1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506
|
from __future__ import annotations
import asyncio
import os
import random
from contextlib import suppress
from time import sleep
from unittest import mock
import psutil
import pytest
from tlz import first, merge, partition_all
import dask.config
from dask import delayed
from dask.utils import parse_bytes
from distributed import Client, Nanny, profile, wait
from distributed.comm import CommClosedError
from distributed.compatibility import MACOS
from distributed.metrics import time
from distributed.utils import CancelledError, sync
from distributed.utils_test import (
NO_AMM,
BlockedGatherDep,
BlockedGetData,
async_wait_for,
captured_logger,
cluster,
div,
gen_cluster,
inc,
slowadd,
slowinc,
)
from distributed.worker_state_machine import FreeKeysEvent
pytestmark = pytest.mark.ci1
@pytest.mark.slow()
def test_submit_after_failed_worker_sync(loop):
with cluster() as (s, [a, b]):
with Client(s["address"], loop=loop) as c:
L = c.map(inc, range(10))
wait(L)
a["proc"]().terminate()
total = c.submit(sum, L)
assert total.result() == sum(map(inc, range(10)))
@pytest.mark.slow()
@pytest.mark.parametrize("compute_on_failed", [False, True])
@gen_cluster(client=True, config={"distributed.comm.timeouts.connect": "500ms"})
async def test_submit_after_failed_worker_async(c, s, a, b, compute_on_failed):
async with Nanny(s.address, nthreads=2) as n:
await c.wait_for_workers(3)
L = c.map(inc, range(10))
await wait(L)
kill_task = asyncio.create_task(n.kill())
compute_addr = n.worker_address if compute_on_failed else a.address
total = c.submit(sum, L, workers=[compute_addr], allow_other_workers=True)
assert await total == sum(range(1, 11))
await kill_task
@gen_cluster(client=True, timeout=60)
async def test_submit_after_failed_worker(c, s, a, b):
L = c.map(inc, range(10))
await wait(L)
await a.close()
total = c.submit(sum, L)
assert await total == sum(range(1, 11))
@pytest.mark.slow
def test_gather_after_failed_worker(loop):
with cluster() as (s, [a, b]):
with Client(s["address"], loop=loop) as c:
L = c.map(inc, range(10))
wait(L)
a["proc"]().terminate()
result = c.gather(L)
assert result == list(map(inc, range(10)))
@pytest.mark.slow
@gen_cluster(client=True, Worker=Nanny, nthreads=[("127.0.0.1", 1)] * 4, timeout=60)
async def test_gather_then_submit_after_failed_workers(c, s, w, x, y, z):
L = c.map(inc, range(20))
await wait(L)
w.process.process._process.terminate()
total = c.submit(sum, L)
for _ in range(3):
await wait(total)
addr = first(s.tasks[total.key].who_has).address
for worker in [x, y, z]:
if worker.worker_address == addr:
worker.process.process._process.terminate()
break
result = await c.gather([total])
assert result == [sum(map(inc, range(20)))]
@gen_cluster(Worker=Nanny, client=True, timeout=60)
async def test_restart(c, s, a, b):
x = c.submit(inc, 1)
y = c.submit(inc, x)
z = c.submit(div, 1, 0)
await y
assert s.tasks[x.key].state == "memory"
assert s.tasks[y.key].state == "memory"
assert s.tasks[z.key].state != "memory"
f = await c.restart()
assert f is c
assert len(s.workers) == 2
assert not any(ws.occupancy for ws in s.workers.values())
assert not s.tasks
assert x.cancelled()
assert y.cancelled()
assert z.cancelled()
assert not s.tasks
assert not any(cs.wants_what for cs in s.clients.values())
@gen_cluster(Worker=Nanny, client=True, timeout=60)
async def test_restart_cleared(c, s, a, b):
x = 2 * delayed(1) + 1
f = c.compute(x)
await wait([f])
await c.restart()
for coll in [s.tasks, s.unrunnable]:
assert not coll
def test_restart_sync(loop):
with cluster(nanny=True) as (s, [a, b]):
with Client(s["address"], loop=loop) as c:
x = c.submit(div, 1, 2)
x.result()
assert sync(loop, c.scheduler.who_has)
c.restart()
assert not sync(loop, c.scheduler.who_has)
assert x.cancelled()
assert len(c.nthreads()) == 2
with pytest.raises(CancelledError):
x.result()
y = c.submit(div, 1, 3)
assert y.result() == 1 / 3
def test_worker_doesnt_await_task_completion(loop):
with cluster(nanny=True, nworkers=1) as (s, [w]):
with Client(s["address"], loop=loop) as c:
future = c.submit(sleep, 100)
sleep(0.1)
start = time()
c.restart(timeout="5s", wait_for_workers=False)
stop = time()
assert stop - start < 10
@gen_cluster(Worker=Nanny, timeout=60)
async def test_multiple_clients_restart(s, a, b):
async with Client(s.address, asynchronous=True) as c1, Client(
s.address, asynchronous=True
) as c2:
x = c1.submit(inc, 1)
y = c2.submit(inc, 2)
xx = await x
yy = await y
assert xx == 2
assert yy == 3
await c1.restart()
assert x.cancelled()
start = time()
while not y.cancelled():
await asyncio.sleep(0.01)
assert time() < start + 5
assert not c1.futures
assert not c2.futures
# Ensure both clients still work after restart.
# Reusing a previous key has no effect.
x2 = c1.submit(inc, 1, key=x.key)
y2 = c2.submit(inc, 2, key=y.key)
assert x2._generation != x._generation
assert y2._generation != y._generation
assert await x2 == 2
assert await y2 == 3
del x2, y2
await async_wait_for(lambda: not s.tasks, timeout=5)
@gen_cluster(Worker=Nanny, timeout=60)
async def test_restart_scheduler(s, a, b):
assert len(s.workers) == 2
pids = (a.pid, b.pid)
assert pids[0]
assert pids[1]
await s.restart()
assert len(s.workers) == 2
pids2 = (a.pid, b.pid)
assert pids2[0]
assert pids2[1]
assert pids != pids2
@gen_cluster(Worker=Nanny, client=True, timeout=60)
async def test_forgotten_futures_dont_clean_up_new_futures(c, s, a, b):
x = c.submit(inc, 1)
await c.restart()
y = c.submit(inc, 1)
del x
# Ensure that the profiler has stopped and released all references to x so that it
# can be garbage-collected
with profile.lock:
pass
await asyncio.sleep(0.1)
await y
@pytest.mark.slow
@pytest.mark.flaky(condition=MACOS, reruns=10, reruns_delay=5)
@gen_cluster(client=True, timeout=60, active_rpc_timeout=10)
async def test_broken_worker_during_computation(c, s, a, b):
s.allowed_failures = 100
async with Nanny(s.address, nthreads=2) as n:
start = time()
while len(s.workers) < 3:
await asyncio.sleep(0.01)
assert time() < start + 5
N = 256
expected_result = N * (N + 1) // 2
i = 0
L = c.map(inc, range(N), key=["inc-%d-%d" % (i, j) for j in range(N)])
while len(L) > 1:
i += 1
L = c.map(
slowadd,
*zip(*partition_all(2, L)),
key=["add-%d-%d" % (i, j) for j in range(len(L) // 2)],
)
await asyncio.sleep(random.random() / 20)
with suppress(CommClosedError): # comm will be closed abrupty
await c.run(os._exit, 1, workers=[n.worker_address])
await asyncio.sleep(random.random() / 20)
while len(s.workers) < 3:
await asyncio.sleep(0.01)
with suppress(
CommClosedError, EnvironmentError
): # perhaps new worker can't be contacted yet
await c.run(os._exit, 1, workers=[n.worker_address])
[result] = await c.gather(L)
assert isinstance(result, int)
assert result == expected_result
@gen_cluster(client=True, Worker=Nanny, timeout=60)
async def test_restart_during_computation(c, s, a, b):
xs = [delayed(slowinc)(i, delay=0.01) for i in range(50)]
ys = [delayed(slowinc)(i, delay=0.01) for i in xs]
zs = [delayed(slowadd)(x, y, delay=0.01) for x, y in zip(xs, ys)]
total = delayed(sum)(zs)
result = c.compute(total)
await asyncio.sleep(0.5)
assert any(ws.processing for ws in s.workers.values())
await c.restart()
assert not any(ws.processing for ws in s.workers.values())
assert not s.tasks
class SlowTransmitData:
def __init__(self, data, delay=0.1):
self.delay = delay
self.data = data
def __reduce__(self):
sleep(self.delay)
return SlowTransmitData, (self.data, self.delay)
def __sizeof__(self) -> int:
# Ensure this is offloaded to avoid blocking loop
return parse_bytes(dask.config.get("distributed.comm.offload")) + 1
@pytest.mark.slow
@gen_cluster(client=True, config={"distributed.scheduler.work-stealing": False})
async def test_worker_who_has_clears_after_failed_connection(c, s, a, b):
"""This test is very sensitive to cluster state consistency. Timeouts often
indicate subtle deadlocks. Be mindful when marking flaky/repeat/etc."""
async with Nanny(s.address, nthreads=2, worker_class=BlockedGetData) as n:
while len(s.workers) < 3:
await asyncio.sleep(0.01)
n_worker_address = n.worker_address
futures = c.map(
inc,
range(20),
key=["f%d" % i for i in range(20)],
workers=[n_worker_address],
allow_other_workers=True,
)
def sink(*args):
pass
await wait(futures)
result_fut = c.submit(sink, futures, workers=a.address)
await n.kill(timeout=1)
while len(s.workers) > 2:
await asyncio.sleep(0.01)
await result_fut
assert not a.state.has_what.get(n_worker_address)
assert not any(
n_worker_address in s for ts in a.state.tasks.values() for s in ts.who_has
)
@gen_cluster(
client=True,
nthreads=[("127.0.0.1", 1), ("127.0.0.1", 2), ("127.0.0.1", 3)],
config=NO_AMM,
)
async def test_worker_same_host_replicas_missing(c, s, a, b, x):
# See GH4784
def mock_address_host(addr):
# act as if A and X are on the same host
nonlocal a, b, x
if addr in [a.address, x.address]:
return "A"
else:
return "B"
with mock.patch("distributed.worker.get_address_host", mock_address_host):
futures = c.map(
slowinc,
range(20),
delay=0.1,
key=["f%d" % i for i in range(20)],
workers=[a.address],
allow_other_workers=True,
)
await wait(futures)
# replicate data to avoid the scheduler retriggering the computation
# retriggering cleans up the state nicely but doesn't reflect real world
# scenarios where there may be replicas on the cluster, e.g. they are
# replicated as a dependency somewhere else
await c.replicate(futures, n=2, workers=[a.address, b.address])
def sink(*args):
pass
# Since A and X are mocked to be co-located, X will consistently pick A
# to fetch data from. It will never succeed since we're removing data
# artificially, without notifying the scheduler.
# This can only succeed if B handles the missing data properly by
# removing A from the known sources of keys
a.handle_stimulus(
FreeKeysEvent(keys=["f1"], stimulus_id="Am I evil?")
) # Yes, I am!
result_fut = c.submit(sink, futures, workers=x.address)
await result_fut
@pytest.mark.slow
@gen_cluster(client=True, timeout=60, Worker=Nanny, nthreads=[("127.0.0.1", 1)])
async def test_restart_timeout_on_long_running_task(c, s, a):
with captured_logger("distributed.scheduler") as sio:
future = c.submit(sleep, 3600)
await asyncio.sleep(0.1)
await c.restart()
text = sio.getvalue()
assert "timeout" not in text.lower()
@pytest.mark.slow
@gen_cluster(client=True, scheduler_kwargs={"worker_ttl": "500ms"})
async def test_worker_time_to_live(c, s, a, b):
from distributed.scheduler import heartbeat_interval
assert set(s.workers) == {a.address, b.address}
a.periodic_callbacks["heartbeat"].stop()
start = time()
while set(s.workers) == {a.address, b.address}:
await asyncio.sleep(0.01)
assert set(s.workers) == {b.address}
# Worker removal is triggered after 10 * heartbeat
# This is 10 * 0.5s at the moment of writing.
interval = 10 * heartbeat_interval(len(s.workers))
# Currently observing an extra 0.3~0.6s on top of the interval.
# Adding some padding to prevent flakiness.
assert time() - start < interval + 2.0
@gen_cluster(client=True, nthreads=[("", 1)])
async def test_forget_data_not_supposed_to_have(c, s, a):
"""If a dependency fetch finishes on a worker after the scheduler already released
everything, the worker might be stuck with a redundant replica which is never
cleaned up.
"""
async with BlockedGatherDep(s.address) as b:
x = c.submit(inc, 1, key="x", workers=[a.address])
y = c.submit(inc, x, key="y", workers=[b.address])
await b.in_gather_dep.wait()
assert b.state.tasks["x"].state == "flight"
x.release()
y.release()
while s.tasks:
await asyncio.sleep(0.01)
b.block_gather_dep.set()
while b.state.tasks:
await asyncio.sleep(0.01)
@gen_cluster(
client=True,
nthreads=[("", 1)] * 3,
config=merge(NO_AMM, {"distributed.comm.timeouts.connect": "1s"}),
Worker=Nanny,
)
async def test_failing_worker_with_additional_replicas_on_cluster(c, s, n0, n1, n2):
"""
If a worker detects a missing dependency, the scheduler is notified. If no
other replica is available, the dependency is rescheduled. A reschedule
typically causes a lot of state to be reset. However, if another replica is
available, we'll need to ensure that the worker can detect outdated state
and correct its state.
"""
def dummy(*args, **kwargs):
return
proc1 = psutil.Process(n1.pid)
f1 = c.submit(
SlowTransmitData,
1,
delay=0.1,
key="f1",
workers=[n0.worker_address],
)
await wait(f1)
# We'll schedule tasks on two workers, s.t. f1 is replicated. We will
# suspend one of the workers and kill the origin worker of f1 such that a
# comm failure causes the worker to handle a missing dependency. It will ask
# the schedule such that it knows that a replica is available on f2 and
# reschedules the fetch
f2 = c.submit(dummy, f1, key="f2", workers=[n1.worker_address])
f3 = c.submit(dummy, f1, key="f3", workers=[n2.worker_address])
proc1.suspend()
await wait(f3)
# Because of this line we need to disable AMM; otherwise it could choose to delete
# the replicas of f1 on n1 and n2 and keep the one on n0.
await n0.close()
proc1.resume()
await c.gather([f1, f2, f3])
|