@imqueue/core
v1.15.0
Published
Simple JSON-based messaging queue for inter service communication
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I Message Queue (@imqueue/core)
Simple JSON-based messaging queue for inter service communication
Related packages:
- @imqueue/rpc - RPC-like client/service implementation over @imqueue/core.
- @imqueue/cli - Command Line Interface for imqueue.
Features
With current implementation on RedisQueue:
- Fast unwarranted message delivery (if consumer grab the message and dies message will be lost). Up to ~35-40k of 1Kb messages per second on i7 core by benchmarks.
- Fast warranted message delivery (only 1.5-2 times slower than unwarranted). If consumer grab a message and dies it will be re-scheduled in queue. Up to ~20-25K of 1Kb messages per second on i7 core by benchmarks.
- No timers or constant redis polling used for implementation, as result - no delays in delivery and low CPU usage on application workers. When idling it does not consume resources!
- Supports gzip compression for messages (decrease traffic usage, but slower).
- Concurrent workers model supported, the same queue can have multiple consumers.
- Delayed messages supported, fast as ~10K of 1Kb messages per second on i7 core by benchmarks.
- Safe predictable scaling of queues. Scaling number of workers does not influence traffic usage.
- Round-robin message balancing between several redis instances. This allows easy messaging queue redis horizontal scaling.
- TypeScript included!
Requirements
Currently this module have only one available adapter which is Redis server related. So redis-server > 3.8+ is required.
If config command is disabled on redis it will be required to turn on manually keyspace notification events (actual on use with ElasticCache on AWS), like:
notify-keyspace-events Ex
Further, more adapters will be added... if needed.
Install
npm i --save @imqueue/core
Usage
import IMQ, { IMessageQueue, IJson } from '@imqueue/core';
(async () => {
const queueOne: IMessageQueue = IMQ.create('QueueOne');
const queueTwo: IMessageQueue = IMQ.create('QueueTwo');
// start queues
await queueOne.start();
await queueTwo.start();
// handle queue messages
queueOne.on('message', (message: IJson, id: string, fromQueue: string) => {
console.log('queueOne message received:', message, id, fromQueue);
if (message.delay) {
queueOne.destroy();
queueTwo.destroy();
}
});
queueTwo.on('message', (message: IJson, id: string, fromQueue: string) => {
console.log('queueTwo message received:', message, id, fromQueue);
});
// sending queue messages
await queueOne.send('QueueTwo', { hello: 'two' });
await queueTwo.send('QueueOne', { hello: 'one' });
// sending delayed messages
const delay = 1000;
await queueOne.send('QueueOne', { delay }, delay);
})();
Benchmarking
First of all make sure redis-server is running on the localhost. Current version of benchmark supposed to have redis running localhost because it is going to measure it's CPU usage stats.
All workers during benchmark test will have their dedicated CPU affinity to make sure collected stats as accurate as possible.
git clone [email protected]:Mikhus/core.git
cd imq
node benchmark -c 4 -m 10000
Other possible benchmark options:
node benchmark -h
Options:
--version Show version number [boolean]
-h, --help Show help [boolean]
-c, --children Number of children test process to fork
-d, --delay Number of milliseconds to delay message delivery
for delayed messages. By default delayed
messages is of and this argument is equal to 0.
-m, --messages Number of messages to be sent by a child process
during test execution.
-z, --gzip Use gzip for message encoding/decoding.[boolean]
-s, --safe Use safe (guaranteed) message delivery
algorithm. [boolean]
-e, --example-message Path to a file containing JSON of example
message to use during the tests.
-p, --port Redis server port to connect to.
-t, --message-multiply-times Increase sample message data given number of
times.
Number of child workers running message queues are limited to a max number of CPU in the system -2. First one, which is CPU0 is reserved for OS tasks and for stats collector process. Second, which is CPU1 is dedicated to redis process running on a local machine, All others are safe to run queue workers.
For example, if there is 8 cores on a machine it is safe to run up to 6 workers. For 4-core machine this number is limited to 2. If there is less cores results will not give good visibility of load.
NOTE: paragraphs above this note are Linux-only related! On MacOS there is no good way to set process affinity to a CPU core, Windows support is not tested and is missing for the moment in benchmarking. I does not mean benchmark will not work on Mac & Win but the results won't be accurate and predictable.
Running Unit Tests
git clone [email protected]:imqueue/core.git
cd imq
npm test