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Remove local/global_scheduler from code and doc. (#4549)

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This commit is contained in:
Yuhong Guo
2019-04-03 17:05:09 -07:00
committed by Philipp Moritz
parent 51dae23d5c
commit c2349cf12d
29 changed files with 177 additions and 204 deletions
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python/ray/tests/test_actor.py
+9 -9
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@@ -873,7 +873,7 @@ def test_actor_load_balancing(ray_start_cluster):
num_attempts = 20
minimum_count = 5
# Make sure that actors are spread between the local schedulers.
# Make sure that actors are spread between the raylets.
attempts = 0
while attempts < num_attempts:
actors = [Actor1.remote() for _ in range(num_actors)]
@@ -1363,7 +1363,7 @@ def test_exception_raised_when_actor_node_dies(ray_start_cluster_head):
self.x += 1
return self.x
# Create an actor that is not on the local scheduler.
# Create an actor that is not on the raylet.
actor = Counter.remote()
while (ray.get(actor.local_plasma.remote()) !=
remote_node.plasma_store_socket_name):
@@ -1496,7 +1496,7 @@ def setup_counter_actor(test_checkpoint=False,
local_plasma = ray.worker.global_worker.plasma_client.store_socket_name
# Create an actor that is not on the local scheduler.
# Create an actor that is not on the raylet.
actor = Counter.remote(save_exception)
while ray.get(actor.local_plasma.remote()) == local_plasma:
actor = Counter.remote(save_exception)
@@ -1531,7 +1531,7 @@ def test_distributed_handle(ray_start_cluster_2_nodes):
count += num_incs * num_iters
# Kill the second plasma store to get rid of the cached objects and
# trigger the corresponding local scheduler to exit.
# trigger the corresponding raylet to exit.
cluster.list_all_nodes()[1].kill_plasma_store(wait=True)
# Check that the actor did not restore from a checkpoint.
@@ -1570,7 +1570,7 @@ def test_remote_checkpoint_distributed_handle(ray_start_cluster_2_nodes):
count += num_incs * num_iters
# Kill the second plasma store to get rid of the cached objects and
# trigger the corresponding local scheduler to exit.
# trigger the corresponding raylet to exit.
cluster.list_all_nodes()[1].kill_plasma_store(wait=True)
# Check that the actor restored from a checkpoint.
@@ -1610,7 +1610,7 @@ def test_checkpoint_distributed_handle(ray_start_cluster_2_nodes):
count += num_incs * num_iters
# Kill the second plasma store to get rid of the cached objects and
# trigger the corresponding local scheduler to exit.
# trigger the corresponding raylet to exit.
cluster.list_all_nodes()[1].kill_plasma_store(wait=True)
# Check that the actor restored from a checkpoint.
@@ -1638,7 +1638,7 @@ def _test_nondeterministic_reconstruction(
def read(self):
return self.queue
# Schedule the shared queue onto the remote local scheduler.
# Schedule the shared queue onto the remote raylet.
local_plasma = ray.worker.global_worker.plasma_client.store_socket_name
actor = Queue.remote()
while ray.get(actor.local_plasma.remote()) == local_plasma:
@@ -1673,7 +1673,7 @@ def _test_nondeterministic_reconstruction(
queue = ray.get(actor.read.remote())
# Kill the second plasma store to get rid of the cached objects and
# trigger the corresponding local scheduler to exit.
# trigger the corresponding raylet to exit.
cluster.list_all_nodes()[1].kill_plasma_store(wait=True)
# Read the queue again and check for deterministic reconstruction.
@@ -2267,7 +2267,7 @@ def test_multiple_actor_reconstruction(ray_start_cluster_head):
result_ids = collections.defaultdict(lambda: [])
# In a loop we are going to create some actors, run some methods, kill
# a local scheduler, and run some more methods.
# a raylet, and run some more methods.
for node in worker_nodes:
# Create some actors.
actors.extend(