Results for queue-just

A thread-safe SQS- and S3-backed queue.

A Resque plugin which allows you to create dedicated queues for jobs that use rate limited apis. These queues will pause when one of the jobs hits a rate limit, and unpause after a suitable time period. The rate_limited_queue can be used directly, and just requires catching the rate limit exception and pausing the queue. There are also additional queues provided that already include the pause/rety logic for twitter, angelist and evernote; these allow you to support rate limited apis with minimal changes.

A Resque plugin which allows you to create dedicated queues for jobs that use rate-limited APIs. These queues will pause when one of the jobs hits a rate limit, and unpause after a suitable time period. The rate-limited queue can be used directly, and just requires catching the rate limit exception and pausing the queue. There are also additional queues provided that already include the pause/retry logic for Twitter, AngelList and Evernote; these allow you to support rate-limited APIs with minimal changes.

Resque can be very useful outside of a web app, too. What if you want to write jobs in Ruby and just enqueue them from your console? Or from a Java application? Or in cron jobs? Cavalcade to the resque! Cavalcade creates a resque-based, stand-alone job queue, and provides rake tasks to enqueue all of your jobs.

Because Solr sometimes fails, it happens. It might be a maintenance work you have to do or just Out-Of-Memory problems. If you are running search-sensitive Rails app, you have to deal with it.This gem was developed to postpone your index tasks automatically into a sidekiq queue if Solr engine becomes unavailable

# 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

Flamingo makes it easy to wade through the Twitter Streaming API by handling all connectivity and resource management for you. You just tell it what to track and consume the information in a resque queue. Flamingo isn't a traditional ruby gem. You don't require it into your code. Instead, it's designed to run as a daemon like redis or mysql. It provides a REST interface to change the parameters sent to the Twitter Streaming resource. All events from the streaming API are placed on a resque job queue where your application can process them. CAVEAT EMPTOR: This gem is alpha code so act accordingly.

= DESCRIPTION: Provides a Chef handler which can report run status, including any changes that were made, to a rabbit server. In the case of failed runs a backtrace will be included in the details reported. Based on the Graylog Gelf handler by Jon Wood (<jon@blankpad.net>) https://github.com/jellybob/chef-gelf = REQUIREMENTS: * A Rabbit server running somewhere. = USAGE: This example makes of the chef_handler cookbook, place some thing like this in cookbooks/chef_handler/recipes/rabbit.rb and add it to your run list. include_recipe "chef_handler::default" gem_package "chef-rabbit" do action :nothing end.run_action(:install) # Make sure the newly installed Gem is loaded. Gem.clear_paths require 'chef/rabbit' chef_handler "Chef::RABBIT::Handler" do source "chef/rabbit" arguments({ :connection => { :host => "your_rabbit_server", :user => "rabbit_user", :pass => "rabbit_pass", :vhost => "/stuff" } :queue => { :name => "some_queue", :params => { :durable => true, ... } }, :exchange => { :name => "some_exchange", :params => { :durable => true, ... } }, :timestamp_tag => "@timestamp" }) supports :exception => true, :report => true end.run_action(:enable) Arguments take the form of an options hash, with the following options: * :connection - http://rubybunny.info/articles/connecting.html * :queue - rabbit queue info to use. name is set to "chef-client" + durable = true by default * :exchange - rabbit exchange to use .default_exchange + durable = true by default * :timestamp_tag - tag for timestamp "timestamp" by default * :blacklist ({}) - A hash of cookbooks, resources and actions to ignore in the change list. = BLACKLISTING: Some resources report themselves as having updated on every run even if nothing changed, or are just things you don't care about. To reduce the amount of noise in your logs these can be ignored by providing a blacklist. In this example we don't want to be told about the GELF handler being activated: chef_handler "Chef::RABBIT::Handler" do source "chef/rabbit" arguments({ :blacklist => { "chef_handler" => { "chef_handler" => [ "nothing", "enable" ] } } }) supports :exception => true, :report => true end.run_action(:enable) = LICENSE and AUTHOR: Copyright 2014 by MTN Satellite Communications Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

ALPHA Alert -- just uploaded initial release. Linux inotify is a means to receive events describing file system activity (create, modify, delete, close, etc). Sinotify was derived from aredridel's package (http://raa.ruby-lang.org/project/ruby-inotify/), with the addition of Paul Boon's tweak for making the event_check thread more polite (see http://www.mindbucket.com/2009/02/24/ruby-daemons-verifying-good-behavior/) In sinotify, the classes Sinotify::PrimNotifier and Sinotify::PrimEvent provide a low level wrapper to inotify, with the ability to establish 'watches' and then listen for inotify events using one of inotify's synchronous event loops, and providing access to the events' masks (see 'man inotify' for details). Sinotify::PrimEvent class adds a little semantic sugar to the event in to the form of 'etypes', which are just ruby symbols that describe the event mask. If the event has a raw mask of (DELETE_SELF & IS_DIR), then the etypes array would be [:delete_self, :is_dir]. In addition to the 'straight' wrapper in inotify, sinotify provides an asynchronous implementation of the 'observer pattern' for notification. In other words, Sinotify::Notifier listens in the background for inotify events, adapting them into instances of Sinotify::Event as they come in and immediately placing them in a concurrent queue, from which they are 'announced' to 'subscribers' of the event. [Sinotify uses the 'cosell' implementation of the Announcements event notification framework, hence the terminology 'subscribe' and 'announce' rather then 'listen' and 'trigger' used in the standard event observer pattern. See the 'cosell' package on github for details.] A variety of 'knobs' are provided for controlling the behavior of the notifier: whether a watch should apply to a single directory or should recurse into subdirectores, how fast it should broadcast queued events, etc (see Sinotify::Notifier, and the example in the synopsis section below). An event 'spy' can also be setup to log all Sinotify::PrimEvents and Sinotify::Events. Sinotify::Event simplifies inotify's muddled event model, sending events only for those files/directories that have changed. That's not to say you can't setup a notifier that recurses into subdirectories, just that any individual event will apply to a single file, and not to its children. Also, event types are identified using words (in the form of ruby :symbols) instead of inotify's event masks. See Sinotify::Event for more explanation. The README for inotify: http://www.kernel.org/pub/linux/kernel/people/rml/inotify/README Selected quotes from the README for inotify: * "Rumor is that the 'd' in 'dnotify' does not stand for 'directory' but for 'suck.'" * "The 'i' in inotify does not stand for 'suck' but for 'inode' -- the logical choice since inotify is inode-based." (The 's' in 'sinotify' does in fact stand for 'suck.')

ALPHA Alert -- just uploaded initial release. Linux inotify is a means to receive events describing file system activity (create, modify, delete, close, etc). Sinotify was derived from aredridel's package (http://raa.ruby-lang.org/project/ruby-inotify/), with the addition of Paul Boon's tweak for making the event_check thread more polite (see http://www.mindbucket.com/2009/02/24/ruby-daemons-verifying-good-behavior/) In sinotify, the classes Sinotify::PrimNotifier and Sinotify::PrimEvent provide a low level wrapper to inotify, with the ability to establish 'watches' and then listen for inotify events using one of inotify's synchronous event loops, and providing access to the events' masks (see 'man inotify' for details). Sinotify::PrimEvent class adds a little semantic sugar to the event in to the form of 'etypes', which are just ruby symbols that describe the event mask. If the event has a raw mask of (DELETE_SELF & IS_DIR), then the etypes array would be [:delete_self, :is_dir]. In addition to the 'straight' wrapper in inotify, sinotify provides an asynchronous implementation of the 'observer pattern' for notification. In other words, Sinotify::Notifier listens in the background for inotify events, adapting them into instances of Sinotify::Event as they come in and immediately placing them in a concurrent queue, from which they are 'announced' to 'subscribers' of the event. [Sinotify uses the 'cosell' implementation of the Announcements event notification framework, hence the terminology 'subscribe' and 'announce' rather then 'listen' and 'trigger' used in the standard event observer pattern. See the 'cosell' package on github for details.] A variety of 'knobs' are provided for controlling the behavior of the notifier: whether a watch should apply to a single directory or should recurse into subdirectores, how fast it should broadcast queued events, etc (see Sinotify::Notifier, and the example in the synopsis section below). An event 'spy' can also be setup to log all Sinotify::PrimEvents and Sinotify::Events. Sinotify::Event simplifies inotify's muddled event model, sending events only for those files/directories that have changed. That's not to say you can't setup a notifier that recurses into subdirectories, just that any individual event will apply to a single file, and not to its children. Also, event types are identified using words (in the form of ruby :symbols) instead of inotify's event masks. See Sinotify::Event for more explanation. The README for inotify: http://www.kernel.org/pub/linux/kernel/people/rml/inotify/README Selected quotes from the README for inotify: * "Rumor is that the 'd' in 'dnotify' does not stand for 'directory' but for 'suck.'" * "The 'i' in inotify does not stand for 'suck' but for 'inode' -- the logical choice since inotify is inode-based." (The 's' in 'sinotify' does in fact stand for 'suck.')

Log2json lets you read, filter and send logs as JSON objects via Unix pipes. It is inspired by Logstash, and is meant to be compatible with it at the JSON event/record level so that it can easily work with Kibana. Reading logs is done via a shell script(eg, `tail`) running in its own process. You then configure(see the `syslog2json` or the `nginxlog2json` script for examples) and run your filters in Ruby using the `Log2Json` module and its contained helper classes. `Log2Json` reads from stdin the logs(one log record per line), parses the log lines into JSON records, and then serializes and writes the records to stdout, which then can be piped to another process for processing or sending it to somewhere else. Currently, Log2json ships with a `tail-log` script that can be run as the input process. It's the same as using the Linux `tail` utility with the `-v -F` options except that it also tracks the positions(as the numbers of lines read from the beginning of the files) in a few files in the file system so that if the input process is interrupted, it can continue reading from where it left off next time if the files had been followed. This feature is similar to the sincedb feature in Logstash's file input. Note: If you don't need the tracking feature(ie, you are fine with always tailling from the end of file with `-v -F -n0`), then you can just use the `tail` utility that comes with your Linux distribution.(Or more specifically, the `tail` from the GNU coreutils). Other versions of the `tail` utility may also work, but are not tested. The input protocol expected by Log2json is very simple and documented in the source code. ** The `tail-log` script uses a patched version of `tail` from the GNU coreutils package. A binary of the `tail` utility compiled for Ubuntu 12.04 LTS is included with the Log2json gem. If the binary doesn't work for your distribution, then you'll need to get GNU coreutils-8.13, apply the patch(it can be found in the src/ directory of the installed gem), and then replace the bin/tail binary in the directory of the installed gem with your version of the binary. ** P.S. If you know of a way to configure and compile ONLY the tail program in coreutils, please let me know! The reason I'm not building tail post gem installation is that it takes too long to configure && make because that actually builds every utilties in coreutils. For shipping logs to Redis, there's the `lines2redis` script that can be used as the output process in the pipe. For shipping logs from Redis to ElasticSearch, Log2json provides a `redis2es` script. Finally here's an example of Log2json in action: From a client machine: tail-log /var/log/{sys,mail}log /var/log/{kern,auth}.log | syslog2json | queue=jsonlogs \ flush_size=20 \ flush_interval=30 \ lines2redis host.to.redis.server 6379 0 # use redis DB 0 On the Redis server: redis_queue=jsonlogs redis2es host.to.es.server Resources that help writing log2json filters: - look at log2json.rb source and example filters - http://grokdebug.herokuapp.com/ - http://www.ruby-doc.org/stdlib-1.9.3/libdoc/date/rdoc/DateTime.html#method-i-strftime

Log2json lets you read, filter and send logs as JSON objects via Unix pipes. It is inspired by Logstash, and is meant to be compatible with it at the JSON event/record level so that it can easily work with Kibana. Reading logs is done via a shell script(eg, `tail`) running in its own process. You then configure(see the `syslog2json` or the `nginxlog2json` script for examples) and run your filters in Ruby using the `Log2Json` module and its contained helper classes. `Log2Json` reads from stdin the logs(one log record per line), parses the log lines into JSON records, and then serializes and writes the records to stdout, which then can be piped to another process for processing or sending it to somewhere else. Currently, Log2json ships with a `tail-log` script that can be run as the input process. It's the same as using the Linux `tail` utility with the `-v -F` options except that it also tracks the positions(as the numbers of lines read from the beginning of the files) in a few files in the file system so that if the input process is interrupted, it can continue reading from where it left off next time if the files had been followed. This feature is similar to the sincedb feature in Logstash's file input. Note: If you don't need the tracking feature(ie, you are fine with always tailling from the end of file with `-v -F -n0`), then you can just use the `tail` utility that comes with your Linux distribution.(Or more specifically, the `tail` from the GNU coreutils). Other versions of the `tail` utility may also work, but are not tested. The input protocol expected by Log2json is very simple and documented in the source code. ** The `tail-log` script uses a patched version of `tail` from the GNU coreutils package. A binary of the `tail` utility compiled for Ubuntu 12.04 LTS is included with the Log2json gem. If the binary doesn't work for your distribution, then you'll need to get GNU coreutils-8.13, apply the patch(it can be found in the src/ directory of the installed gem), and then replace the bin/tail binary in the directory of the installed gem with your version of the binary. ** P.S. If you know of a way to configure and compile ONLY the tail program in coreutils, please let me know! The reason I'm not building tail post gem installation is that it takes too long to configure && make because that actually builds every utilties in coreutils. For shipping logs to Redis, there's the `lines2redis` script that can be used as the output process in the pipe. For shipping logs from Redis to ElasticSearch, Log2json provides a `redis2es` script. Finally here's an example of Log2json in action: From a client machine: tail-log /var/log/{sys,mail}log /var/log/{kern,auth}.log | syslog2json | queue=jsonlogs \ flush_size=20 \ flush_interval=30 \ lines2redis host.to.redis.server 6379 0 # use redis DB 0 On the Redis server: redis_queue=jsonlogs redis2es host.to.es.server Resources that help writing log2json filters: - look at log2json.rb source and example filters - http://grokdebug.herokuapp.com/ - http://www.ruby-doc.org/stdlib-1.9.3/libdoc/date/rdoc/DateTime.html#method-i-strftime

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