object_table(object_id)
else:
# Return the entire object table.
object_keys = self._keys(gcs_utils.TablePrefix_OBJECT_string + "*")
object_ids_binary = {
key[len(gcs_utils.TablePrefix_OBJECT_string):]
for key in object_keys
}
results = {}
for object_id_binary in object_ids_binary:
results[binary_to_object_id(object_id_binary)] = (
self._object_table(binary_to_object_id(object_id_binary)))
return results
def object_table(self, object_id=None):
"""Fetch and parse the object table info for one or more object IDs.
Args:
object_id: An object ID to fetch information about. If this is
None, then the entire object table is fetched.
Returns:
Information from the object table.
"""
self._check_connected()
if object_id is not None:
# Return information about a single object ID.
return self._object_table(object_id)
else:
# Return the entire object table.
object_info_keys = self._keys(OBJECT_INFO_PREFIX + "*")
object_location_keys = self._keys(OBJECT_LOCATION_PREFIX + "*")
object_ids_binary = set(
[key[len(OBJECT_INFO_PREFIX):] for key in object_info_keys] + [
key[len(OBJECT_LOCATION_PREFIX):]
for key in object_location_keys
])
results = {}
for object_id_binary in object_ids_binary:
results[binary_to_object_id(object_id_binary)] = (
self._object_table(binary_to_object_id(object_id_binary)))
return results
def object_table(self, object_id=None):
"""Fetch and parse the object table info for one or more object IDs.
Args:
object_id: An object ID to fetch information about. If this is
None, then the entire object table is fetched.
Returns:
Information from the object table.
"""
self._check_connected()
if object_id is not None:
# Return information about a single object ID.
return self._object_table(object_id)
else:
# Return the entire object table.
object_keys = self._keys(ray.gcs_utils.TablePrefix_OBJECT_string +
"*")
object_ids_binary = {
key[len(ray.gcs_utils.TablePrefix_OBJECT_string):]
for key in object_keys
}
results = {}
for object_id_binary in object_ids_binary:
results[binary_to_object_id(object_id_binary)] = (
self._object_table(binary_to_object_id(object_id_binary)))
return results
def _task_table(self, task_id):
"""Fetch and parse the task table information for a single task ID.
Args:
task_id_binary: A string of bytes with the task ID to get
information about.
Returns:
A dictionary with information about the task ID in question.
TASK_STATUS_MAPPING should be used to parse the "State" field
into a human-readable string.
"""
task_table_response = self._execute_command(task_id,
"RAY.TASK_TABLE_GET",
task_id.id())
if task_table_response is None:
raise Exception("There is no entry for task ID {} in the task "
"table.".format(binary_to_hex(task_id.id())))
task_table_message = TaskReply.GetRootAsTaskReply(task_table_response,
0)
task_spec = task_table_message.TaskSpec()
task_spec_message = TaskInfo.GetRootAsTaskInfo(task_spec, 0)
args = []
for i in range(task_spec_message.ArgsLength()):
arg = task_spec_message.Args(i)
if len(arg.ObjectId()) != 0:
args.append(binary_to_object_id(arg.ObjectId()))
else:
args.append(pickle.loads(arg.Data()))
# TODO(atumanov): Instead of hard coding these indices, we should use
# the flatbuffer constants.
assert task_spec_message.RequiredResourcesLength() == 3
required_resources = {
"CPUs": task_spec_message.RequiredResources(0),
"GPUs": task_spec_message.RequiredResources(1),
"CustomResource": task_spec_message.RequiredResources(2)}
task_spec_info = {
"DriverID": binary_to_hex(task_spec_message.DriverId()),
"TaskID": binary_to_hex(task_spec_message.TaskId()),
"ParentTaskID": binary_to_hex(task_spec_message.ParentTaskId()),
"ParentCounter": task_spec_message.ParentCounter(),
"ActorID": binary_to_hex(task_spec_message.ActorId()),
"ActorCounter": task_spec_message.ActorCounter(),
"FunctionID": binary_to_hex(task_spec_message.FunctionId()),
"Args": args,
"ReturnObjectIDs": [binary_to_object_id(
task_spec_message.Returns(i))
for i in range(
task_spec_message.ReturnsLength())],
"RequiredResources": required_resources}
return {"State": task_table_message.State(),
"LocalSchedulerID": binary_to_hex(
task_table_message.LocalSchedulerId()),
"TaskSpec": task_spec_info}
def to_shard_index(id_bin):
if len(id_bin) == ray.TaskID.size():
return binary_to_task_id(id_bin).redis_shard_hash() % len(
ray.state.state.redis_clients)
else:
return binary_to_object_id(id_bin).redis_shard_hash() % len(
ray.state.state.redis_clients)
def cleanup_task_table(self):
"""Clean up global state for failed local schedulers.
This marks any tasks that were scheduled on dead local schedulers as
TASK_STATUS_LOST. A local scheduler is deemed dead if it is in
self.dead_local_schedulers.
"""
tasks = self.state.task_table()
num_tasks_updated = 0
for task_id, task in tasks.items():
# See if the corresponding local scheduler is alive.
if task["LocalSchedulerID"] not in self.dead_local_schedulers:
continue
# Remove dummy objects returned by actor tasks from any plasma
# manager. Although the objects may still exist in that object
# store, this deletion makes them effectively unreachable by any
# local scheduler connected to a different store.
# TODO(swang): Actually remove the objects from the object store,
# so that the reconstructed actor can reuse the same object store.
if hex_to_binary(task["TaskSpec"]["ActorID"]) != NIL_ACTOR_ID:
dummy_object_id = task["TaskSpec"]["ReturnObjectIDs"][-1]
obj = self.state.object_table(dummy_object_id)
manager_ids = obj["ManagerIDs"]
if manager_ids is not None:
# The dummy object should exist on at most one plasma
# manager, the manager associated with the local scheduler
# that died.
assert len(manager_ids) <= 1
# Remove the dummy object from the plasma manager
# associated with the dead local scheduler, if any.
for manager in manager_ids:
ok = self.state._execute_command(
dummy_object_id, "RAY.OBJECT_TABLE_REMOVE",
dummy_object_id.id(), hex_to_binary(manager))
if ok != b"OK":
log.warn("Failed to remove object location for "
"dead plasma manager.")
# If the task is scheduled on a dead local scheduler, mark the
# task as lost.
key = binary_to_object_id(hex_to_binary(task_id))
ok = self.state._execute_command(
key, "RAY.TASK_TABLE_UPDATE",
hex_to_binary(task_id),
ray.experimental.state.TASK_STATUS_LOST, NIL_ID,
task["ExecutionDependenciesString"],
task["SpillbackCount"])
if ok != b"OK":
log.warn("Failed to update lost task for dead scheduler.")
num_tasks_updated += 1
if num_tasks_updated > 0:
log.warn("Marked {} tasks as lost.".format(num_tasks_updated))
def cleanup_task_table(self):
"""Clean up global state for failed local schedulers.
This marks any tasks that were scheduled on dead local schedulers as
TASK_STATUS_LOST. A local scheduler is deemed dead if it is in
self.dead_local_schedulers.
"""
tasks = self.state.task_table()
num_tasks_updated = 0
for task_id, task in tasks.items():
# See if the corresponding local scheduler is alive.
if task["LocalSchedulerID"] not in self.dead_local_schedulers:
continue
# Remove dummy objects returned by actor tasks from any plasma
# manager. Although the objects may still exist in that object
# store, this deletion makes them effectively unreachable by any
# local scheduler connected to a different store.
# TODO(swang): Actually remove the objects from the object store,
# so that the reconstructed actor can reuse the same object store.
if hex_to_binary(task["TaskSpec"]["ActorID"]) != NIL_ACTOR_ID:
dummy_object_id = task["TaskSpec"]["ReturnObjectIDs"][-1]
obj = self.state.object_table(dummy_object_id)
manager_ids = obj["ManagerIDs"]
if manager_ids is not None:
# The dummy object should exist on at most one plasma
# manager, the manager associated with the local scheduler
# that died.
assert len(manager_ids) <= 1
# Remove the dummy object from the plasma manager
# associated with the dead local scheduler, if any.
for manager in manager_ids:
ok = self.state._execute_command(
dummy_object_id, "RAY.OBJECT_TABLE_REMOVE",
dummy_object_id.id(), hex_to_binary(manager))
if ok != b"OK":
log.warn("Failed to remove object location for "
"dead plasma manager.")
# If the task is scheduled on a dead local scheduler, mark the
# task as lost.
key = binary_to_object_id(hex_to_binary(task_id))
ok = self.state._execute_command(
key, "RAY.TASK_TABLE_UPDATE",
hex_to_binary(task_id),
ray.experimental.state.TASK_STATUS_LOST, NIL_ID,
task["ExecutionDependenciesString"],
task["SpillbackCount"])
if ok != b"OK":
log.warn("Failed to update lost task for dead scheduler.")
num_tasks_updated += 1
if num_tasks_updated > 0:
log.warn("Marked {} tasks as lost.".format(num_tasks_updated))
def profile_table(self):
profile_table_keys = self._keys(
ray.gcs_utils.TablePrefix_PROFILE_string + "*")
component_identifiers_binary = [
key[len(ray.gcs_utils.TablePrefix_PROFILE_string):]
for key in profile_table_keys
]
return {
binary_to_hex(component_id):
self._profile_table(binary_to_object_id(component_id))
for component_id in component_identifiers_binary
}
def profile_table(self):
profile_table_keys = self._keys(
ray.gcs_utils.TablePrefix_PROFILE_string + "*")
batch_identifiers_binary = [
key[len(ray.gcs_utils.TablePrefix_PROFILE_string):]
for key in profile_table_keys
]
result = defaultdict(list)
for batch_id in batch_identifiers_binary:
profile_data = self._profile_table(binary_to_object_id(batch_id))
# Note that if keys are being evicted from Redis, then it is
# possible that the batch will be evicted before we get it.
if len(profile_data) > 0:
component_id = profile_data[0]["component_id"]
result[component_id].extend(profile_data)
return dict(result)
def profile_table(self):
profile_table_keys = self._keys(
ray.gcs_utils.TablePrefix_PROFILE_string + "*")
batch_identifiers_binary = [
key[len(ray.gcs_utils.TablePrefix_PROFILE_string):]
for key in profile_table_keys
]
result = defaultdict(list)
for batch_id in batch_identifiers_binary:
profile_data = self._profile_table(binary_to_object_id(batch_id))
# Note that if keys are being evicted from Redis, then it is
# possible that the batch will be evicted before we get it.
if len(profile_data) > 0:
component_id = profile_data[0]["component_id"]
result[component_id].extend(profile_data)
return dict(result)
def cleanup_task_table(self):
"""Clean up global state for failed local schedulers.
This marks any tasks that were scheduled on dead local schedulers as
TASK_STATUS_LOST. A local scheduler is deemed dead if it is in
self.dead_local_schedulers.
"""
tasks = self.state.task_table()
num_tasks_updated = 0
for task_id, task in tasks.items():
# See if the corresponding local scheduler is alive.
if task["LocalSchedulerID"] in self.dead_local_schedulers:
# If the task is scheduled on a dead local scheduler, mark the task as
# lost.
key = binary_to_object_id(hex_to_binary(task_id))
ok = self.state._execute_command(
key, "RAY.TASK_TABLE_UPDATE", hex_to_binary(task_id),
ray.experimental.state.TASK_STATUS_LOST, NIL_ID)
if ok != b"OK":
log.warn("Failed to update lost task for dead scheduler.")
num_tasks_updated += 1
if num_tasks_updated > 0:
log.warn("Marked {} tasks as lost.".format(num_tasks_updated))
def _task_table(self, task_id_binary):
"""Fetch and parse the task table information for a single object task ID.
Args:
task_id_binary: A string of bytes with the task ID to get information
about.
Returns:
A dictionary with information about the task ID in question.
"""
task_table_response = self.redis_client.execute_command(
"RAY.TASK_TABLE_GET", task_id_binary)
if task_table_response is None:
raise Exception(
"There is no entry for task ID {} in the task table.".format(
binary_to_hex(task_id_binary)))
task_table_message = TaskReply.GetRootAsTaskReply(
task_table_response, 0)
task_spec = task_table_message.TaskSpec()
task_spec_message = TaskInfo.GetRootAsTaskInfo(task_spec, 0)
args = []
for i in range(task_spec_message.ArgsLength()):
arg = task_spec_message.Args(i)
if len(arg.ObjectId()) != 0:
args.append(binary_to_object_id(arg.ObjectId()))
else:
args.append(pickle.loads(arg.Data()))
assert task_spec_message.RequiredResourcesLength() == 2
required_resources = {
"CPUs": task_spec_message.RequiredResources(0),
"GPUs": task_spec_message.RequiredResources(1)
}
task_spec_info = {
"DriverID":
binary_to_hex(task_spec_message.DriverId()),
"TaskID":
binary_to_hex(task_spec_message.TaskId()),
"ParentTaskID":
binary_to_hex(task_spec_message.ParentTaskId()),
"ParentCounter":
task_spec_message.ParentCounter(),
"ActorID":
binary_to_hex(task_spec_message.ActorId()),
"ActorCounter":
task_spec_message.ActorCounter(),
"FunctionID":
binary_to_hex(task_spec_message.FunctionId()),
"Args":
args,
"ReturnObjectIDs": [
binary_to_object_id(task_spec_message.Returns(i))
for i in range(task_spec_message.ReturnsLength())
],
"RequiredResources":
required_resources
}
return {
"State":
task_state_mapping[task_table_message.State()],
"LocalSchedulerID":
binary_to_hex(task_table_message.LocalSchedulerId()),
"TaskSpec":
task_spec_info
}
def ToShardIndex(index):
return binary_to_object_id(index).redis_shard_hash() % len(
self.state.redis_clients)
def to_shard_index(id_bin):
return binary_to_object_id(id_bin).redis_shard_hash() % len(
self.state.redis_clients)
def ToShardIndex(index):
return binary_to_object_id(index).redis_shard_hash() % len(
self.state.redis_clients)
def to_shard_index(id_bin):
return binary_to_object_id(id_bin).redis_shard_hash() % len(
self.state.redis_clients)
