Skip to content

fix: cap ThreadPoolExecutor max_workers to prevent resource exhaustion #620

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
hobostay wants to merge 1 commit into
base: main
Choose a base branch
from
Open

fix: cap ThreadPoolExecutor max_workers to prevent resource exhaustion #620

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
5 changes: 4 additions & 1 deletion workflow/executor/parallel_executor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,10 +1,13 @@
"""Parallel execution helpers that eliminate duplicated code."""

import concurrent.futures
import os
from typing import Any, Callable, List, Tuple

from utils.log_manager import LogManager

MAX_WORKERS = min(32, (os.cpu_count() or 1) + 4)


class ParallelExecutor:
"""Manage parallel execution for workflow nodes.
Expand Down Expand Up @@ -103,7 +106,7 @@ def _execute_parallel_batch(
"""
self.log_manager.debug(f"Executing {len(items)} items in parallel")

with concurrent.futures.ThreadPoolExecutor(max_workers=len(items)) as executor:
with concurrent.futures.ThreadPoolExecutor(max_workers=min(len(items), MAX_WORKERS)) as executor:
futures = []
for item in items:
future = executor.submit(executor_func, item)
Expand Down