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  • Redis Cookbook Chat Recipe

    - by Tommy Kennedy
    I am a new starter to Node.Js and Redis. I got the Redis cookbook and was trying out the Chat client & Server recipe. I was wondering if anybody got the code to work or if there is some bug in the code. I dont see where the sent messages from the client get invoked on the server. Any help would be great. Regards, Tom Client Code: <?php ?> <html> <head> <title></title> <script src="http://192.168.0.118:8000/socket.io/socket.io.js"></script> <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.6.1/jquery.min.js"></script> <script> var socket = io.connect('192.168.0.118',{port:8000}); socket.on('message', function(data){ alert(data); //var li = new Element('li').insert(data); //$('messages').insert({top: li}); }); </script> </head> <body> <ul id="messages"> <!-- chat messages go here --> </ul> <form id="chatform" action=""> <input id="chattext" type="text" value="" /> <input type="submit" value="Send" /> </form> <script> $('#chatform').submit(function() { socket.emit('message', 'test'); //$('chattext').val()); $('chattext').val(""); // cleanup the field return false; }); </script> </body> </html> Server Code: var http = require('http'); io = require('socket.io'); redis = require('redis'); rc = redis.createClient(); //rc1 = redis.createClient(); rc.on("connect",function(){ rc.subscribe("chat"); console.log("In Chat Stream"); }); rc.on("message",function (channel,message){ console.log("Sending hope: " + message); //rc1.publish("chat","hope"); socketio.sockets.emit('message',message); }); server = http.createServer(function(req,res){ res.writeHead(200,{'content-type':'text/html'}); res.end('<h1>hello world</h1>'); }); server.listen(8000); var socketio = io.listen(server);

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  • Redis suggesstion for selecting data type

    - by PHP Connect
    We have questions based where in home page we were showing 2 list Questions by date modified Question have bigger views and ans count. And in this both listing if question have same views or ans count then sorting is based on date. Previously i am directly quiring to MySQL database and fetching the values so it's easy. But each page request hitting to MySQL it's bit expensive then start doing caching. I started using Redis. Following is the cases when i use redis cache Issues is On second listing i have to display questions by votes and not answered combine. How can i stored this type of data in redis to load faster with sorting based by 2 conditions votes with time and ans count with time?

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  • Redis autocomplete

    - by Alfred
    Hi, How can I implement an autocomplete using redis? Say for example I have an array ["alfred","joel","jeff","addick"]. When I type a I get ["alfred", "addick"] I hope you get the point. How can I implement this using redis commands efficiently(if possible but I think it is). It would be great if I could get some simple commands I can try out via telnet to mimic this behaviour. Thanks P.S: Merry x-mas to all of you :)

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  • Resque Runtime Error at /workers: wrong number of arguments for 'exists' command

    - by Superflux
    I'm having a runtime errror when i'm looking at the "workers" tab on resque-web (localhost). Everything else works. Edit: when this error occurs, i also have some (3 or 4) unknown workers 'not working'. I think they are responsible for the error but i don't understand how they got here Can you help me on this ? Did i do something wrong ? Config: Resque 1.8.5 as a gem in a rails 2.3.8 app on Snow Leopard redis 1.0.7 / rack 1.1 / sinatra 1.0 / vegas 0.1.7 file: client.rb location: format_error_reply line: 558 BACKTRACE: * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in format_error_reply * 551. when DOLLAR then format_bulk_reply(line) 552. when ASTERISK then format_multi_bulk_reply(line) 553. else raise ProtocolError.new(reply_type) 554. end 555. end 556. 557. def format_error_reply(line) 558. raise "-" + line.strip 559. end 560. 561. def format_status_reply(line) 562. line.strip 563. end 564. 565. def format_integer_reply(line) * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in format_reply * 541. 542. def reconnect 543. disconnect && connect_to_server 544. end 545. 546. def format_reply(reply_type, line) 547. case reply_type 548. when MINUS then format_error_reply(line) 549. when PLUS then format_status_reply(line) 550. when COLON then format_integer_reply(line) 551. when DOLLAR then format_bulk_reply(line) 552. when ASTERISK then format_multi_bulk_reply(line) 553. else raise ProtocolError.new(reply_type) 554. end 555. end * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in read_reply * 478. disconnect 479. 480. raise Errno::EAGAIN, "Timeout reading from the socket" 481. end 482. 483. raise Errno::ECONNRESET, "Connection lost" unless reply_type 484. 485. format_reply(reply_type, @sock.gets) 486. end 487. 488. 489. if "".respond_to?(:bytesize) 490. def get_size(string) 491. string.bytesize 492. end * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in process_command * 448. return pipeline ? results : results[0] 449. end 450. 451. def process_command(command, argvv) 452. @sock.write(command) 453. argvv.map do |argv| 454. processor = REPLY_PROCESSOR[argv[0].to_s] 455. processor ? processor.call(read_reply) : read_reply 456. end 457. end 458. 459. def maybe_lock(&block) 460. if @thread_safe 461. @mutex.synchronize(&block) 462. else * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in map * 446. end 447. 448. return pipeline ? results : results[0] 449. end 450. 451. def process_command(command, argvv) 452. @sock.write(command) 453. argvv.map do |argv| 454. processor = REPLY_PROCESSOR[argv[0].to_s] 455. processor ? processor.call(read_reply) : read_reply 456. end 457. end 458. 459. def maybe_lock(&block) 460. if @thread_safe * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in process_command * 446. end 447. 448. return pipeline ? results : results[0] 449. end 450. 451. def process_command(command, argvv) 452. @sock.write(command) 453. argvv.map do |argv| 454. processor = REPLY_PROCESSOR[argv[0].to_s] 455. processor ? processor.call(read_reply) : read_reply 456. end 457. end 458. 459. def maybe_lock(&block) 460. if @thread_safe * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in raw_call_command * 435. @sock.write(command) 436. return true 437. end 438. # The normal command execution is reading and processing the reply. 439. results = maybe_lock do 440. begin 441. set_socket_timeout!(0) if requires_timeout_reset?(argvv[0][0].to_s) 442. process_command(command, argvv) 443. ensure 444. set_socket_timeout!(@timeout) if requires_timeout_reset?(argvv[0][0].to_s) 445. end 446. end 447. 448. return pipeline ? results : results[0] 449. end * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in synchronize * 454. processor = REPLY_PROCESSOR[argv[0].to_s] 455. processor ? processor.call(read_reply) : read_reply 456. end 457. end 458. 459. def maybe_lock(&block) 460. if @thread_safe 461. @mutex.synchronize(&block) 462. else 463. block.call 464. end 465. end 466. 467. def read_reply 468. * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in maybe_lock * 454. processor = REPLY_PROCESSOR[argv[0].to_s] 455. processor ? processor.call(read_reply) : read_reply 456. end 457. end 458. 459. def maybe_lock(&block) 460. if @thread_safe 461. @mutex.synchronize(&block) 462. else 463. block.call 464. end 465. end 466. 467. def read_reply 468. * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in raw_call_command * 432. end 433. # When in Pub/Sub mode we don't read replies synchronously. 434. if @pubsub 435. @sock.write(command) 436. return true 437. end 438. # The normal command execution is reading and processing the reply. 439. results = maybe_lock do 440. begin 441. set_socket_timeout!(0) if requires_timeout_reset?(argvv[0][0].to_s) 442. process_command(command, argvv) 443. ensure 444. set_socket_timeout!(@timeout) if requires_timeout_reset?(argvv[0][0].to_s) 445. end 446. end * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in call_command * 336. # try to reconnect just one time, otherwise let the error araise. 337. def call_command(argv) 338. log(argv.inspect, :debug) 339. 340. connect_to_server unless connected? 341. 342. begin 343. raw_call_command(argv.dup) 344. rescue Errno::ECONNRESET, Errno::EPIPE, Errno::ECONNABORTED 345. if reconnect 346. raw_call_command(argv.dup) 347. else 348. raise Errno::ECONNRESET 349. end 350. end * /Library/Ruby/Gems/1.8/gems/redis-1.0.7/lib/redis/client.rb in method_missing * 385. connect_to(@host, @port) 386. call_command([:auth, @password]) if @password 387. call_command([:select, @db]) if @db != 0 388. @sock 389. end 390. 391. def method_missing(*argv) 392. call_command(argv) 393. end 394. 395. def raw_call_command(argvp) 396. if argvp[0].is_a?(Array) 397. argvv = argvp 398. pipeline = true 399. else * /Library/Ruby/Gems/1.8/gems/redis-namespace-0.4.4/lib/redis/namespace.rb in send * 159. args = add_namespace(args) 160. args.push(last) if last 161. when :alternate 162. args = [ add_namespace(Hash[*args]) ] 163. end 164. 165. # Dispatch the command to Redis and store the result. 166. result = @redis.send(command, *args, &block) 167. 168. # Remove the namespace from results that are keys. 169. result = rem_namespace(result) if after == :all 170. 171. result 172. end 173. * /Library/Ruby/Gems/1.8/gems/redis-namespace-0.4.4/lib/redis/namespace.rb in method_missing * 159. args = add_namespace(args) 160. args.push(last) if last 161. when :alternate 162. args = [ add_namespace(Hash[*args]) ] 163. end 164. 165. # Dispatch the command to Redis and store the result. 166. result = @redis.send(command, *args, &block) 167. 168. # Remove the namespace from results that are keys. 169. result = rem_namespace(result) if after == :all 170. 171. result 172. end 173. * /Library/Ruby/Gems/1.8/gems/resque-1.8.5/lib/resque/worker.rb in state * 416. def idle? 417. state == :idle 418. end 419. 420. # Returns a symbol representing the current worker state, 421. # which can be either :working or :idle 422. def state 423. redis.exists("worker:#{self}") ? :working : :idle 424. end 425. 426. # Is this worker the same as another worker? 427. def ==(other) 428. to_s == other.to_s 429. end 430. * /Library/Ruby/Gems/1.8/gems/resque-1.8.5/lib/resque/server/views/workers.erb in __tilt_a2112543c5200dbe0635da5124b47311 * 46. <tr> 47. <th>&nbsp;</th> 48. <th>Where</th> 49. <th>Queues</th> 50. <th>Processing</th> 51. </tr> 52. <% for worker in (workers = resque.workers.sort_by { |w| w.to_s }) %> 53. <tr class="<%=state = worker.state%>"> 54. <td class='icon'><img src="<%=u state %>.png" alt="<%= state %>" title="<%= state %>"></td> 55. 56. <% host, pid, queues = worker.to_s.split(':') %> 57. <td class='where'><a href="<%=u "workers/#{worker}"%>"><%= host %>:<%= pid %></a></td> 58. <td class='queues'><%= queues.split(',').map { |q| '<a class="queue-tag" href="' + u("/queues/#{q}") + '">' + q + '</a>'}.join('') %></td> 59. 60. <td class='process'> * /Library/Ruby/Gems/1.8/gems/resque-1.8.5/lib/resque/server/views/workers.erb in each * /Library/Ruby/Gems/1.8/gems/resque-1.8.5/lib/resque/server/views/workers.erb in __tilt_a2112543c5200dbe0635da5124b47311 * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/tilt.rb in send * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/tilt.rb in evaluate * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/tilt.rb in render * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in render * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in erb * /Library/Ruby/Gems/1.8/gems/resque-1.8.5/lib/resque/server.rb in show * /Library/Ruby/Gems/1.8/gems/resque-1.8.5/lib/resque/server.rb in GET /workers * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in call * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in route * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in instance_eval * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in route_eval * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in route! * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in catch * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in route! * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in each * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in route! * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in dispatch! * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in call! * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in instance_eval * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in invoke * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in catch * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in invoke * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in call! * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in call * /Volumes/Donnees/Users/**/.gem/ruby/1.8/gems/rack-1.1.0/lib/rack/showexceptions.rb in call * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in call * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in synchronize * /Library/Ruby/Gems/1.8/gems/sinatra-1.0/lib/sinatra/base.rb in call * /Volumes/Donnees/Users/**/.gem/ruby/1.8/gems/rack-1.1.0/lib/rack/content_length.rb in call * /Volumes/Donnees/Users/**/.gem/ruby/1.8/gems/rack-1.1.0/lib/rack/chunked.rb in call * /Volumes/Donnees/Users/**/.gem/ruby/1.8/gems/rack-1.1.0/lib/rack/handler/mongrel.rb in process * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in process_client * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in each * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in process_client * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in run * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in initialize * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in new * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in run * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in initialize * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in new * /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/lib/ruby/gems/1.8/gems/mongrel-1.1.5/lib/mongrel.rb in run * /Volumes/Donnees/Users/**/.gem/ruby/1.8/gems/rack-1.1.0/lib/rack/handler/mongrel.rb in run * /Library/Ruby/Gems/1.8/gems/vegas-0.1.7/lib/vegas/runner.rb in run! * /Library/Ruby/Gems/1.8/gems/vegas-0.1.7/lib/vegas/runner.rb in start * /Library/Ruby/Gems/1.8/gems/resque-1.8.5/bin/resque-web in new * /Library/Ruby/Gems/1.8/gems/resque-1.8.5/bin/resque-web in nil * /usr/bin/resque-web in load

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  • How to install Predis

    - by user782860
    I am trying to install Predis, but keep getting a 500 Server errror. Here is what I have done. 1.) Have apache and php installed on Ubuntu Natty. 2.) Used the instructions on this page http://redis.io/download to download Redis. 3.) Ran the following example to confirm that Redis is working: $ src/redis-cli redis> set foo bar OK redis> get foo "bar" 4.) Have a local website at /home/user/Dropbox/documents/www/mywebsite.com/index.php and have confirmed that php is working. 5.) Downloaded the .zip version of Predis ( https://github.com/nrk/predis Version: v0.6.6-PHP5.2 ), and unzipped the contents to /home/user/Dropbox/documents/www/mywebsite.com/. So now Predis is here: /home/user/Dropbox/documents/www/mywebsite.com/nrk-predis-3bf1230/ 6.) Opened the /home/user/Dropbox/documents/www/mywebsite.com/index.php page. Here is its contents: <? define("PREDIS_BASE_PATH", "nrk-predis-3bf1230/lib/"); spl_autoload_register(function($class) { $file = PREDIS_BASE_PATH.strtr($class, '\\', '/').'.php'; if (file_exists($file)) { require $file; return true; } }); $redis = new Predis_Client(); $redis->set('foo', 'bar'); $value = $redis->get('foo'); ?> I have tried changing: $redis = new Predis_Client(); to: $redis = new Predis\Client(); Have tried changing the the PREDIS_BASE_PATH to: /nrk-predis-3bf1230/lib /home/user/Dropbox/documents/www/mywebsite.com/nrk-predis-3bf1230/lib/ /home/user/Dropbox/documents/www/mywebsite.com/nrk-predis-3bf1230/lib Have done a chmod +x on both: /home/user/Dropbox/documents/www/mywebsite.com/nrk-predis-3bf1230/ /home/user/Dropbox/documents/www/mywebsite.com And doing all of the above always results in a 500 server error. What am I doing wrong?

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  • Scaling a node.js application, nginx as a base server, but varnish or redis for caching?

    - by AntelopeSalad
    I'm not close to being well versed in using nginx or varnish but this is my setup at the moment. I have a node.js server running which is serving either json, html templates, or socket.io events. Then I have nginx running in front of node which is serving all static content (css, js, etc.). At this point I would like to cache both static content and dynamic content to memory. It's to my understanding that varnish can cache static content quite well and it wouldn't require touching my application code. I also think it's capable of caching dynamic content too but there cannot be any cookie headers? I do use redis at the moment for holding session data and planned to use it for other things in the future like keeping track of non-crucial but fun stats. I just have no idea how I should handle caching everything on the site. I think it comes down to these options but there might be more: Throw varnish in front of nginx and let varnish cache static pages, no app code changes. Redis would cache dynamic db calls which would require modifying my app code. Ignore using varnish completely and let redis handle caching everything, then use one of the nginx-redis modules. I'm not sure if this would require a lot of app code changes (for the static files). I'm not having any luck finding benchmarks that compare nginx+varnish vs nginx+redis and I'm too inexperienced to bench it myself (high chances of my configs being awful). I'm basically looking for the solution that would be the most efficient in terms of req/sec and scalable in the future (throw new hardware at the problem + maybe adjust some values in a config = new servers up and running semi-painlessly).

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  • Looking for: nosql (redis/mongodb) based event logging for Django

    - by Parand
    I'm looking for a flexible event logging platform to store both pre-defined (username, ip address) and non-pre-defined (can be generated as needed by any piece of code) events for Django. I'm currently doing some of this with log files, but it ends up requiring various analysis scripts and ends up in a DB anyway, so I'm considering throwing it immediately into a nosql store such as MongoDB or Redis. The idea is to be easily able to query, for example, which ip address the user most commonly comes from, whether the user has ever performed some action, lookup the outcome for a specific event, etc. Is there something that already does this? If not, I'm thinking of this: The "event" is a dictionary attached to the request object. Middleware fills in various pieces (username, ip, sql timing), code fills in the rest as needed. After the request is served a post-request hook drops the event into mongodb/redis, normalizing various fields (eg. incrementing the username:ip address counter) and dropping the rest in as is. Words of wisdom / pointers to code that does some/all of this would be appreciated.

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  • Redis - Records Fall Off

    - by Ian
    With memcache, when you exceed the available ram, it automatically drops the oldest records off the end of the stack.. Is there a way to do this with redis? I'm trying to find ways to avoid running in to a write error (when there's no more available ram), other than setting a timeout. The only reason the timeout isn't useful, it because it doesn't guaranty the ability to write.

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  • Migrating to AWS Cloud with auto-scaling - where to put Redis and ElasticSearch?

    - by RobMasters
    I've been trying to research this topic but haven't found anywhere that recommends where to install services such as Redis and ElasticSearch when migrating to a cloud framework. I'm currently running a Symfony2 application on 2 static servers - one is running MySQL and the other is the public facing web server, which also has Redis and ElasticSearch running on it. Both of these servers are virtualised, but they're static in terms of not being able to replicate at present (various aspects are still dependent on the local filesystem). The goal is to migrate to AWS and use auto-scaling to be able to spin up and kill web servers as required, but I'm not clear on what I should put on each EC2 instance. Should they be single-responsibility only? i.e. Set up individual instances for the web server(s), Redis, and ElasticSearch and most likely an RDS instance for MySQL and only set up auto-scaling on the web server(s)? I don't foresee having to scale the ElasticSearch server anytime soon as it's only driving the search functionality, but it's possible that Redis may need to be replicated at some point - but should this be done manually? I'm not sure of how this could be done automatically as each instance needs to be configured to know about it's master/slave(s) as far as I know. I'd appreciate advice on this. One more quick question while I'm here - how would I be able to deploy code changes when there are X web servers currently active? I'm using a Capifony deployment script (Symfony2 version of Capistrano), which I think can handle multiple servers easily enough by specifying an array of :domain addresses...but how can should this be handled when the number of web servers can vary?

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  • Using MongoDB + Redis + Apache on the same server in production?

    - by Dayson
    I intend to launch my web app using a 8 GB VPS. It uses MongoDB + Redis for storage/caching and Apache + PHP-FPM for serving requests. Could there be any issues with running Mongo + Redis + Apache on the same server? Would it make more sense to setup 2 x 4 GB VPS servers and keep Mongo on one and Redis + Apache on another? Should I just start with one server and worry about scaling horizontally later by delegating the existing server to Mongo in the future (due to its large RAM) and moving the web servers on to multiple smaller VPS'?

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  • Is redis a durable datastore?

    - by allyourcode
    By "durable" I mean, the server can crash at any time, and as long as the disk remains in tact, no data is lost (see ACID). Seems like that's what journaling mode is for, but if you enable journaling, doesn't that defeat the purpose of operating on in-memory data? Read operations might not be affected by journaling, but it seems like journaling would kill your write performance.

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  • 2 approaches for tracking online users with Redis. Which one is faster?

    - by Stanislav
    Recently I found an nice blog post presenting 2 approaches for tracking online users of a web site with the help of Redis. 1) Smart-keys and setting their expiration http://techno-weenie.net/2010/2/3/where-s-waldo-track-user-locations-with-node-js-and-redis 2) Set-s and intersects http://www.lukemelia.com/blog/archives/2010/01/17/redis-in-practice-whos-online/ Can you judge which one should be faster and why?

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  • How to create a local Windows-based service bus outside of Azure, similar to Redis with automatic fail-over?

    - by ElHaix
    We are implementing a service/message-bus feature in our SignalR application and have been looking at Redis, with automatic fail-over using Redis Sentiel. We would like to maintain our own servers and have read SignalR powered by Service Bus. Since this is a Winddows Azure implementation, how can I accomplish this in our internal network with VM's with automatic fail-over similar to the Redis solution discussed above?

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  • Get more space for redis in unix server

    - by DevTraveler
    In our app we have only windows servers beside the cases we use redis queues. This case , we use unix server created by amazon. As you can see we do not have a lot of space available and we want to make sure redis has enough space to work without getting stuck. I am little bit new in unix and after reading some data about the unix file system i still was not fully sure how can i give the redis drive (it is in the home directory) more space. I see the mnt that has a lot of space but read it is temporary for cd-rom and network drives. Can you help me figure out how to get more space to my redis ? If it is possible i prefer not to re-install the redis server. Filesystem Size Used Avail Use% Mounted on /dev/xvda1 7.9G 6.7G 880M 89% / udev 7.4G 4.0K 7.4G 1% /dev tmpfs 3.0G 152K 3.0G 1% /run none 5.0M 0 5.0M 0% /run/lock none 7.4G 0 7.4G 0% /run/shm /dev/xvdb 414G 30G 364G 8% /mnt Thanks.

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  • Deploying Memcached as 32bit or 64bit?

    - by rlotun
    I'm curious about how people deploy memcached on 64 bit machines. Do you compile a 64bit (standard) memcached binary and run that, or do people compile it in 32bit mode and run N instances (where N = machine_RAM / 4GB)? Consider a recommended deployment of Redis (from the Redis FAQ): Redis uses a lot more memory when compiled for 64 bit target, especially if the dataset is composed of many small keys and values. Such a database will, for instance, consume 50 MB of RAM when compiled for the 32 bit target, and 80 MB for 64 bit! That's a big difference. You can run 32 bit Redis binaries in a 64 bit Linux and Mac OS X system without problems. For OS X just use make 32bit. For Linux instead, make sure you have libc6-dev-i386 installed, then use make 32bit if you are using the latest Git version. Instead for Redis <= 1.2.2 you have to edit the Makefile and replace "-arch i386" with "-m32". If your application is already able to perform application-level sharding, it is very advisable to run N instances of Redis 32bit against a big 64 bit Redis box (with more than 4GB of RAM) instead than a single 64 bit instance, as this is much more memory efficient. Would not the same recommendation also apply to a memcached cluster?

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  • How should I implement simple caches with concurrency on Redis?

    - by solublefish
    Background I have a 2-tier web service - just my app server and an RDBMS. I want to move to a pool of identical app servers behind a load balancer. I currently cache a bunch of objects in-process. I hope to move them to a shared Redis. I have a dozen or so caches of simple, small-sized business objects. For example, I have a set of Foos. Each Foo has a unique FooId and an OwnerId. One "owner" may own multiple Foos. In a traditional RDBMS this is just a table with an index on the PK FooId and one on OwnerId. I'm caching this in one process simply: Dictionary<int,Foo> _cacheFooById; Dictionary<int,HashSet<int>> _indexFooIdsByOwnerId; Reads come straight from here, and writes go here and to the RDBMS. I usually have this invariant: "For a given group [say by OwnerId], the whole group is in cache or none of it is." So when I cache miss on a Foo, I pull that Foo and all the owner's other Foos from the RDBMS. Updates make sure to keep the index up to date and respect the invariant. When an owner calls GetMyFoos I never have to worry that some are cached and some aren't. What I did already The first/simplest answer seems to be to use plain ol' SET and GET with a composite key and json value: SET( "ServiceCache:Foo:" + theFoo.Id, JsonSerialize(theFoo)); I later decided I liked: HSET( "ServiceCache:Foo", theFoo.FooId, JsonSerialize(theFoo)); That lets me get all the values in one cache as HVALS. It also felt right - I'm literally moving hashtables to Redis, so perhaps my top-level items should be hashes. This works to first order. If my high-level code is like: UpdateCache(myFoo); AddToIndex(myFoo); That translates into: HSET ("ServiceCache:Foo", theFoo.FooId, JsonSerialize(theFoo)); var myFoos = JsonDeserialize( HGET ("ServiceCache:FooIndex", theFoo.OwnerId) ); myFoos.Add(theFoo.OwnerId); HSET ("ServiceCache:FooIndex", theFoo.OwnerId, JsonSerialize(myFoos)); However, this is broken in two ways. Two concurrent operations can read/modify/write at the same time. The latter "wins" the final HSET and the former's index update is lost. Another operation could read the index in between the first and second lines. It would miss a Foo that it should find. So how do I index properly? I think I could use a Redis set instead of a json-encoded value for the index. That would solve part of the problem since the "add-to-index-if-not-already-present" would be atomic. I also read about using MULTI as a "transaction" but it doesn't seem like it does what I want. Am I right that I can't really MULTI; HGET; {update}; HSET; EXEC since it doesn't even do the HGET before I issue the EXEC? I also read about using WATCH and MULTI for optimistic concurrency, then retrying on failure. But WATCH only works on top-level keys. So it's back to SET/GET instead of HSET/HGET. And now I need a new index-like-thing to support getting all the values in a given cache. If I understand it right, I can combine all these things to do the job. Something like: while(!succeeded) { WATCH( "ServiceCache:Foo:" + theFoo.FooId ); WATCH( "ServiceCache:FooIndexByOwner:" + theFoo.OwnerId ); WATCH( "ServiceCache:FooIndexAll" ); MULTI(); SET ("ServiceCache:Foo:" + theFoo.FooId, JsonSerialize(theFoo)); SADD ("ServiceCache:FooIndexByOwner:" + theFoo.OwnerId, theFoo.FooId); SADD ("ServiceCache:FooIndexAll", theFoo.FooId); EXEC(); //TODO somehow set succeeded properly } Finally I'd have to translate this pseudocode into real code depending how my client library uses WATCH/MULTI/EXEC; it looks like they need some sort of context to hook them together. All in all this seems like a lot of complexity for what has to be a very common case; I can't help but think there's a better, smarter, Redis-ish way to do things that I'm just not seeing. How do I lock properly? Even if I had no indexes, there's still a (probably rare) race condition. A: HGET - cache miss B: HGET - cache miss A: SELECT B: SELECT A: HSET C: HGET - cache hit C: UPDATE C: HSET B: HSET ** this is stale data that's clobbering C's update. Note that C could just be a really-fast A. Again I think WATCH, MULTI, retry would work, but... ick. I know in some places people use special Redis keys as locks for other objects. Is that a reasonable approach here? Should those be top-level keys like ServiceCache:FooLocks:{Id} or ServiceCache:Locks:Foo:{Id}? Or make a separate hash for them - ServiceCache:Locks with subkeys Foo:{Id}, or ServiceCache:Locks:Foo with subkeys {Id} ? How would I work around abandoned locks, say if a transaction (or a whole server) crashes while "holding" the lock?

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  • 100,000 complex structures that are accessed frequently by 100,000 users

    - by Saad
    If you are required to store 100,000 complex structures that are accessed frequently by 100,000 users, which of the following solutions would you use and why? Memcached, In-code python objects, Redis, or a relational database (MySQL). With the little knowledge that I have I think that memcached and In-code python object will not store permanent persistent data. so they don't qualify as the right answer for such a problem. And for complex data structures its best to use Redis. Please correct me if I am wrong.

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