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90 lines
3.6 KiB
Python
90 lines
3.6 KiB
Python
import csv
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from timeit import timeit
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from typing import Any, Union
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from django.core.management.base import BaseCommand, CommandParser
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from zerver.lib.queue import SimpleQueueClient, queue_json_publish
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from zerver.worker.queue_processors import BatchNoopWorker, NoopWorker
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class Command(BaseCommand):
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help = """Times the overhead of enqueuing and dequeuing messages from RabbitMQ."""
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def add_arguments(self, parser: CommandParser) -> None:
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parser.add_argument(
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"--count", help="Number of messages to enqueue", default=10000, type=int
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)
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parser.add_argument("--reps", help="Iterations of enqueue/dequeue", default=1, type=int)
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parser.add_argument("--batch", help="Enables batch dequeuing", action="store_true")
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parser.add_argument("--csv", help="Path to CSV output", default="rabbitmq-timings.csv")
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parser.add_argument(
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"--prefetches",
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help="Limits the prefetch size; RabbitMQ defaults to unbounded (0)",
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default=[0],
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nargs="+",
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type=int,
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)
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parser.add_argument(
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"--slow",
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help="Which request numbers should take 60s (1-based)",
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action="append",
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type=int,
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default=[],
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)
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def handle(self, *args: Any, **options: Any) -> None:
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print("Purging queue...")
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queue = SimpleQueueClient()
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queue_name = "noop_batch" if options["batch"] else "noop"
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queue.ensure_queue(queue_name, lambda channel: channel.queue_purge("noop"))
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count = options["count"]
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reps = options["reps"]
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with open(options["csv"], "w", newline="") as csvfile:
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writer = csv.DictWriter(
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csvfile, fieldnames=["Queue size", "Queue type", "Prefetch", "Rate"]
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)
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writer.writeheader()
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for prefetch in options["prefetches"]:
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print(f"Queue size {count}, prefetch {prefetch}...")
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worker: Union[NoopWorker, BatchNoopWorker] = NoopWorker(count, options["slow"])
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if options["batch"]:
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worker = BatchNoopWorker(count, options["slow"])
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if prefetch > 0 and prefetch < worker.batch_size:
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print(
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f" Skipping, as prefetch {prefetch} is less than batch size {worker.batch_size}"
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)
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continue
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worker.ENABLE_TIMEOUTS = True
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worker.setup()
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assert worker.q is not None
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assert worker.q.channel is not None
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worker.q.channel.basic_qos(prefetch_count=prefetch)
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total_time = 0.0
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for i in range(1, reps + 1):
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worker.consumed = 0
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timeit(
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lambda: queue_json_publish(queue_name, {}),
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number=count,
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)
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duration = timeit(
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lambda: worker.start(),
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number=1,
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)
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print(f" {i}/{reps}: {count}/{duration}s = {count / duration}/s")
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total_time += duration
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writer.writerow(
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{
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"Queue size": count,
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"Queue type": queue_name,
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"Prefetch": prefetch,
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"Rate": count / duration,
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}
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)
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csvfile.flush()
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print(f" Overall: {reps * count}/{total_time}s = {(reps * count) / total_time}/s")
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