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https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
01dcb993c7
Now that `HeadOnly` becomes the new default HTTP location, we can re-enable the long running tests to use local multi-clusters. (also fixed the controller's API to match up to date, we should have caught these, I will open issues for this.)
71 lines
1.7 KiB
Python
71 lines
1.7 KiB
Python
import time
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import subprocess
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from subprocess import PIPE
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import requests
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import ray
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from ray import serve
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from ray.cluster_utils import Cluster
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num_redis_shards = 1
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redis_max_memory = 10**8
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object_store_memory = 10**8
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num_nodes = 4
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cluster = Cluster()
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for i in range(num_nodes):
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cluster.add_node(
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redis_port=6379 if i == 0 else None,
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num_redis_shards=num_redis_shards if i == 0 else None,
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num_cpus=8,
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num_gpus=0,
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resources={str(i): 2},
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object_store_memory=object_store_memory,
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redis_max_memory=redis_max_memory,
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dashboard_host="0.0.0.0",
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)
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ray.init(address=cluster.address, dashboard_host="0.0.0.0")
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client = serve.start()
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@serve.accept_batch
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def echo(requests_batch):
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time.sleep(0.01) # Sleep for 10ms
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return ["hi" for _ in range(len(requests_batch))]
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config = {"num_replicas": 7, "max_batch_size": 16}
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client.create_backend("echo:v1", echo, config=config)
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client.create_endpoint("echo", backend="echo:v1", route="/echo")
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print("Warming up")
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for _ in range(5):
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resp = requests.get("http://127.0.0.1:8000/echo").text
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print(resp)
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time.sleep(0.5)
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connections = int(config["num_replicas"] * config["max_batch_size"] * 0.75)
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num_threads = 2
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time_to_run = "60m"
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while True:
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proc = subprocess.Popen(
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[
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"wrk",
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"-c",
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str(connections),
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"-t",
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str(num_threads),
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"-d",
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time_to_run,
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"http://127.0.0.1:8000/echo",
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],
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stdout=PIPE,
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stderr=PIPE,
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)
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print("started load testing")
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proc.wait()
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out, err = proc.communicate()
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print(out.decode())
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print(err.decode())
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