def test_host_hash(self):
hash = host_hash()
salted = host_hash('salt')
empty_salted = host_hash('')
self.assertNotEqual(salted, hash)
self.assertEqual(empty_salted, hash)
def _task_fn(index, driver_addresses, settings):
task = task_service.SparkTaskService(index, settings.key)
try:
driver_client = driver_service.SparkDriverClient(driver_addresses, settings.key, settings.verbose)
driver_client.register_task(index, task.addresses(), host_hash.host_hash())
task.wait_for_initial_registration(settings.timeout)
# Tasks ping each other in a circular fashion to determine interfaces reachable within
# the cluster.
next_task_index = (index + 1) % settings.num_proc
next_task_addresses = driver_client.all_task_addresses(next_task_index)
# We request interface matching to weed out all the NAT'ed interfaces.
next_task_client = \
task_service.SparkTaskClient(next_task_index, next_task_addresses,
settings.key, settings.verbose,
match_intf=True)
driver_client.register_task_to_task_addresses(next_task_index, next_task_client.addresses())
task_indices_on_this_host = driver_client.task_host_hash_indices(
host_hash.host_hash())
if task_indices_on_this_host[0] == index:
# Task with first index will execute orted that will run mpirun_exec_fn for all tasks.
task.wait_for_command_start(settings.timeout)
task.wait_for_command_termination()
else:
# The rest of tasks need to wait for the first task to finish.
first_task_addresses = driver_client.all_task_addresses(task_indices_on_this_host[0])
first_task_client = \
task_service.SparkTaskClient(task_indices_on_this_host[0],
first_task_addresses, settings.key,
settings.verbose)
first_task_client.wait_for_command_termination()
return task.fn_result()
finally:
task.shutdown()
def _task_fn(index, driver_addresses, key, settings, use_gloo):
# deserialized on Spark workers, settings do not contain the key, so it is given here explicitly
# Spark RPC communicates the key and supports encryption
# for convenience, we put it back into settings
settings.key = key
task = task_service.SparkTaskService(index, settings.key, settings.nics,
settings.verbose)
try:
driver_client = driver_service.SparkDriverClient(
driver_addresses, settings.key, settings.verbose)
driver_client.register_task(index, task.addresses(),
host_hash.host_hash())
task.wait_for_initial_registration(settings.timeout)
task_indices_on_this_host = driver_client.task_host_hash_indices(
host_hash.host_hash())
# With Gloo all tasks wait for the command
# With MPI task with first index executes orted which will run mpirun_exec_fn for all tasks.
if use_gloo or task_indices_on_this_host[0] == index:
task.wait_for_command_start(settings.timeout)
task.wait_for_command_termination()
else:
# The rest of tasks need to wait for the first task to finish.
first_task_addresses = driver_client.all_task_addresses(
task_indices_on_this_host[0])
first_task_client = \
task_service.SparkTaskClient(task_indices_on_this_host[0],
first_task_addresses, settings.key,
settings.verbose)
first_task_client.wait_for_command_termination()
return task.fn_result()
finally:
task.shutdown()
def _task_fn(index, num_hosts, driver_addresses, settings):
task = task_service.HorovodRunTaskService(index, settings.key,
settings.nics)
try:
driver = driver_service.HorovodRunDriverClient(driver_addresses,
settings.key,
settings.verbose)
driver.register_task(index, task.addresses(), host_hash.host_hash())
task.wait_for_initial_registration(settings.start_timeout)
# Tasks ping each other in a circular fashion to determine interfaces
# reachable within the cluster.
next_task_index = (index + 1) % num_hosts
next_task_addresses = driver.all_task_addresses(next_task_index)
# We request interface matching to weed out all the NAT'ed interfaces.
next_task = task_service.HorovodRunTaskClient(next_task_index,
next_task_addresses,
settings.key,
settings.verbose,
match_intf=True,
attempts=10)
driver.register_task_to_task_addresses(next_task_index,
next_task.addresses())
# Notify the next task that the address checks are completed.
next_task.task_to_task_address_check_completed()
# Wait to get a notification from previous task that its address checks
# are completed as well.
task.wait_for_task_to_task_address_check_finish_signal(
settings.start_timeout)
finally:
task.shutdown()
def _task_fn(index, driver_addresses, key, settings, use_gloo):
# deserialized on Spark workers, settings do not contain the key, so it is given here explicitly
# Spark RPC communicates the key and supports encryption
# for convenience, we put it back into settings
settings.key = key
task = task_service.SparkTaskService(index, settings.key, settings.nics,
settings.verbose)
try:
driver_client = driver_service.SparkDriverClient(
driver_addresses, settings.key, settings.verbose)
driver_client.register_task(index, task.addresses(),
host_hash.host_hash())
task.wait_for_initial_registration(settings.timeout)
task_indices_on_this_host = driver_client.task_host_hash_indices(
host_hash.host_hash())
# With Gloo all tasks wait for the command
# With MPI task with first index executes orted which will run mpirun_exec_fn for all tasks.
minimum_lifetime_after_start = None
if use_gloo or task_indices_on_this_host[0] == index:
task.wait_for_command_start(settings.timeout)
minimum_lifetime_after_start = timeout.Timeout(
MINIMUM_COMMAND_LIFETIME_S, message='Just measuring runtime')
task.wait_for_command_termination()
else:
# The rest of tasks need to wait for the first task to finish.
first_task_addresses = driver_client.all_task_addresses(
task_indices_on_this_host[0])
first_task_client = \
task_service.SparkTaskClient(task_indices_on_this_host[0],
first_task_addresses, settings.key,
settings.verbose)
first_task_client.wait_for_command_termination()
# command terminated, make sure this task service does not shutdown too quickly after
# the client started the command as it needs some time to connect again
# to wait for the result after starting the command (see horovod.spark.driver.rsh).
if minimum_lifetime_after_start is not None:
time.sleep(minimum_lifetime_after_start.remaining())
return task.fn_result()
finally:
# this has to block on running requests (wait_for_command_exit_code)
# so they can finish serving the exit code
# shutdown does block with network.BasicService._server._block_on_close = True
task.shutdown()
def host_hash(salt=None):
"""
Computes this host's host hash by invoking horovod.run.common.util.host_hash.host_hash.
Consider environment variable CONTAINER_ID which is present when running Spark via YARN.
A YARN container does not share memory with other containers on the same host,
so it must be considered a `host` in the sense of the `host_hash`.
:param salt: extra information to include in the hash, ignores Falsy values
:return: host hash
"""
# turn salt into an array of a single string if given
salt = [str(salt)] if salt else []
# We would violate resource allocation if we run all tasks of a host in one container.
# See [issues 1497](https://github.com/horovod/horovod/issues/1497) for details.
container = os.environ.get("CONTAINER_ID")
if container is not None:
salt.append(container)
return hh.host_hash(salt='-'.join(salt))
def test_host_hash(self):
hash = host_hash()
# host_hash should consider CONTAINER_ID environment variable
with override_env({'CONTAINER_ID': 'a container id'}):
self.assertNotEqual(host_hash(), hash)
self.assertEqual(host_hash(), hash)
