[Windows] Enable test_advanced_2 on windows (ray-project#20994)

.gitignore

@@ -57,6 +57,7 @@ python/.eggs
 *.so
 *.dylib
 *.dll
+python/ray/_raylet.pyd
 
 # Incremental linking files
 *.ilk

ci/travis/ci.sh

@@ -148,7 +148,6 @@ test_python() {
       -python/ray/serve:test_standalone # timeout
       -python/ray/tests:test_actor_advanced # timeout
       -python/ray/tests:test_actor_failures # flaky
-      -python/ray/tests:test_advanced_2
       -python/ray/tests:test_autoscaler # We don't support Autoscaler on Windows
       -python/ray/tests:test_autoscaler_aws
       -python/ray/tests:test_component_failures

python/ray/_private/services.py

@@ -650,6 +650,15 @@ def preexec_fn():
     # before the process itself is assigned to the job.
     # After that point, its children will not be added to the job anymore.
     CREATE_SUSPENDED = 0x00000004  # from Windows headers
+    if sys.platform == "win32":
+        # CreateProcess, which underlies Popen, is limited to
+        # 32,767 characters, including the Unicode terminating null
+        # character
+        total_chrs = sum([len(x) for x in command])
+        if total_chrs > 31766:
+            raise ValueError(
+                f"command is limited to a total of 31767 characters, "
+                f"got {total_chrs}")
 
     process = ConsolePopen(
         command,

python/ray/tests/test_advanced.py

@@ -371,7 +371,6 @@ def test_illegal_api_calls(ray_start_regular):
 
 @pytest.mark.skipif(
     client_test_enabled(), reason="grpc interaction with releasing resources")
-@pytest.mark.skipif(sys.platform == "win32", reason="Time out on Windows")
 def test_multithreading(ray_start_2_cpus):
     # This test requires at least 2 CPUs to finish since the worker does not
     # release resources when joining the threads.
@@ -653,7 +652,6 @@ def bar():
 
 # This case tests whether gcs-based actor scheduler works properly with
 # a normal task co-existed.
-@pytest.mark.skipif(sys.platform == "win32", reason="Time out on Windows")
 def test_schedule_actor_and_normal_task(ray_start_cluster):
     cluster = ray_start_cluster
     cluster.add_node(
@@ -699,7 +697,6 @@ def fun(singal1, signal_actor2):
 
 # This case tests whether gcs-based actor scheduler works properly
 # in a large scale.
-@pytest.mark.skipif(sys.platform == "win32", reason="Time out on Windows")
 def test_schedule_many_actors_and_normal_tasks(ray_start_cluster):
     cluster = ray_start_cluster
 
@@ -742,7 +739,6 @@ def fun():
 # This case tests whether gcs-based actor scheduler distributes actors
 # in a balanced way. By default, it uses the `SPREAD` strategy of
 # gcs resource scheduler.
-@pytest.mark.skipif(sys.platform == "win32", reason="Time out on Windows")
 @pytest.mark.parametrize("args", [[5, 20], [5, 3]])
 def test_actor_distribution_balance(ray_start_cluster, args):
     cluster = ray_start_cluster
@@ -783,7 +779,6 @@ def method(self):
 
 # This case tests whether RequestWorkerLeaseReply carries normal task resources
 # when the request is rejected (due to resource preemption by normal tasks).
-@pytest.mark.skipif(sys.platform == "win32", reason="Time out on Windows")
 def test_worker_lease_reply_with_resources(ray_start_cluster):
     cluster = ray_start_cluster
     cluster.add_node(

python/ray/tests/test_advanced_2.py

@@ -18,6 +18,7 @@
 logger = logging.getLogger(__name__)
 
 
+@pytest.mark.skipif(sys.platform == "win32", reason="OOM on Windows")
 def test_resource_constraints(shutdown_only):
     num_workers = 20
     ray.init(num_cpus=10, num_gpus=2)
@@ -94,6 +95,7 @@ def f(n):
     assert duration > 1
 
 
+@pytest.mark.skipif(sys.platform == "win32", reason="OOM on Windows")
 def test_multi_resource_constraints(shutdown_only):
     num_workers = 20
     ray.init(num_cpus=10, num_gpus=10)
@@ -559,7 +561,12 @@ def k():
 
 
 def test_many_custom_resources(shutdown_only):
-    num_custom_resources = 10000
+    # This eventually turns into a command line argument which on windows is
+    # limited to 32,767 characters.
+    if sys.platform == "win32":
+        num_custom_resources = 4000
+    else:
+        num_custom_resources = 10000
     total_resources = {
         str(i): np.random.randint(1, 7)
         for i in range(num_custom_resources)