How to Avoid Deadlocks and Keep Your Programs Running Smoothly

Struggling with deadlocks in your multithreaded applications? This guide provides a clear explanation of deadlocks and practical strategies to minimize and handle them, ensuring your programs run efficiently.
How to Avoid Deadlocks and Keep Your Programs Running Smoothly
Last updated 18:18 17/07/2024 GMT+7

How deadlocks occur, their impact, and various techniques to prevent and manage them. You'll learn about acquiring resources in a specific order, using timeouts, avoiding circular dependencies, and leveraging deadlock detection mechanisms. Additionally, the post explores methods for reducing lock duration and choosing appropriate isolation levels to minimize conflicts. Finally, it highlights deadlock analysis tools available in popular databases like MySQL and Postgres. By understanding deadlocks, programmers can create robust and efficient multithreaded applications.

What is deadlock?

Imagine you're in a busy school cafeteria. You need a fork and a knife to eat your lunch. Your friend also needs both utensils. There's only one fork and one knife on the table.
You grab the fork, and your friend grabs the knife. Now you're both stuck! You can't eat without the knife, and your friend can't eat without the fork. Neither of you wants to give up your utensil, hoping the other will share first. This situation where everyone is waiting for someone else is called a deadlock.

In computer programming, deadlock happens in multithreading when:

  • Multiple threads (like you and your friend) need multiple resources (like the fork and knife).
  • Each thread holds one resource and waits for the other.
  • None of the threads are willing to give up their resource.
  • All threads are stuck, waiting forever.

To prevent deadlock

In the same order

Implement a system where resources are always requested in the same order.

Example: In a banking app, let's say we have two accounts: A and B. To transfer money, we need to lock both accounts. To prevent deadlock, we always lock the account with the lower account number first.

def transfer(from_account, to_account, amount):
    first_lock = min(from_account, to_account)
    second_lock = max(from_account, to_account)
    
    with lock(first_lock):
        with lock(second_lock):
            # Perform the transfer
            pass

Use timeouts

Use timeouts, so threads don't wait forever. Example: When trying to acquire a lock, we set a maximum wait time. If the lock isn't acquired within this time, the thread gives up and tries again later.

SET LOCK_TIMEOUT 5000; -- Sets timeout to 5 seconds
BEGIN TRANSACTION;
-- Your SQL statements here
COMMIT;

Avoid circular dependencies

Design your program to avoid circular dependencies. Example: Instead of having Thread A wait for Thread B while Thread B waits for Thread A, redesign so that only one thread waits for the other.

# Avoid this:
def thread_a():
    with lock_a:
        # do something
        with lock_b:
            # do something else

def thread_b():
    with lock_b:
        # do something
        with lock_a:
            # do something else

# Do this instead:
def thread_a():
    with lock_a:
        # do something
        # Signal thread_b to continue

def thread_b():
    # Wait for signal from thread_a
    with lock_b:
        # do something

Deadlock detection

Many databases have built-in deadlock detection. When detected, one transaction is chosen as a "victim" and rolled back.

Reducing lock duration

Keep transactions as short as possible to minimize the chance of conflicts.

-- Instead of this:
BEGIN TRANSACTION;
-- Long-running operation
UPDATE LargeTable SET column = value;
COMMIT;

-- Do this:
BEGIN TRANSACTION;
UPDATE LargeTable SET column = value WHERE id BETWEEN 1 AND 1000;
COMMIT;
-- Repeat for other ranges

Using appropriate isolation levels

Choose the right isolation level for your needs. Lower isolation levels can reduce lock contention.

SET TRANSACTION ISOLATION LEVEL READ COMMITTED;
BEGIN TRANSACTION;
-- Your SQL statements here
COMMIT;

Deadlock analysis

Many databases provide tools to analyze deadlocks. Use these to identify and fix problematic query patterns.
Examples:

Understanding deadlock helps programmers create more efficient and reliable software.