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mount: Add a stress test with multiple clients #25

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Oct 19, 2023
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57 changes: 57 additions & 0 deletions testcases/mount/mount_stress.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,57 @@
import threading
import testhelper
import pathlib


def _perform_file_operations(
client_id: int, root_dir: str, num_operations: int, file_size: int
) -> None:
try:
for i in range(num_operations):
filename = f"testfile_{client_id}_{i}.txt"
file_content = testhelper.generate_random_bytes(file_size)
path = pathlib.Path(root_dir, filename)
path.write_bytes(file_content)
file_content_out = path.read_bytes()

if file_content_out != file_content:
raise IOError("content mismatch")

path.unlink()
except Exception as ex:
print(f"Error while stress testing with Client {client_id}: %s", ex)
raise


def _stress_test(
root_dir: str, num_clients: int, num_operations: int, file_size: int
) -> None:
threads = []

for i in range(num_clients):
thread = threading.Thread(
target=_perform_file_operations,
args=(i, root_dir, num_operations, file_size),
)
threads.append(thread)

for thread in threads:
thread.start()

for thread in threads:
thread.join()

print("Stress test complete.")


def check_mnt_stress(root_dir: str) -> None:
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If this were a test we could consider using pytest's parametrize feature for generating the various combinations.

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Added a tracker in issue-30

_stress_test(root_dir, num_clients=5, num_operations=20, file_size=2**22)
_stress_test(
root_dir, num_clients=10, num_operations=30, file_size=2**23
)
_stress_test(
root_dir, num_clients=20, num_operations=40, file_size=2**24
)
_stress_test(
root_dir, num_clients=15, num_operations=25, file_size=2**25
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If I did my math right this means were creating files on the multiple gigabytes range, right? If so, I'm a little leery of using APIs like write_bytes that have to consume a single huge buffer in memory. I would much rather see a loop where the buffer size is something more typical like 4k and then write() out each chunk in a loop. In my past experience we had a python program reading files from http into a single huge buffer and that ended up taxing the memory of the system, when changing it to a read-write-loop it was much more manageable.

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@phlogistonjohn I am a bit confused here: the largest file-size here is 32M, and the overall data-set size if up 480M. Those numbers looks reasonably. In all odds, if we want to split those write/reads into multiple chunks, I would vote for larger chunk sized (say, 1M).

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I really can't do math. You are right about the sizes.

I'm fine with the code for now, I just don't find the use-one-buffer approach for all file sizes scalable and so I tend to shy away from it. I'd be open to a buffer size of 1M.

)
2 changes: 2 additions & 0 deletions testcases/mount/test_mount.py
Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@

from .mount_io import check_io_consistency
from .mount_dbm import check_dbm_consistency
from .mount_stress import check_mnt_stress

test_info = os.getenv("TEST_INFO_FILE")
test_info_dict = testhelper.read_yaml(test_info)
Expand All @@ -29,6 +30,7 @@ def mount_check(ipaddr: str, share_name: str) -> None:
os.mkdir(test_dir)
check_io_consistency(test_dir)
check_dbm_consistency(test_dir)
check_mnt_stress(test_dir)
finally:
if flag_mounted:
shutil.rmtree(test_dir, ignore_errors=True)
Expand Down