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LMAX Disruptor & Conduit Framework

Overview

The LMAX Disruptor is a high-performance inter-thread messaging library that provides a simple yet powerful framework for exchanging data between threads. It is designed for low-latency, high-throughput scenarios where traditional queuing mechanisms introduce too much overhead.

The Conduit framework builds on top of the LMAX Disruptor to provide a reactive, event-driven architecture for building complex data processing pipelines.

What is the LMAX Disruptor?

The LMAX Disruptor is a library that enables very high performance concurrent programming. It was developed by LMAX Exchange, a financial trading platform that required extremely low-latency message passing between threads.

Key Features

  • Lock-free: Uses CAS (Compare-And-Swap) operations instead of locks
  • Ring Buffer: Pre-allocated circular buffer eliminates garbage collection overhead
  • Memory Barriers: Carefully controlled memory visibility without locks
  • Cache-friendly: Data structures designed to minimize cache line contention
  • Batching: Naturally supports batch processing of events

Core Concepts

Ring Buffer

A fixed-size circular buffer that holds references to events. It's pre-allocated at startup, which eliminates memory allocation during runtime.

flowchart LR
    S0["slot 0"] --> S1["slot 1"] --> S2["slot 2"] --> S3["slot 3"] --> S0
    Producer["Producer cursor<br/>(next slot to write)"] -.-> S1
    Consumer["Consumer cursor<br/>(next slot to read)"] -.-> S3

The buffer never grows or shrinks — producer and consumer cursors just keep advancing and wrapping back to slot 0 once they pass the end. See Hand-Rolled Ring Buffer for exactly how that wrap-around is made safe without locks.

Sequence Numbers

Used to track positions in the ring buffer. Producers claim sequence numbers before writing, and consumers track which events they've processed.

Wait Strategies

Different strategies for consumers waiting for new events:

  • BusySpinWaitStrategy: Lowest latency, highest CPU usage
  • YieldingWaitStrategy: Low latency with some CPU yield
  • SleepingWaitStrategy: Lower CPU usage, higher latency
  • BlockingWaitStrategy: Lowest CPU usage, highest latency

Why Use Disruptor?

Traditional Queue Problems

Traditional concurrent queues (like java.util.concurrent queues) suffer from:

  1. Lock Contention: Multiple threads competing for locks
  2. Cache Coherency: False sharing and cache line bouncing
  3. Memory Allocation: Creating/destroying objects causes GC pressure
  4. Context Switching: Blocking operations cause thread context switches

Disruptor Solutions

Problem Disruptor Solution
Lock Contention Lock-free algorithms using CAS
Cache Coherency Cache line padding to prevent false sharing
Memory Allocation Pre-allocated ring buffer
Context Switching Busy-spin wait strategies

Performance Characteristics

The Disruptor can process millions of events per second with nanosecond latencies on modern hardware.

Benchmark Comparison

Queue Throughput (ops/sec)
Disruptor ~25M
ArrayBlockingQueue ~5M
LinkedBlockingQueue ~3M

Illustrative, not measured on this project's hardware

These numbers are the kind of ratio commonly cited for the Disruptor vs. java.util.concurrent queues, not a benchmark run captured on a specific machine here. Treat them as "expect roughly this shape of difference," and benchmark on your own target hardware before relying on exact figures — see the real, captured numbers in Hand-Rolled Ring Buffer for an example of the latter.

Common Use Cases

  1. Financial Trading Systems: Ultra-low latency order processing
  2. Real-time Analytics: High-throughput data stream processing
  3. Event Sourcing: Recording domain events in order
  4. Log Aggregation: Collecting and processing log entries
  5. IoT Data Processing: Handling sensor data streams

Getting Started

To use the Disruptor in your project, add the dependency:

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<dependency>
    <groupId>com.lmax</groupId>
    <artifactId>disruptor</artifactId>
    <version>4.0.0</version>
</dependency>

Next Steps

Resources