Introduction
Working in the finance industry there is always a need to write software that can achieve low latency, high performance characteristics. The LMAX disruptor is a Java technology that has gained a lot of interest by developers in this field.
Pulsar is not a port of disruptor, rather it is an attempt to provide a native C++11 library that implements a lot of the concepts used by disruptor.
The goals for pulsar are as follows:
- Better performance than disruptor
- A simpler API than disruptor
Usage
Pulsar applications are implemented in terms of publishers and subscribers. A publisher can be subscribed to by 1 or more subscribers. For example
pulsar::publisher< long > p;
pulsar::subscriber< long >& s0 = p.subscribe();
pulsar::subscriber< long >& s1 = p.subscribe();
pulsar::subscriber< long >& s2 = p.subscribe();
In the example above there are 3 subscribers - each one will receive the data published by p. All subscribers operate in parallel - there are no guarantees about the order in which each subscriber will see the data. If p publishers item 1, s1 might see that data before s0 or s2.
It is also possible to chain subscribers together to create a pipeline processing arrangement. For example
pulsar::publisher< long > p;
pulsar::subscriber< long >& s0 = p.subscribe();
pulsar::subscriber< long >& s1 = s0.subscribe();
pulsar::subscriber< long >& s2 = s1.subscribe();
This example differs from the first as data is guaranteed to be processed in sequence. If p publishes item 1 it is guaranteed to be received by subscribers s0, s1 and s2 in that order.
To start receiving data on the subscriber side you supply a callable object. The subscriber will invoke the supplied callable everytime an item of data arrives. When you are done subscribing the callable should return false. Here is a simple example using a lambda. In this case subscribe would return after the first invocation of the lambda
s.subscribe( []( const long& e ) {
return false;
} );
The following code demonstrates how we might publish 100 data items.
for( size_t i=0; i<100; ) {
p.publish( 1, [&]( long& e ){
e = i++;
} );
}
The publish() method expects 2 arguments. Argument 1 is the number of data items we want to publish. Argument 2 is a callable object used to populate each data item. If will be called as many times as specified in argument 1.
Performance
The following table compares the performance of pulsar against
- LMAX disruptor 3.3.2 (jdk 8u31) https://github.com/LMAX-Exchange/disruptor
- disruptor-- (most popular C++ disruptor implementation on github) https://github.com/fsaintjacques/disruptor--
- A thread safe std queue implementation using condition variables for synchronization
The test case for each is to pass 100 billion items of data (longs) between 2 threads and measure the time taken to calculate the rate at which data is passed (operations per second)
All tests were executed on a Intel i5 4590 3.30GHz CPU
The source code for the pulsar test can be found here - https://github.com/mmcilroy/pulsar_cpp/blob/master/src/one_to_one_performance_test.cpp
| tech | ops/s |
|---|---|
| pulsar | 291,923,762 |
| disruptor java | 186,572,620 |
| disruptor-- | 7,328,783 |
| std queue | 8,244,023 |
Building