[CLI] Improve ray status for placement groups (ray-project#18289)

python/ray/autoscaler/_private/util.py

@@ -418,59 +418,81 @@ def parse_placement_group_resource_str(
         placement_group_resource_str: str) -> Tuple[str, Optional[str]]:
     """Parse placement group resource in the form of following 3 cases:
     {resource_name}_group_{bundle_id}_{group_name};
+    -> This case is ignored as it is duplicated to the case below.
     {resource_name}_group_{group_name};
     {resource_name}
 
     Returns:
-        Tuple of (resource_name, placement_group_name). placement_group_name
-        could be None if its not a placement group resource.
+        Tuple of (resource_name, placement_group_name, is_countable_resource).
+        placement_group_name could be None if its not a placement group
+        resource. is_countable_resource is True if the resource
+        doesn't contain bundle index. We shouldn't count resources
+        with bundle index because it will
+        have duplicated resource information as
+        wildcard resources (resource name without bundle index).
     """
     result = PLACEMENT_GROUP_RESOURCE_BUNDLED_PATTERN.match(
         placement_group_resource_str)
     if result:
-        return (result.group(1), result.group(3))
+        return (result.group(1), result.group(3), False)
     result = PLACEMENT_GROUP_RESOURCE_PATTERN.match(
         placement_group_resource_str)
     if result:
-        return (result.group(1), result.group(2))
-    return (placement_group_resource_str, None)
+        return (result.group(1), result.group(2), True)
+    return (placement_group_resource_str, None, True)
 
 
 def get_usage_report(lm_summary: LoadMetricsSummary) -> str:
     # first collect resources used in placement groups
-    placement_group_resource_usage = collections.defaultdict(float)
+    placement_group_resource_usage = {}
+    placement_group_resource_total = collections.defaultdict(float)
     for resource, (used, total) in lm_summary.usage.items():
-        (pg_resource_name,
-         pg_name) = parse_placement_group_resource_str(resource)
+        (pg_resource_name, pg_name,
+         is_countable) = parse_placement_group_resource_str(resource)
         if pg_name:
-            placement_group_resource_usage[pg_resource_name] += used
+            if pg_resource_name not in placement_group_resource_usage:
+                placement_group_resource_usage[pg_resource_name] = 0
+            if is_countable:
+                placement_group_resource_usage[pg_resource_name] += used
+                placement_group_resource_total[pg_resource_name] += total
             continue
 
     usage_lines = []
     for resource, (used, total) in sorted(lm_summary.usage.items()):
         if "node:" in resource:
             continue  # Skip the auto-added per-node "node:<ip>" resource.
 
-        (_, pg_name) = parse_placement_group_resource_str(resource)
+        (_, pg_name, _) = parse_placement_group_resource_str(resource)
         if pg_name:
             continue  # Skip resource used by placement groups
 
-        used_in_pg = placement_group_resource_usage[resource]
-
-        line = f" {used}/{total} {resource}"
-        if used_in_pg != 0:
-            line = line + f" ({used_in_pg} reserved in placement groups)"
+        pg_used = 0
+        pg_total = 0
+        used_in_pg = resource in placement_group_resource_usage
+        if used_in_pg:
+            pg_used = placement_group_resource_usage[resource]
+            pg_total = placement_group_resource_total[resource]
+            # Used includes pg_total because when pgs are created
+            # it allocates resources.
+            # To get the real resource usage, we should subtract the pg
+            # reserved resources from the usage and add pg used instead.
+            used = used - pg_total + pg_used
 
         if resource in ["memory", "object_store_memory"]:
             to_GiB = 1 / 2**30
-            used *= to_GiB
-            total *= to_GiB
-            used_in_pg *= to_GiB
-            line = f" {used:.2f}/{total:.3f} GiB {resource}"
-            if used_in_pg != 0:
-                line = line + f" ({used_in_pg:.2f} GiB reserved" \
-                    + " in placement groups)"
-        usage_lines.append(line)
+            line = (f" {(used * to_GiB):.2f}/"
+                    f"{(total * to_GiB):.3f} GiB {resource}")
+            if used_in_pg:
+                line = line + (f" ({(pg_used * to_GiB):.2f} used of "
+                               f"{(pg_total * to_GiB):.2f} GiB " +
+                               "reserved in placement groups)")
+            usage_lines.append(line)
+        else:
+            line = f" {used}/{total} {resource}"
+            if used_in_pg:
+                line += (f" ({pg_used} used of "
+                         f"{pg_total} reserved in placement groups)")
+            usage_lines.append(line)
     usage_report = "\n".join(usage_lines)
     return usage_report
 
@@ -488,8 +510,8 @@ def filter_placement_group_from_bundle(bundle: ResourceBundle):
         using_placement_group = False
         result_bundle = dict()
         for pg_resource_str, resource_count in bundle.items():
-            (resource_name,
-             pg_name) = parse_placement_group_resource_str(pg_resource_str)
+            (resource_name, pg_name,
+             _) = parse_placement_group_resource_str(pg_resource_str)
             result_bundle[resource_name] = resource_count
             if pg_name:
                 using_placement_group = True
@@ -600,6 +622,32 @@ def format_info_string(lm_summary, autoscaler_summary, time=None):
     return formatted_output
 
 
+def format_no_node_type_string(node_type: dict):
+    placement_group_resource_usage = {}
+    regular_resource_usage = collections.defaultdict(float)
+    for resource, total in node_type.items():
+        (pg_resource_name, pg_name,
+         is_countable) = parse_placement_group_resource_str(resource)
+        if pg_name:
+            if not is_countable:
+                continue
+            if pg_resource_name not in placement_group_resource_usage:
+                placement_group_resource_usage[pg_resource_name] = 0
+            placement_group_resource_usage[pg_resource_name] += total
+        else:
+            regular_resource_usage[resource] += total
+
+    output_lines = [""]
+    for resource, total in regular_resource_usage.items():
+        output_line = f"{resource}: {total}"
+        if resource in placement_group_resource_usage:
+            pg_resource = placement_group_resource_usage[resource]
+            output_line += f" ({pg_resource} reserved in placement groups)"
+        output_lines.append(output_line)
+
+    return "\n  ".join(output_lines)
+
+
 def format_info_string_no_node_types(lm_summary, time=None):
     if time is None:
         time = datetime.now()
@@ -608,7 +656,8 @@ def format_info_string_no_node_types(lm_summary, time=None):
 
     node_lines = []
     for node_type, count in lm_summary.node_types:
-        line = f" {count} node(s) with resources: {node_type}"
+        line = (f" {count} node(s) with resources:"
+                f"{format_no_node_type_string(node_type)}")
         node_lines.append(line)
     node_report = "\n".join(node_lines)
 

python/ray/tests/test_cli.py

@@ -204,9 +204,8 @@ def _check_output_via_pattern(name, result):
     expected_lines = _load_output_pattern(name)
 
     if result.exception is not None:
-        print(result.output)
         raise result.exception from None
-
+    print(result.output)
     expected = r" *\n".join(expected_lines) + "\n?"
     if re.fullmatch(expected, result.output) is None:
         _debug_check_line_by_line(result, expected_lines)

python/ray/tests/test_cli_patterns/test_ray_status.txt

@@ -1,7 +1,11 @@
 ======== Cluster status: .+
 Node status
 ------------------------------------------------------------
- 1 node\(s\) with resources: .+
+ 1 node\(s\) with resources:
+ .+
+ .+
+ .+
+ .+
 
 Resources
 ------------------------------------------------------------

python/ray/tests/test_placement_group.py

@@ -1980,5 +1980,44 @@ def is_usage_updated():
     assert demand_output["demand"] == "(no resource demands)"
 
 
+def test_placement_group_status(ray_start_cluster):
+    cluster = ray_start_cluster
+    cluster.add_node(num_cpus=4)
+    ray.init(address=cluster.address)
+
+    @ray.remote(num_cpus=1)
+    class A:
+        def ready(self):
+            pass
+
+    pg = ray.util.placement_group([{"CPU": 1}])
+    ray.get(pg.ready())
+
+    # Wait until the usage is updated, which is
+    # when the demand is also updated.
+    def is_usage_updated():
+        demand_output = get_ray_status_output(cluster.address)
+        return demand_output["usage"] != ""
+
+    wait_for_condition(is_usage_updated)
+    demand_output = get_ray_status_output(cluster.address)
+    cpu_usage = demand_output["usage"].split("\n")[0]
+    expected = "0.0/4.0 CPU (0.0 used of 1.0 reserved in placement groups)"
+    assert cpu_usage == expected
+
+    # 2 CPU + 1 PG CPU == 3.0/4.0 CPU (1 used by pg)
+    actors = [A.remote() for _ in range(2)]
+    actors_in_pg = [A.options(placement_group=pg).remote() for _ in range(1)]
+
+    ray.get([actor.ready.remote() for actor in actors])
+    ray.get([actor.ready.remote() for actor in actors_in_pg])
+    # Wait long enough until the usage is propagated to GCS.
+    time.sleep(5)
+    demand_output = get_ray_status_output(cluster.address)
+    cpu_usage = demand_output["usage"].split("\n")[0]
+    expected = "3.0/4.0 CPU (1.0 used of 1.0 reserved in placement groups)"
+    assert cpu_usage == expected
+
+
 if __name__ == "__main__":
     sys.exit(pytest.main(["-sv", __file__]))

python/ray/tests/test_resource_demand_scheduler.py

@@ -2391,7 +2391,7 @@ def test_info_string():
     lm_summary = LoadMetricsSummary(
         head_ip="0.0.0.0",
         usage={
-            "CPU": (530, 544),
+            "CPU": (530.0, 544.0),
             "GPU": (2, 2),
             "AcceleratorType:V100": (0, 2),
             "memory": (2 * 2**30, 2**33),
@@ -2439,7 +2439,7 @@ def test_info_string():
 
 Usage:
  0/2 AcceleratorType:V100
- 530/544 CPU
+ 530.0/544.0 CPU
  2/2 GPU
  2.00/8.000 GiB memory
  3.14/16.000 GiB object_store_memory
@@ -2461,7 +2461,7 @@ def test_info_string_failed_node_cap():
     lm_summary = LoadMetricsSummary(
         head_ip="0.0.0.0",
         usage={
-            "CPU": (530, 544),
+            "CPU": (530.0, 544.0),
             "GPU": (2, 2),
             "AcceleratorType:V100": (0, 2),
             "memory": (2 * 2**30, 2**33),
@@ -2532,7 +2532,7 @@ def test_info_string_failed_node_cap():
 
 Usage:
  0/2 AcceleratorType:V100
- 530/544 CPU (2.0 reserved in placement groups)
+ 530.0/544.0 CPU (2.0 used of 2.0 reserved in placement groups)
  2/2 GPU
  2.00/8.000 GiB memory
  3.14/16.000 GiB object_store_memory
@@ -2556,13 +2556,16 @@ def test_info_string_no_node_type():
     lm_summary = LoadMetricsSummary(
         head_ip="0.0.0.0",
         usage={
-            "CPU": (530, 544),
+            "CPU": (530.0, 544.0),
             "GPU": (2, 2),
             "AcceleratorType:V100": (0, 2),
-            "memory": (2 * 2**30, 2**33),
+            "memory": (6 * 2**30, 2**33),
             "object_store_memory": (3.14 * 2**30, 2**34),
-            "CPU_group_4a82a217aadd8326a3a49f02700ac5c2": (2.0, 2.0),
-            "memory_group_4a82a217aadd8326a3a49f02700ac5c2": (2**32, 2.0)
+            "CPU_group_4a82a217aadd8326a3a49f02700ac5c2": (1.0, 2.0),
+            "CPU_group_1_4a82a217aadd8326a3a49f02700ac5c2": (0.0, 1.0),
+            "CPU_group_2_4a82a217aadd8326a3a49f02700ac5c2": (1.0, 1.0),
+            "memory_group_4a82a217aadd8326a3a49f02700ac5c2": (2**32, 2**32),
+            "memory_group_0_4a82a217aadd8326a3a49f02700ac5c2": (2**32, 2**32)
         },
         resource_demand=[({
             "GPU": 0.5,
@@ -2585,22 +2588,30 @@ def test_info_string_no_node_type():
             "CPU": 16
         }, 100)],
         node_types=[({
-            "CPU": 16
+            "CPU": 16,
+            "CPU_group_4a82a217aadd8326a3a49f02700ac5c2": 2.0,
+            "CPU_group_1_4a82a217aadd8326a3a49f02700ac5c2": 1.0,
+            "CPU_group_2_4a82a217aadd8326a3a49f02700ac5c2": 1.0,
+            "memory": 2**33,
+            "memory_group_4a82a217aadd8326a3a49f02700ac5c2": 4 * 2**30,
+            "memory_group_0_4a82a217aadd8326a3a49f02700ac5c2": 4 * 2**30,
         }, 1)])
 
     expected = """
 ======== Cluster status: 2020-12-28 01:02:03 ========
 Node status
 -----------------------------------------------------
- 1 node(s) with resources: {'CPU': 16}
+ 1 node(s) with resources:
+  CPU: 16.0 (2.0 reserved in placement groups)
+  memory: 8589934592.0 (4294967296 reserved in placement groups)
 
 Resources
 -----------------------------------------------------
 Usage:
  0/2 AcceleratorType:V100
- 530/544 CPU (2.0 reserved in placement groups)
+ 529.0/544.0 CPU (1.0 used of 2.0 reserved in placement groups)
  2/2 GPU
- 2.00/8.000 GiB memory (4.00 GiB reserved in placement groups)
+ 6.00/8.000 GiB memory (4.00 used of 4.00 GiB reserved in placement groups)
  3.14/16.000 GiB object_store_memory
 
 Demands: