Designed to allow running task in a queue with parallel support. Can be used for image or file loading.
Tiny queue data structure
fast, tiny `queueMicrotask` shim for modern engines
A shim for the setImmediate efficient script yielding API
Promise queue with concurrency control
queue-lit is a tiny queue data structure in case you `Array#push()` or `Array#shift()` on large arrays very often
The smallest and simplest JavaScript priority queue
A simple tool to keep requests to be executed in order.
Next tick shim that prefers process.nextTick over queueMicrotask for compat
LRU Queue
Promise-based queue
Simple JS queue with auto run for node and browsers
In memory queue system prioritizing tasks
A React component for managing loads with a load queue
The fastest javascript implementation of a double-ended queue. Used by the official Redis, MongoDB, MariaDB & MySQL libraries for Node.js and many other libraries. Maintains compatability with deque.
Designed to allow running task in a queue with parallel support. Can be used for image or file loading.
Simple JS queue with auto run for node and browsers
Sequential asynchronous lock-based queue for promises
Fast, in memory work queue
asynchronous function queue with adjustable concurrency
Priority queue data structures
A promise based, dynamic priority queue runner, with concurrency limiting.
Microsoft Azure Storage SDK for JavaScript - Queue
Extremely fast double-ended queue implementation
Queueing software load balancer.
Queueing software load balancer.
Hansel is a pure ruby driver for httperf for automated load and performance testing. It will load a job queue file, in a yaml format, run httperf with each job.
An industrial-strength background worker system for rails using RabbitMQ.
Puma plugin which should be able to handle all your metric needs regarding your webserver: - ability to publish basic puma statistics (like queue backlog) to both logs and datadog - ability to add custom target whenever you need it - ability to monitor puma socket listen queue (!) - ability to report requests queue time via custom rack middleware - the time request spent between being accepted by Load Balancer and start of its processing by Puma worker
# EventReporter EventReporter is a CSV parser and sorter. you can load a CSV and then search it. ## Installation $ gem install the_only_event_reporter_ever $ gem list event_reporter -d ## Usage After installation run: $ event_reporter Then Type 'load <filename>' to load records from a CSV $ Load event_attendees.csv Try these commands $ Find first_name sarah $Queue Print $Queue Save to <filename> ### Saving the queue accepts extensions JSON, XML, TXT, CSV. ## Contributing 1. Fork it 2. Create your feature branch (`git checkout -b my-new-feature`) 3. Commit your changes (`git commit -am 'Add some feature'`) 4. Push to the branch (`git push origin my-new-feature`) 5. Create new Pull Request
NOTE: This is a fork of puma-plugin-telemetry, modified to: - Support Puma 7 - Add LogTarget, with custom formatter: and transform: options - Warn about socket telemetry on unsupported platforms Puma plugin which should be able to handle all your metric needs regarding your webserver: - ability to publish basic puma statistics (like queue backlog) to both logs and datadog - ability to add custom target whenever you need it - ability to monitor puma socket listen queue (!) - ability to report requests queue time via custom rack middleware - the time request spent between being accepted by Load Balancer and start of its processing by Puma worker
`qless` is meant to be a performant alternative to other queueing systems, with statistics collection, a browser interface, and strong guarantees about job losses. It's written as a collection of Lua scipts that are loaded into the Redis instance to be used, and then executed by the client library. As such, it's intended to be extremely easy to port to other languages, without sacrificing performance and not requiring a lot of logic replication between clients. Keep the Lua scripts updated, and your language-specific extension will also remain up to date.
# Sparrow is a really fast lightweight queue written in Ruby that speaks memcached. # That means you can use Sparrow with any memcached client library (Ruby or otherwise). # # Basic tests shows that Sparrow processes messages at a rate of 850-900 per second. # The load Sparrow can cope with increases exponentially as you add to the cluster. # Sparrow also takes advantage of eventmachine, which uses a non-blocking io, offering great performance. # # Sparrow is a in-memory queue but will persist the data to disk when receiving a term signal. # # Sparrow comes with built in support for daemonization and clustering. # Also included are example libraries and clients. For example: # # require 'memcache' # m = MemCache.new('127.0.0.1:11212') # m['queue_name'] = '1' # Publish to queue # m['queue_name'] #=> 1 Pull next msg from queue # m['queue_name'] #=> nil # m.delete('queue_name) # Delete queue # # # or using the included client: # # class MyQueue < MQ3::Queue # def on_message # logger.info "Received msg with args: #{args.inspect}" # end # end # # MyQueue.servers = [ # MQ3::Protocols::Memcache.new({:host => '127.0.0.1', :port => 11212, :weight => 1}) # ] # MyQueue.publish('test msg') # MyQueue.run # # Messages are deleted as soon as they're read and the order you add messages to the queue probably won't # be the same order when they're removed. # # Additional memcached commands that are supported are: # flush_all # Deletes all queues # version # quit # The memcached commands 'add', and 'replace' just call 'set'. # # Call sparrow with --help for usage options # # The daemonization won't work on Windows. # # Check out the code: # svn checkout http://sparrow.googlecode.com/svn/trunk/ sparrow # # Sparrow was inspired by Twitter's Starling
Compatible with Resque 1.x. Use Resque.push if you are using >= 2.x. Resque is great. So is job processing with redis. Our biggest drawback has been that resque requires the class that will be processing a job to be loaded when the job is enqueued. But what happens when the implementing job is defined in a separate application and isn't currently loaded into memory? Enter Resque Remote. Resque Remote's simple goal is to allow you to add a job to a queue with a string identifier for the class rather than the class constant. It is assumed that the worker-side of the equation _will_ have the class in memory and hence will be able to run it no problem. Feedback, comments and questions are welcome at bj [dot] neilsen [at] gmail [dot] com.
`reqless` is meant to be a performant alternative to other queueing systems, with statistics collection, a browser interface, and strong guarantees about job losses. It's written as a collection of Lua scipts that are loaded into the Redis instance to be used, and then executed by the client library. As such, it's intended to be extremely easy to port to other languages, without sacrificing performance and not requiring a lot of logic replication between clients. Keep the Lua scripts updated, and your language-specific extension will also remain up to date.
== DESCRIPTION: The RightScale AWS gems have been designed to provide a robust, fast, and secure interface to Amazon EC2, EBS, S3, SQS, SDB, and CloudFront. These gems have been used in production by RightScale since late 2006 and are being maintained to track enhancements made by Amazon. The RightScale AWS gems comprise: - RightAws::Ec2 -- interface to Amazon EC2 (Elastic Compute Cloud), VPC (Virtual Private Cloud) and the associated EBS (Elastic Block Store) - RightAws::S3 and RightAws::S3Interface -- interface to Amazon S3 (Simple Storage Service) - RightAws::Sqs and RightAws::SqsInterface -- interface to first-generation Amazon SQS (Simple Queue Service) - RightAws::SqsGen2 and RightAws::SqsGen2Interface -- interface to second-generation Amazon SQS (Simple Queue Service) - RightAws::SdbInterface and RightAws::ActiveSdb -- interface to Amazon SDB (SimpleDB) - RightAws::AcfInterface -- interface to Amazon CloudFront, a content distribution service - RightAws::AsInterface -- interface to Amazon Auto Scaling - RightAws::AcwInterface -- interface to Amazon Cloud Watch - RightAws::ElbInterface -- interface to Amazon Elastic Load Balancer - RightAws::RdsInterface -- interface to Amazon RDS instances == FEATURES:
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