Files
ray/python/ray/tests/test_multi_node_2.py
T
2019-09-11 12:26:04 -07:00

219 lines
6.2 KiB
Python

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from flaky import flaky
import logging
import pytest
import time
import ray
import ray.ray_constants as ray_constants
from ray.monitor import Monitor
from ray.tests.cluster_utils import Cluster
from ray.tests.conftest import generate_internal_config_map
logger = logging.getLogger(__name__)
def test_cluster():
"""Basic test for adding and removing nodes in cluster."""
g = Cluster(initialize_head=False)
node = g.add_node()
node2 = g.add_node()
assert node.remaining_processes_alive()
assert node2.remaining_processes_alive()
g.remove_node(node2)
g.remove_node(node)
assert not any(n.any_processes_alive() for n in [node, node2])
def test_shutdown():
g = Cluster(initialize_head=False)
node = g.add_node()
node2 = g.add_node()
g.shutdown()
assert not any(n.any_processes_alive() for n in [node, node2])
@pytest.mark.parametrize(
"ray_start_cluster_head",
[generate_internal_config_map(num_heartbeats_timeout=20)],
indirect=True)
def test_internal_config(ray_start_cluster_head):
"""Checks that the internal configuration setting works.
We set the cluster to timeout nodes after 2 seconds of no timeouts. We
then remove a node, wait for 1 second to check that the cluster is out
of sync, then wait another 2 seconds (giving 1 second of leeway) to check
that the client has timed out.
"""
cluster = ray_start_cluster_head
worker = cluster.add_node()
cluster.wait_for_nodes()
cluster.remove_node(worker)
time.sleep(1)
assert ray.cluster_resources()["CPU"] == 2
time.sleep(2)
assert ray.cluster_resources()["CPU"] == 1
def setup_monitor(address):
monitor = Monitor(address, None)
monitor.subscribe(ray.gcs_utils.XRAY_HEARTBEAT_BATCH_CHANNEL)
monitor.subscribe(ray.gcs_utils.XRAY_JOB_CHANNEL) # TODO: Remove?
monitor.update_raylet_map(_append_port=True)
monitor._maybe_flush_gcs()
return monitor
def verify_load_metrics(monitor, expected_resource_usage=None, timeout=10):
while True:
monitor.process_messages()
resource_usage = monitor.load_metrics.get_resource_usage()
if "memory" in resource_usage[1]:
del resource_usage[1]["memory"]
if "object_store_memory" in resource_usage[2]:
del resource_usage[1]["object_store_memory"]
if "memory" in resource_usage[2]:
del resource_usage[2]["memory"]
if "object_store_memory" in resource_usage[2]:
del resource_usage[2]["object_store_memory"]
if expected_resource_usage is None:
if all(x for x in resource_usage[1:]):
break
elif all(x == y
for x, y in zip(resource_usage, expected_resource_usage)):
break
else:
timeout -= 1
time.sleep(1)
if timeout <= 0:
raise ValueError("Timeout. {} != {}".format(
resource_usage, expected_resource_usage))
return resource_usage
@pytest.mark.parametrize(
"ray_start_cluster_head", [{
"num_cpus": 1,
}, {
"num_cpus": 2,
}],
indirect=True)
def test_heartbeats_single(ray_start_cluster_head):
"""Unit test for `Cluster.wait_for_nodes`.
Test proper metrics.
"""
cluster = ray_start_cluster_head
timeout = 5
monitor = setup_monitor(cluster.address)
total_cpus = ray.state.cluster_resources()["CPU"]
verify_load_metrics(monitor, (0.0, {"CPU": 0.0}, {"CPU": total_cpus}))
@ray.remote
def work(timeout):
time.sleep(timeout)
return True
work_handle = work.remote(timeout * 2)
verify_load_metrics(monitor, (1.0 / total_cpus, {
"CPU": 1.0
}, {
"CPU": total_cpus
}))
ray.get(work_handle)
@ray.remote
class Actor(object):
def work(self, timeout):
time.sleep(timeout)
return True
test_actor = Actor.remote()
work_handle = test_actor.work.remote(timeout * 2)
verify_load_metrics(monitor, (1.0 / total_cpus, {
"CPU": 1.0
}, {
"CPU": total_cpus
}))
ray.get(work_handle)
@flaky(max_runs=4)
def test_heartbeats_cluster(ray_start_cluster_head):
"""Unit test for `Cluster.wait_for_nodes`.
Test proper metrics.
"""
cluster = ray_start_cluster_head
timeout = 8
num_workers_nodes = 3
num_nodes_total = int(num_workers_nodes + 1)
[cluster.add_node() for i in range(num_workers_nodes)]
cluster.wait_for_nodes()
monitor = setup_monitor(cluster.address)
verify_load_metrics(monitor, (0.0, {"CPU": 0.0}, {"CPU": num_nodes_total}))
@ray.remote
class Actor(object):
def work(self, timeout):
time.sleep(timeout)
return True
test_actors = [Actor.remote() for i in range(num_nodes_total)]
work_handles = [actor.work.remote(timeout * 2) for actor in test_actors]
verify_load_metrics(monitor, (num_nodes_total, {
"CPU": num_nodes_total
}, {
"CPU": num_nodes_total
}))
ray.get(work_handles)
verify_load_metrics(monitor, (0.0, {"CPU": 0.0}, {"CPU": num_nodes_total}))
ray.shutdown()
def test_wait_for_nodes(ray_start_cluster_head):
"""Unit test for `Cluster.wait_for_nodes`.
Adds 4 workers, waits, then removes 4 workers, waits,
then adds 1 worker, waits, and removes 1 worker, waits.
"""
cluster = ray_start_cluster_head
workers = [cluster.add_node() for i in range(4)]
cluster.wait_for_nodes()
[cluster.remove_node(w) for w in workers]
cluster.wait_for_nodes()
assert ray.cluster_resources()["CPU"] == 1
worker2 = cluster.add_node()
cluster.wait_for_nodes()
cluster.remove_node(worker2)
cluster.wait_for_nodes()
assert ray.cluster_resources()["CPU"] == 1
def test_worker_plasma_store_failure(ray_start_cluster_head):
cluster = ray_start_cluster_head
worker = cluster.add_node()
cluster.wait_for_nodes()
# Log monitor doesn't die for some reason
worker.kill_log_monitor()
worker.kill_reporter()
worker.kill_plasma_store()
worker.all_processes[ray_constants.PROCESS_TYPE_RAYLET][0].process.wait()
assert not worker.any_processes_alive(), worker.live_processes()