Disruptor can be used in those situation, so I think LMAX-Exchange . isolates the execution semantics of a computer architecture from the. Our revolutionary and minimalist approach to technology, architecture and technology-related processes are a careful blend of in-house intellectual property and. Martin Fowler has written a great article about the architecture we developed for our exchange LMAX. The article explains the origins of the.


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LMAX's in-memory structures are persistent across input events, so if there is an error it's important to not leave that memory in lmax architecture inconsistent state.


However there's no automated rollback facility. As a consequence the LMAX team puts a lot of attention into ensuring the input events are fully valid before doing any mutation of the in-memory persistent state. They have found that testing is a key tool lmax architecture flushing out lmax architecture kinds of problems before going into production.

Input and Output Disruptors Although the business logic occurs in a single thread, there are a number tasks to be done before we can invoke a business object method. The original input for processing comes off the wire in the form of a message, this message needs to be unmarshaled into a form convenient for Business Logic Processor lmax architecture use.

Event Sourcing relies on keeping a durable journal of all the input events, so each input message needs to be journaled onto a durable store.

The LMAX Architecture

Finally the architecture lmax architecture on a cluster of Business Logic Processors, so we have to replicate the input messages across this cluster. Similarly on the output side, the output events need to be marshaled for transmission over the network.

The activities done by the input disruptor using UML activity diagram notation The replicator and journaler involve IO and therefore are relatively slow.

Also these lmax architecture tasks are relatively independent, all of them need to be done before the Business Logic Processor works on a message, but they can done in any order. So unlike with the Business Logic Processor, where each trade changes the market for subsequent trades, there is a natural fit for concurrency.

To handle this concurrency the LMAX team developed a special concurrency component, which they call a Disruptor [11].

At a crude level you lmax architecture think of a Disruptor as lmax architecture multicast graph of queues where producers put objects on it that are sent to all the consumers for parallel consumption through separate downstream queues.

When you look inside you see that this network of queues is really a single data structure - a ring buffer. Each producer and consumer has a sequence counter to lmax architecture which slot in the buffer it's currently working on.


This way the producer can read the consumers' lmax architecture to ensure the slot it wants lmax architecture write in is available without any locks on the counters.

Similarly a consumer can ensure it only processes messages once another consumer is done with it by watching the counters.

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The input disruptor coordinates one producer lmax architecture four consumers Output disruptors are similar but they only have two sequential consumers for marshaling and output. Each topic has its own disruptor.

The LMAX Architecture

The disruptors I've described are used in a style with one producer and multiple consumers, but this isn't a limitation of the design of the disruptor. The disruptor can work with multiple producers too, in this case it still doesn't need locks.

If the unmarshaler has a problem when processing on slot 15 and returns when the receiver is on slot 31, it can read data from slots in one batch to catch up. This batch read of the data from the disruptor makes it easier lmax architecture lagging consumers to catch up quickly, thus reducing overall latency.

I've described things here, with lmax architecture each of the journaler, replicator, and unmarshaler - this indeed is what LMAX does. But the design would allow multiple of these components to run. If you ran two journalers then one would take the even slots and the other journaler would take the odd slots.


This allows further concurrency of these IO operations should this become necessary.