Synchronization and Locks
Explore how to prevent race conditions and ensure data consistency in multithreaded Java applications by mastering synchronization techniques. Learn to use synchronized methods, blocks, and ReentrantLock for controlling thread access to shared resources and improving program reliability.
Threads allow our applications to multitask, executing complex operations in parallel to maximize performance. However, this power comes with a significant challenge when threads share memory. If two threads attempt to update the same variable at the exact same time, subtle bugs appear, updates are lost, and results become unpredictable.
In this lesson, we will master the tools required to enforce order. We will learn how to create “critical sections” that allow only one thread to enter at a time, ensuring our data remains consistent regardless of how many threads are running.
Understanding race conditions
Before we fix the problem, we must understand exactly what goes wrong. A race condition occurs when the correctness of a computation depends on the relative timing or interleaving of multiple threads. The most common form is the “check-then-act” or “read-modify-write” scenario.
Consider a simple counter. When we write count++, it looks like a single action. In reality, the computer performs three distinct steps:
Read the current value of
countfrom memory.Add one to that value.
Write the new value back to memory.
If two threads perform this sequence simultaneously, they might both read the value 0, both add 1, and both write 1. We expected the count to be 2, but we lost an update because the operation was not atomic. Here, “atomic” means the operation completes as a single, indivisible step from the perspective of ...