Welcome to Part 3 of our multithreading series!
In this part, we’ll dive into the mechanics of Deadlock in multithreading. What causes it, How to identify and preventive strategies you can use to avoid turning your code into a gridlocked intersection. Application grinds to a halt, often without any visible errors, leaving developers puzzled and systems frozen.
A useful analogy to understand deadlock is to imagine a railway network with multiple trains on intersecting tracks.
Since each train is waiting for the next one to move, none can proceed, leading to a deadlock. In this scenario, the inefficient signaling system allowed each train to enter its respective section without first confirming that the next section would be free, trapping all trains in an unbreakable cycle.
This train example illustrates a typical deadlock in multithreading, where threads (like the trains) hold onto resources (track sections) while waiting for other resources to be freed, but none can progress. To prevent this kind of deadlock in software, effective resource management strategies—analogous to smarter railway signaling—must be implemented to avoid circular dependencies and ensure safe passage for each thread.
Deadlock is a situation in which threads (or processes) are indefinitely blocked, waiting for resources that other threads hold. This scenario leads to an unbreakable cycle of dependencies, where no involved thread can make progress. Understanding the basics of deadlock is essential before exploring the methods for detection, prevention, and resolution.
For a deadlock to occur, four conditions must be met simultaneously, known as the Coffman conditions:
Mutual Exclusion: At least one resource must be held in a non-shareable mode, meaning only one thread can use it at a time.
Hold and Wait: A thread must hold one resource and wait to acquire additional resources that other threads hold.
No Preemption: Resources cannot be forcibly taken away from threads. They must be released voluntarily.
Circular Wait: A closed chain of threads exists, where each thread holds at least one resource needed by the next thread in the chain.
Let's understand as a sequence diagram
In above animation,
All four conditions shared above for deadlock are present, which results indefinite block. Breaking any one of them can prevent deadlock.
Detecting deadlocks, especially in large-scale applications, can be challenging. However, the following approaches can help identify deadlocks
For detailed overview to understand how to debug/monitor deadlocks please visit Debug and Monitor Deadlock using VisualVM and jstack
Applying the Wait-Die and Wound-Wait Schemes
Wait-Die Scheme: When a thread requests a lock held by another thread, the database assesses the relative priority (usually based on the timestamp of each thread). If the requesting thread has a higher priority, it waits; otherwise, it dies (restarts).
Wound-Wait Scheme: If the requesting thread has a higher priority, it wounds (preempts) the lower-priority thread by forcing it to release the lock.
Immutable Objects for Shared State
Design shared state as immutable wherever possible. Since immutable objects cannot be modified, they require no locks for concurrent access, reducing the risk of deadlock and simplifying code.
Using tryLock with Timeout for Lock Acquisition: Unlike a standard synchronized block, ReentrantLock allows using tryLock(timeout, unit) to attempt acquiring a lock within a specified period. If the lock isn’t acquired within that time, it releases resources, preventing indefinite blocking.
ReentrantLock lock1 = new ReentrantLock(); ReentrantLock lock2 = new ReentrantLock(); public void acquireLocks() { try { if (lock1.tryLock(100, TimeUnit.MILLISECONDS)) { try { if (lock2.tryLock(100, TimeUnit.MILLISECONDS)) { // Critical section } } finally { lock2.unlock(); } } } catch (InterruptedException e) { Thread.currentThread().interrupt(); } finally { lock1.unlock(); } }
import java.util.concurrent.locks.Lock; import java.util.concurrent.locks.ReentrantLock; public class LockOrderingExample { private static final Lock lock1 = new ReentrantLock(); private static final Lock lock2 = new ReentrantLock(); public static void main(String[] args) { Thread thread1 = new Thread(() -> { acquireLocksInOrder(lock1, lock2); }); Thread thread2 = new Thread(() -> { acquireLocksInOrder(lock1, lock2); }); thread1.start(); thread2.start(); } private static void acquireLocksInOrder(Lock firstLock, Lock secondLock) { try { firstLock.lock(); System.out.println(Thread.currentThread().getName() + " acquired lock1"); secondLock.lock(); System.out.println(Thread.currentThread().getName() + " acquired lock2"); // Perform some operations } finally { secondLock.unlock(); System.out.println(Thread.currentThread().getName() + " released lock2"); firstLock.unlock(); System.out.println(Thread.currentThread().getName() + " released lock1"); } } }
Use Thread-Safe/Concurrent Collections: Java’s java.util.concurrent package provides thread-safe implementations of common data structures (ConcurrentHashMap, CopyOnWriteArrayList, etc.) that handle synchronization internally, reducing the need for explicit locks. These collections minimize deadlocks as they’re designed to avoid the need for explicit locking, using techniques like internal partitioning.
Avoid Nested Locks
Minimize acquiring multiple locks within the same block to avoid circular dependencies. If nested locks are necessary, use consistent lock ordering
Whether you're a beginner or a seasoned developer, understanding deadlock is crucial for writing robust, efficient code in concurrent systems. In this article, we explored what deadlocks are, their causes, and practical ways to prevent them. By implementing effective resource allocation strategies, analyzing task dependencies, and utilizing tools like thread dumps and deadlock detection tools, developers can minimize deadlock risk and optimize their code for smooth concurrency.
As we continue our journey through the core concepts of multithreading, stay tuned for the next articles in this series. We’ll dive into Critical Sections, understanding how to manage shared resources safely among multiple thread. We will also discuss the concept of Race Conditions, a common concurrency issue that can lead to unpredictable behavior and bugs if left unchecked.
With each step, you’ll gain deeper insights into how to make your applications thread-safe, efficient, and resilient. Keep pushing the boundaries of your multithreading knowledge to build better, more performant software!
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