[pull] master from ray-project:master#1068
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The assertion assumed that `a` and `b` would always be scheduled and none of `c`, which is not guaranteed. Added a condition to wait until `a` and `b` are scheduled before submitting the `c`s. I couldn't use `SignalActor` here because it would add task metrics. --------- Signed-off-by: Edward Oakes <ed.nmi.oakes@gmail.com>
We have observed that the idle worker memory usage as reported in the per component memory usage metric grows over time. Previous investigation has concluded that it's possible for idle workers to "leak" memory due to imported libraries caching memory regions between tasks, resulting in a large idle worker footprint between runs. We have also previously uncovered that memory leaks in popular libraries can also result in idle worker memory growth: apache/arrow#39808. However a recent investigation into the trivial workload below with no library usage still showed idle worker memory growth over time. ```py import ray from tqdm import tqdm import time ray.init() @ray.remote def produce(): a = b"0" * int(0.5 * 1024**3) time.sleep(5) return a @ray.remote def consume(bytes): time.sleep(5) return "done" refs = [] for _ in tqdm(range(16)): ref = produce.remote() refs.append(ref) consume_refs = [] for i in range(4): consume_refs.append(consume.remote(ref)) print(ray.get(consume_refs)) ``` Per component metric showing idle worker memory growth: <img width="1687" height="398" alt="image" src="https://github.com/user-attachments/assets/a8201713-d64a-44ff-bfd3-d9e070dd88b3" /> This growth is attributed to how "unique set size" is calculated in the query for per component memory usage metric. Previously, we computed the unique set size via the following query: ``` (sum(ray_component_rss_mb{instance=~".+",SessionName=~".+",ray_io_cluster=~".*",ClusterId=~"ID"} * 1024 * 1024) by (Component)) - (sum(ray_component_mem_shared_bytes{instance=~".+",SessionName=~".+",ray_io_cluster=~".*",ClusterId=~"ID"}) by (Component)) ``` The problematic part is the `* 1024 * 1024` which attempts to convert the rss back into bytes. However, the RSS was actually recorded in megabytes instead mebibytes, resulting in over calculation. As the RSS for the worker grows, this calculation grows increasingly incorrect as shown by the graph below where we demonstrate the difference between computing `pre-existing query (were we incorrectly convert megabytes into bytes)` and the actual `unique set size`. <img width="1189" height="590" alt="image" src="https://github.com/user-attachments/assets/5537ac8a-efb2-4160-926c-9259540e135b" /> This PR addresses this mis-conversion by establishing bytes as the unit for all per component memory metrics. The updated graph of idle worker memory usage in the per component memory usage panel is shown below: <img width="1689" height="398" alt="image" src="https://github.com/user-attachments/assets/09437ccd-b7a3-43f4-a7cc-7a430710164e" /> --------- Signed-off-by: davik <davik@anyscale.com> Co-authored-by: davik <davik@anyscale.com>
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