Welcome!

Microservices Expo Authors: Pat Romanski, Liz McMillan, Elizabeth White, Dana Gardner, Christopher Keene

Related Topics: Java IoT, Industrial IoT, Microservices Expo, Eclipse, IoT User Interface, Apache

Java IoT: Article

The Disruptor Framework: A Concurrency Framework for Java

Rediscovering the Producer-Consumer Model with the Disruptor

Let's start with the basic question: What is the disruptor? The disruptor is a concurrency framework for Java that allows data sharing between threads. The age old way of coding a producer-consumer model is to use a queue as the buffer area between the producer and the consumer, where the producer adds data objects to the queue, which are in turn processed by the consumer. However, such a model does not work well at the hardware level and ends up being highly inefficient. The disruptor in its simplest form replaces the queue with a data structure known as the ‘ring buffer'. Which brings us to the next question, what is the ring buffer? The ring buffer is an array of fixed length (which must be a power of 2), it's circular and wraps. This data structure is at the core of what makes the disruptor super fast.

Let's explore a simple everyday scenario in enterprise architectures. A producer (let's call it the publisher) creates data and stores it in the queue. Two immediate consumers (let's call them fooHandler and barHandler) consume the data and make updates to it. Once these 2 processors are done with a piece of data, it is then passed on to a third consumer (let's call it fooBarHandler) for further processing. In a concurrent processing system using legacy techniques, coding this architecture would involve a crisscross of queues and numerous concurrency challenges, such as dealing with locks, CAS, write contention, etc. The disruptor on the other hand immensely simplifies such a scenario by providing a simple API for creating the producer, consumers and ring buffer, which in turn relieve the developer of all concerns surrounding handling concurrency and doing so in an efficient manner. We shall now explore how the disruptor works its magic and provides a reliable messaging framework.

Writing to the ring buffer

Looking at the figure above, we find ourselves in the middle of the action. The ring buffer is an array of length 4 and is populated with data items - 4,5,6 and 7, which in the case of the disruptor are known as events. The square above the ring buffer containing the number 7 is the current sequence number, which denotes the highest populated event in the ring buffer. The ring buffer keeps track of this sequence number and increments it as and when new events are published to it. The fooHandler, barHandler and fooBarHandler are the consumers, which in disruptor terminology are called ‘event processors'. Each of these also has a square containing a sequence number, which in the case of the event processors denotes the highest event that they have consumed/processed so far. Thus its apparent that each entity (except the publisher) tracks its own sequence number and thus does not need to rely on a third party to figure out which is the next event its after.

The publisher asks the ring buffer for the next sequence number. The ring buffer is currently at 7, so the next sequence number would be 8. However, this would also entail overwriting the event with sequence number 4 (since there are only 4 slots in the array and the oldest event gets replaced with the newest one). The ring buffer first checks the most downstream consumer (fooBarHandler) to determine whether it is done processing the event with sequence number 4. In this case, it has, so it returns the number 8 to the publisher. In case fooBarHandler was stuck at a sequence number lower than 4, the ring buffer would have waited for it to finish processing the 4th event before returning the next sequence number to the publisher. This sequence number helps the publisher identify the next available slot in the ring buffer by performing a simple mod operation. indexOfNextAvailableSlot = highestSeqNo%longthOfRingBuffer, which in this case is 0 (8%4). The publisher then claims the next slot in the ring buffer (via a customizable strategy depending on whether there is a single or multiple publishers), which is currently occupied by event 4, and publishes event 8 to it.

Reading from the ring buffer by immediate consumers

The figure above shows the state of operations after the publisher has published event 8 to the ring buffer. The ring buffer's sequence number has been updated to 8 and now contains events 5,6,7 and 8. We see that foohandler, which has processed events upto 7, has been waiting (using a customizable strategy) for the 8th event to be published. Unlike the publisher though, it does not directly communicate with the ring buffer, but uses an entity known as the ‘sequence barrier' to do so on its behalf. The sequence barrier let's fooHandler know that the highest sequence number available in the ring buffer is now 8. FooHandler may now get this event and process it.

Similarly, barHandler checks the sequence barrier to determine whether there are any more events it can process. However, rather than just telling barHandler that the next (6th) event is up for grabs, the sequence barrier returns the highest sequence number present in the ring buffer to barHandler too. This way, barHandler can grab events 6,7,8 and process them in a batch before it has to enquire about further events being published. This saves time and reduces load.

Another important thing to note here is that in the case of multiple event processors, any given field in the event object must only be written to by any one event processor. Doing so prevents write contention, and thus removes the need for locks or CAS.

Reading from the ring buffer by downstream consumers

A few moments after the set of immediate consumers grab the next set of data, the state of affairs looks like the figure above. fooHandler is done processing all 8 available events (and has accordingly updated its sequence number to 8), whereas barHandler, being the slow coach that it is, has only processed events upto number 6 (and thus has updated sequence number to 6). We now see that fooBarHandler, which was done processing events upto number 5 at the start of our examination, is still waiting for an event higher than that to process. Why did its sequence barrier not inform it once event 8 was published to the ring buffer? Well, that is because downstream consumers don't automatically get notified of the highest sequence number present in the ring buffer. Their sequence barriers on the other hand determine the next sequence number they can process by calculating the minimum sequence number that the set of event processors directly before them have processed. This helps ensure that the downstream consumers only act on an event once its processing has been completed by the entire set of upstream consumers. The sequence barrier examines the sequence number on fooHandler (which is 8) and the sequence number on barHandler (which is 6) and decides that event 6 is the highest event that fooBarHandler can process. It returns this info to fooBarHandler, which then grabs event 6 and processes it. It must be noted that even in the case of the downstream consumers, they grab the events directly from the ring buffer and not from the consumers before them.

Well, that is about all you would need to know about the working of the disruptor framework to get started. But while this is all well and good in theory, the question still remains, how would one code the above architecture using the disruptor library? The answer to that question lies below.

Coding the disruptor

public final class FooBarEvent {
private double foo=0;
private double bar=0;
public double getFoo(){
return foo;
}
public double getBar() {
return bar;
}
public void setFoo(final double foo) {
this.foo = foo;
}
public void setBar(final double bar) {
this.bar = bar;
}
public final static EventFactory<FooBarEvent> EVENT_FACTORY
= new EventFactory<FooBarEvent>() {
public FooBarEvent newInstance() {
return new FooBarEvent();
}
};
}

The class FooBarEvent, as the name suggests, acts as the event object which is published by the publisher to the ring buffer and consumed by the eventProcessors - fooHandler, barHandler and fooBarHandler. It contains two fields ‘foo' and ‘bar' of type double, along with their corresponding setters/getters. It also contains an entity ‘EVENT_FACTORY' of type EventFactory, which is used to create an instance of this event.

public class FooBarDisruptor {           
public static final int RING_SIZE=4;
public static final ExecutorService EXECUTOR
=Executors.newCachedThreadPool();

final EventTranslator<FooBarEvent> eventTranslator
=new EventTranslator<FooBarEvent>() {
public void translateTo(FooBarEvent event,
long sequence) {
double foo=event.getFoo();
double bar=event.getBar();
system.out.println("foo="+foo
+", bar="+bar
+" (sequence="+sequence+")");
}
};

final EventHandler<FooBarEvent> fooHandler
= new EventHandler<FooBarEvent>() {
public void onEvent(final FooBarEvent event,
final long sequence,
final boolean endOfBatch)
throws Exception {
double foo=Math.random();
event.setFoo(foo);
System.out.println("setting foo to "+foo
+" (sequence="+sequence+")");
}
};

final EventHandler<FooBarEvent> barHandler
= new EventHandler<FooBarEvent>() {
public void onEvent(final FooBarEvent event,
final long sequence,
final boolean endOfBatch)
throws Exception {
double bar=Math.random();
event.setBar(bar);
System.out.println("setting bar to "+bar
+" (sequence="+sequence+")");
}
};

final EventHandler<FooBarEvent> fooBarHandler
= new EventHandler<FooBarEvent>() {
public void onEvent(final FooBarEvent event,
final long sequence,
final boolean endOfBatch)
throws Exception {
double foo=event.getFoo();
double bar=event.getBar();
System.out.println("foo="+foo
+", bar="+bar
+" (sequence="+sequence+")");
}
};

public Disruptor setup() {
Disruptor<FooBarEvent> disruptor =
new Disruptor<FooBarEvent>(FooBarEvent.EVENT_FACTORY,
EXECUTOR,
new SingleThreadedClaimStrategy(RING_SIZE),
new SleepingWaitStrategy());
disruptor.handleEventsWith(fooHandler, barHandler).then(fooBarHandler);
RingBuffer<FooBarEvent> ringBuffer = disruptor.start();             
return disruptor;
}

public void publish(Disruptor<FooBarEvent> disruptor) {
for(int i=0;i<1000;i++) {
disruptor.publishEvent(eventTranslator);
}
}

public static void main(String[] args) {
FooBarDisruptor fooBarDisruptor=new FooBarDisruptor();
Disruptor disruptor=fooBarDisruptor.setup();
fooBarDisruptor.publish(disruptor);
}
}

The class FooBarDisruptor is where all the action happens. The ‘eventTranslator' is an entity which aids the publisher in publishing events to the ring buffer. It implements a method ‘translateTo' which gets invoked when the publisher is granted permission to publish the next event. fooHandler, barHandler and fooBarHandler are the event processors, and are objects of type ‘EventHandler'. Each of them implements a method ‘onEvent' which gets invoked once the event processor is granted access to a new event. The method ‘setup' is responsible for creating the disruptor, assigning the corresponding event handlers, and setting the dependency rules amongst them. The method ‘publish' is responsible for publishing a thousand events of the type ‘FooBarEvent' to the ring buffer.

In order to get the above code to work, you must download the disruptor jar file from http://code.google.com/p/disruptor/downloads/list and include the same in your classpath.

Conclusion
The disruptor is currently in use in the ultra efficient LMAX architecture, where it has proven to be a reliable model for inter thread communication and data sharing, reducing the end to end latency to a fraction of what queue based architectures provided. It does so using a variety of techniques, including replacing the array blocking queue with a ring buffer, getting rid of all locks, write contention and CAS operations (except in the scenario where one has multiple publishers), having each entity track its own progress by way of a sequence number, etc. Adopting this framework can greatly boost a developer's productivity in terms of coding a producer-consumer pattern, while at the same time aid in creating an end product far superior in terms of both design and performance to the legacy queue based architectures.

More Stories By Sanat Vij

Sanat Vij is a professional software engineer currently working at CenturyLink. He has vast experience in developing high availability applications, configuring application servers, JVM profiling and memory management. He specializes in performance tuning of applications, reducing response times, and increasing stability.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@MicroservicesExpo Stories
DevOps at Cloud Expo, taking place Nov 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 19th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long dev...
19th Cloud Expo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy. Meanwhile, 94% of enterpri...
Using new techniques of information modeling, indexing, and processing, new cloud-based systems can support cloud-based workloads previously not possible for high-throughput insurance, banking, and case-based applications. In his session at 18th Cloud Expo, John Newton, CTO, Founder and Chairman of Alfresco, described how to scale cloud-based content management repositories to store, manage, and retrieve billions of documents and related information with fast and linear scalability. He addres...
Akana has announced the availability of version 8 of its API Management solution. The Akana Platform provides an end-to-end API Management solution for designing, implementing, securing, managing, monitoring, and publishing APIs. It is available as a SaaS platform, on-premises, and as a hybrid deployment. Version 8 introduces a lot of new functionality, all aimed at offering customers the richest API Management capabilities in a way that is easier than ever for API and app developers to use.
The burgeoning trends around DevOps are translating into new types of IT infrastructure that both developers and operators can take advantage of. The next BriefingsDirect Voice of the Customer thought leadership discussion focuses on the burgeoning trends around DevOps and how that’s translating into new types of IT infrastructure that both developers and operators can take advantage of.
With so much going on in this space you could be forgiven for thinking you were always working with yesterday’s technologies. So much change, so quickly. What do you do if you have to build a solution from the ground up that is expected to live in the field for at least 5-10 years? This is the challenge we faced when we looked to refresh our existing 10-year-old custom hardware stack to measure the fullness of trash cans and compactors.
SYS-CON Events announced today that Isomorphic Software will exhibit at DevOps Summit at 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Isomorphic Software provides the SmartClient HTML5/AJAX platform, the most advanced technology for building rich, cutting-edge enterprise web applications for desktop and mobile. SmartClient combines the productivity and performance of traditional desktop software with the simp...
The emerging Internet of Everything creates tremendous new opportunities for customer engagement and business model innovation. However, enterprises must overcome a number of critical challenges to bring these new solutions to market. In his session at @ThingsExpo, Michael Martin, CTO/CIO at nfrastructure, outlined these key challenges and recommended approaches for overcoming them to achieve speed and agility in the design, development and implementation of Internet of Everything solutions wi...
Internet of @ThingsExpo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 19th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago. All major researchers estimate there will be tens of billions devices - comp...
Internet of @ThingsExpo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with the 19th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world and ThingsExpo Silicon Valley Call for Papers is now open.
To leverage Continuous Delivery, enterprises must consider impacts that span functional silos, as well as applications that touch older, slower moving components. Managing the many dependencies can cause slowdowns. See how to achieve continuous delivery in the enterprise.
Thomas Bitman of Gartner wrote a blog post last year about why OpenStack projects fail. In that article, he outlined three particular metrics which together cause 60% of OpenStack projects to fall short of expectations: Wrong people (31% of failures): a successful cloud needs commitment both from the operations team as well as from "anchor" tenants. Wrong processes (19% of failures): a successful cloud automates across silos in the software development lifecycle, not just within silos.
There's a lot of things we do to improve the performance of web and mobile applications. We use caching. We use compression. We offload security (SSL and TLS) to a proxy with greater compute capacity. We apply image optimization and minification to content. We do all that because performance is king. Failure to perform can be, for many businesses, equivalent to an outage with increased abandonment rates and angry customers taking to the Internet to express their extreme displeasure.
The 19th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Digital Transformation, Microservices and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportuni...
Right off the bat, Newman advises that we should "think of microservices as a specific approach for SOA in the same way that XP or Scrum are specific approaches for Agile Software development". These analogies are very interesting because my expectation was that microservices is a pattern. So I might infer that microservices is a set of process techniques as opposed to an architectural approach. Yet in the book, Newman clearly includes some elements of concept model and architecture as well as p...
SYS-CON Events announced today that eCube Systems, a leading provider of middleware modernization, integration, and management solutions, will exhibit at @DevOpsSummit at 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. eCube Systems offers a family of middleware evolution products and services that maximize return on technology investment by leveraging existing technical equity to meet evolving business needs. ...
A company’s collection of online systems is like a delicate ecosystem – all components must integrate with and complement each other, and one single malfunction in any of them can bring the entire system to a screeching halt. That’s why, when monitoring and analyzing the health of your online systems, you need a broad arsenal of different tools for your different needs. In addition to a wide-angle lens that provides a snapshot of the overall health of your system, you must also have precise, ...
The following fictional case study is a composite of actual horror stories I’ve heard over the years. Unfortunately, this scenario often occurs when in-house integration teams take on the complexities of DevOps and ALM integration with an enterprise service bus (ESB) or custom integration. It is written from the perspective of an enterprise architect tasked with leading an organization’s effort to adopt Agile to become more competitive. The company has turned to Scaled Agile Framework (SAFe) as ...
As the world moves toward more DevOps and Microservices, application deployment to the cloud ought to become a lot simpler. The Microservices architecture, which is the basis of many new age distributed systems such as OpenStack, NetFlix and so on, is at the heart of Cloud Foundry - a complete developer-oriented Platform as a Service (PaaS) that is IaaS agnostic and supports vCloud, OpenStack and AWS. Serverless computing is revolutionizing computing. In his session at 19th Cloud Expo, Raghav...
Cloud Expo 2016 New York at the Javits Center New York was characterized by increased attendance and a new focus on operations. These were both encouraging signs for all involved in Cloud Computing and all that it touches. As Conference Chair, I work with the Cloud Expo team to structure three keynotes, numerous general sessions, and more than 150 breakout sessions along 10 tracks. Our job is to balance the state of enterprise IT today with the trends that will be commonplace tomorrow. Mobile...