LMAX Disruptor: Mechanical Sympathy in Action
Why is your multi-threaded Java code slower than you expected? The answer is often Lock Contention and Cache Misses. The LMAX Disruptor was built to solve this by embracing "Mechanical Sympathy"—designing software that works with the CPU hardware rather than against it.
1. The Cost of Locks
Standard Java queues (like ) use locks to manage thread safety. At millions of operations per second, the time spent context switching and managing lock overhead exceeds the time spent on business logic.
2. The Ring Buffer
The Disruptor uses a pre-allocated Ring Buffer. Because it's a fixed size and pre-allocated, it eliminates garbage collection pressure and ensures that data stays contiguous in memory, which the CPU loves.
3. Solving False Sharing
By using Cache Line Padding, the Disruptor ensures that independent counters (like the head and tail of the queue) don't inhabit the same cache line, preventing unnecessary cache invalidations across CPU cores.
Build the Ledger: Case Study: Global Fintech Ledger Design
