Missing Statistics in OpenX Again – This Time in 2.8.7

November 3rd, 2011

After upgrading to OpenX 2.8.7 from 2.4.1 our statistics suddenly seemed to have vanished. Debugging an issue like this isn’t just straight forward, but after digging through google searches, wiki pages at OpenX and, well, reading the source (brrrrrrrrr), I think I’ve nailed it.

After upgrading to 2.8.7 the DeliveryLog plugin didn’t get installed – which meant that no delivery / clicks / impressions were logged. After discovering that this had been moved to a plugin I tried simply unzippping the plugin and copying the files to the plugins/-directory. This seemed to make OpenX recognize the plugin if I went to “groups” in the plugin menu, but not under the “plugin” menu. Another problem was the fact that it didn’t actually log anything, which could be considered a problem.

All the Google searches had shown that OpenX had changed the logging format to a new table structure (named buckets), but they don’t provide of restoring / creating the bucket tables if they don’t exist, and they don’t give any error about the bucket tables missing if the plugin doesn’t load. I couldn’t find anything at all about how the tables should look and which tables should be installed, but I finally tried to simply install the plugin through the web interface (Log in as Administrator -> Select Plugins in the top menu) by uploading the zip file directly, and then FINALLY the post install script ran. That created the tables (I’ll dump the definitions later if someone needs them), and after reloading the ads the bucket tables started getting values.

Now we’ll just have to hope that they actually gets aggregated into something useful as well..

PS: I’m less than impressed by the OpenX upgrade procedure, it always seem to fsck up some detail that leaves your installation in limbo, without being able to detect that something has gone wrong and provide a way to resolve the issue. I understand that they need to – and want to – focus on their pay product, so well, I’ll keep having to fix things manually for a while, but Google’s Doubleclick for Small Businesses may see a new customer soon.

Python, httplib and Empty Content for 200/201 Responses

October 27th, 2011

While hacking together a client for Imbo in python, I weren’t able to read the response from a connection initiated with httplib. If the request errored out (http response code 400/403/404) everything worked as it should, but if the response code were 200 / 201, the response read from the httplib connection was empty (read by using getresponse()).

Turns out the issue was related to calling close on the connection before reading the response. This apparently works if there’s an error (which means that the response should be rather small), but not if there’s a regular “OK” response from the server (it’s not enough just retrieving the HTTPResponse object, you have to call read() on it before closing the connection).

  1. connection.request(method, path, data)
  2. data = connection.getresponse().read()
  3. connection.close()

(Compared to the previous solution which retrieve the HTTPResponse object, closed the connection and then read the response)

Evolution & Exchange: Unable to retrieve message

October 24th, 2011

Some time after upgrading to Ubuntu 11.10 I ended up with the dreaded “Unable to retrieve message” in Evolution (which I use for Exchange connectivity). This has usually corrected itself by simply restarting Evolution, but this time nothing would help. I stumbled across a thread that provided a few ways to possibly solve the issue, but the .evolution directory didn’t contain any live installation in Ubuntu.

Turns out the directory is:

.local/share/evolution

As both my mailstore and address book lives on the Exchange server, I decided to just move the evolution directory to a new name and recreate the evolution directory from scratch. This takes a bit of time while Evolution indexes everything, but after a while everything were back to normal.

Solr Response Empty from PHP, but Works in Browser or CURL?

October 19th, 2011

Weird issue that I think I’ve stumbled upon earlier, but yet again reared it’s head yesterday. Certain application containers (possibly Jetty in this case) will for some reason not produce any output from Solr (or other applications I’d guess) if the request is made with HTTP/1.0 as the version identifier (“GET /…/ HTTP/1.0″ as the first line of the request). The native HTTP support in PHP identifies itself as HTTP/1.0 as it doesn’t support request chunking, which then turns into a magical problem with requests that used to work, but doesn’t work any longer (the response is just zero bytes in size – all other headers are identical) – but still works as expected if you open them in your browser.

The solution is to either gamble on the server not sending any chunked responses and then setting protocol_version in the stream context that you pass to the file retrieving function (the list of HTTP wrapper settings (.. I don’t think it’s a good idea to define protocol_version as float, but .. well.)), or use cURL instead. The Solr pecl extension uses cURL internally, so it’s not affected by this issue.

E:Error, pkgProblemResolver::Resolve generated breaks

October 14th, 2011

While attempting to upgrade to Ubuntu 11.10 (Oneiric) from 11.04, do-release-upgrade refused to do anything useful. The only message it felt like delivering was “E:Error, pkgProblemResolver::Resolve generated breaks”. Googling didn’t turn up much, but a forum thread (which I seem to have lost now) suggested (among other attempts) to remove any references to external (3rd party) APT repositories. I thought do-release-upgrade did this by itself, but apparently not …

Commenting out the external repositories in /etc/apt/sources.list and in /etc/apt/sources.list.d/* solved the problem (I had spotify, dropbox and Google Chrome there), allowing do-release-upgrade to do its thing.

Checking Status of a Background Task in python-gearman

October 3rd, 2011

After stumbling over a question on stackoverflow about how you’d use python-gearman for checking the current status of a running background task, I decided to dig a bit deeper into python-gearman and .. well, answer how you’d do just that.

It turns out it wasn’t as straight forward as it should have been, but at least I managed to solve it by using the current API. First of all you’ll have to keep track of which Gearman server gets your task, and what handle it has assigned to the task. These two values identify a current running task, and since the identifiers (handle) isn’t globally unique, you’ll also have to keep track of the current server (so you know where to ask).

To request the current status of a long running task you’ll have to create appropriate instances of the GearmanJob and GearmanJobRequest yourself.

Here’s a small example of how you can do this:

  1. import gearman
  2.    
  3. client = gearman.GearmanClient(['localhost'])
  4. result = client.submit_job('reverse', 'this is a string', background=True);

The connection information is available through result.job.connection (.gearman_host and .gearman_port), while the handle is available through result.job.handle.

To check the status of a currently running job you create a GearmanClient, but only supply the server you want to query for the current state:

  1. client = gearman.GearmanClient(['localhost'])
  2.  
  3. # configure the job to request status for – the last four is not needed for Status requests.
  4. j = gearman.job.GearmanJob(client.connection_list[0], result.job.handle, None, None, None, None)
  5.  
  6. # create a job request
  7. jr = gearman.job.GearmanJobRequest(j)
  8. jr.state = 'CREATED'
  9.  
  10. # request the state from gearmand
  11. res = client.get_job_status(jr)
  12.  
  13. # the res structure should now be filled with the status information about the task
  14. print(str(res.status.numerator) + " / " + str(res.status.denominator))

That should at least solve the problem until python-gearman gets an easier API to do these kinds of requests.

Update: I’ve also added a convenience function to my python-gearman fork at github.

Gearman and Locking for Identical Jobs / Tasks

August 16th, 2011

A question that came up on #gearman on freenode today was how to make sure that a task is only performed by one worker at a time (remember from our previous introduction to Gearman that a worker is the actual piece of code performing a task that has been submitted to gearmand).

I had a few naive suggestions:

Run memcache with a low timeout (add a key when the task arrives with a low timeout value, if the add fails, simply return as someone else is probably doing the task).

Add a function for each unique identification value that can be performed, and only register one worker for each function (I like the memcache solution way better…, but it’d work. at least for a bit.)

But neither of these are a good solution to the problem; luckily Brian Moon also saw the question and was quick to point out that Gearman actually has a built-in mechanism for handling de-duplication of tasks. I’ve never used it myself (only read about it a couple of times), so it’s a good thing that Brian paid attention :-)

The solution: Use gearman_job_unique (in the PHP extension this value (named $unique in the documentation) can be tacked on to the end of most methods that add tasks or perform tasks directly (such as the do* methods)) – if Gearman sees a value that there’s already a worker active for, it’ll not resubmit the task but simply return the same result when the first worker returns (unless it’s a background task, where the second call will just return – there’s no difference in a task being submitted or already being run if you’re counting on Gearman to de-duplicate your tasks).

So if you need to lock and exit, remember that Gearman has de-duplication of non-unique tasks built-in. I tend to forget.

A Gentle Introduction to Gearman and its Concepts

August 1st, 2011

Gearman (an anagram for “Manager”) is a system for farming out work units to several different servers (or several processes on one server), allowing the calling code to do something completely different while the task is performed. Gearman is not intended for inter-process communication, but is a way to tell other processes that there are work available, and letting these processes (called workers) grab a piece of work for themselves.

One of the common themes that show up at the gearman IRC channel on freenode is an attempt to understand what gearman is and how everything fits together. I’ll try to explain the different concepts and what the different responsibilities of a working gearman infrastructure are. There’s also a “Getting Started” guide on the Gearman web site with a bit of example code and installation instructions, so you might want to keep that open in another tab. So here we go: a simple gearman tutorial explaining the concepts and not just throwing example code your way.

There are three core components of a gearman installation. These are a client (someone requesting a task to be performed), a worker (someone performing a task) and the server (which coordinates tasks between clients and workers). All these three components need to be running for you to be able to something useful with gearman. It’s worth noting that I’ll use name “task” for a single item to be performed, you’ll also see this named ‘function’ (which is the name of the actual function the task asks to be performed – a server offers several “functions” that a client can call). Some APIs might also refer to a “task” as a collection of functions to be called. I’ll use the first definition; a task is a call to a function on the server, together with the data for the task and a task identifier. Several subsequent tasks will call the same function.

I’ll go a bit more in detail about each of these components, but it’s important that you understand how everything is interconnected first. An exchange of messages between the different parts can be illustrated as follows:

client -> server: ask server to perform a task
server acknowledges request and assigns an identificator to the request
server -> all workers: tell workers registered for the task that there is work to be performed
worker -> server: I'll perform the task you just told us about
server -> worker: ok, go ahead, here's the information about the task.
worker -> server: here's the result of the task performed
server -> client: here's the result of the task you asked me to get someone to do for you

The idea behind the server telling all the workers that there are work available is to let the worker that responds fastest to actually get the task, as it’s assumed that this is the worker with the least load on the server it’s running on (as it responds quickly, the server is not busy doing other things). As I wrote above, the worker is the piece of code actually doing the work – the worker performs the task that a client has submitted to the gearman server.

You’ll find that most of Gearman is designed according to the same principle – keep stuff simple. The server only needs to keep track of which workers perform which functions, and then let the workers grab a task when it becomes available.

The Gearman Client

In Gearman the client is the piece of code that connects to the server and asks for a task to be performed. This can be a dynamic web page (running in python, ruby, PHP, perl or another language with a suitable Gearman library), a completely application that connects to Gearman, a worker (to submit a new task or to divide the current task into several smaller tasks to be performed by other workers) or a combination of the above. The important part is that this is simply a client – it has a task that needs to be handled, and it’ll ask the Gearman server to find someone who can perform the task.

The client can be run in synchronous (blocking) or asynchronous (non-blocking) mode. The first will make the client wait until the task has been performed by a worker (and if no worker is available, it’ll wait indefinitely or until reaching a timeout in the client), while the latter will simply fire-and-forget the task to the Gearman server (the server will confirm that the task has been received) and then go on its merry way afterwards. The Gearman server will provide a task identification value which the asynchronous client can use to query the current state of the task it asked to be performed (as long as the actual worker provide such updates).

A small example of how a client might work (using PHP):

  1. <?php
  2. $client = new GearmanClient();
  3. $client->addServer('localhost', 4730);
  4.  
  5. $arguments = array(
  6.     'url' => 'http://www.example.com/',
  7. );
  8.  
  9. $client->addTaskBackground('fetchURL', json_encode($arguments));
  10.  
  11. $client->runTasks();

This will submit a request to a Gearman server running on the same machine as the script, asking for the function “fetchURL” to be run, and including an array of arguments to the function (you could simply include just the URL, but I find that this way is easier to extend in the future – and using JSON for data exchange makes the worker code more programming language independent). This code uses addTaskBackground to submit the task to be performed in an asynchronous manner. We’re not interested in the result of this task in this particular piece of code – the worker will either provide the result through other means (storing it in a database, in memcache, call an API function telling us that it’s finished) or perhaps we’re not interested in the result at all, just that we’ve attempted to perform the task. If you’re using the synchronous interface, the data returned from the worker will be returned to your code as the return value from the client.

As you can see, the client code is very, very simple. There is no actual work being performed here, we’re just telling the server that we’d like some work to be performed for us.

The Gearman Worker

The Gearman worker is where all the actual work (.. who’d guess) is performed. This is the application that receives a notice that it has to wake up and do a bit of hard work, and which actually goes out and does just that. What kind of work it does depends on what you’re using Gearman for, but a couple of use cases could be to resize an image into smaller sizes (such as thumbnails), to convert an uploaded video into another format for a specific device, sending notification emails, updating an internal search engine such a Solr and quite a few other tasks. As long as the task is not important for the application to continue running (no need for waiting for an E-mail to be delivered if you’re going to show a “Your information has been saved” message), then Gearman (and other alternative message queues) is a valid solution.

You’ll run each worker as its own process. A worker can perform several different functions (although you should (usually) stay away from multi-threading to perform them at the same time). This means starting several copies of the same worker if you want to allow for more than one worker performing a task at the same time (i.e., if you want to send 30 e-mails in parallel), you’ll start each worker as separate processes (30 workers in that case). There are several daemons and frameworks that can help you manage the number of processes available depending on server and task load, such as supervisord and GearmanManager (a PHP daemon). Another possible solution is to use screen to start several workers, which also will allow you to attach to the output of any worker at any time.

How the worker performs its work is up to the worker itself. In most cases you’ll have to write a bit of code to expose your code as a Gearman function (so that clients can submit tasks to perform that function), but this code will usually just instantiate the worker framework from the Gearman library you’re using, letting you register what functions you’ll be able to perform and attaching callbacks telling the library what part of your own code should be called when a request to perform a task arrives.

A simple example modified from the Gearman Getting Started guide:

  1. <?php
  2. $worker = new GearmanWorker();
  3. $worker->addServer("localhost", 4730);
  4. $worker->addFunction("fetchURL", "fetch_url");
  5.  
  6. while ($worker->work());
  7.  
  8. function fetch_url($job)
  9. {
  10.     $arguments = json_decode($job->workload());
  11.  
  12.     if (!empty($arguments['url']))
  13.     {
  14.         print("Fetching " . $arguments['url'] . "\n");
  15.         return file_get_contents($arguments['url']);
  16.     }
  17. }

The $worker->work() method call will wait until a work arrives, then execute the callback as defined in the addFunction call. addFunction instructs the worker to tell the gearman server that this worker is able to perform any tasks calling the “fetchURL” function. The callback provided to the library (“call this PHP function (‘fetch_url’) when tasks want to call ‘fetchURL’”) will then receive the job object containing information about the job (task) to be performed. The workload() method returns the workload – the information we included in addition to which function to call in the client example. The server receives the workload from the client and then sends it to the worker together with the task information.

Since our client calls the server using the asynchronous interface it’ll not wait for the worker to return the web page contents, but by using ->do() or one of the other foreground methods in the PHP Gearman library.

The Gearman Server

The Gearman Server used is usually the C version of the server. There’s also a PERL version, but these days the C server is the one being actively developed. There’s not much to say about the server, you usually just start it and let it run by itself, doing what it was supposed to do all along.

I’ve got one simple suggestion if you’re just playing around with Gearman for the first time: start the server with the -vvv option. This will make gearmand a lot noisier, and will allow you to see clients registering themselves with the server, pinging the server and getting a bit more information about what’s happening inside the server process.

You’ll also want to provide an IP address that the gearman server should bind to – by default it binds to all interfaces, and since gearmand does not have any authentication built in by default, you don’t want to expose your server to the whole world.

Here’s an example of how we start gearmand at one of our servers:

  1. screen -d -m -S gearmand /usr/local/sbin/gearmand -L 127.0.0.1 -p 4730 -vvv

You can drop the part related to screen if you just want to play with gearmand:

  1. /usr/local/sbin/gearmand -L 127.0.0.1 -p 4730 -vvv

If you have gearmand in your path and not in the same location as us, drop /usr/local/sbin :-) This will bind gearmand to your localhost and use the default port (earlier the default port was something other than 4730, so we provide it just in case).

Making it all come together

The easiest way to play around with gearman is to simply open three terminal windows: one for gearmand with logging turned on, one for your worker and its output and the last window for a client sending a task request to gearmand (you can use the ‘gearman’ binary for this, just be sure to include any data in an appropriate format). As you submit a task for a function that the worker has registered, you should see it pick it up and then start processing the task as soon as possible. After a while (depending on how you’ve implemented your worker and what function it performs) the result should appear in your client.

Our production setups usually use a web application (PHP or python/django) as the client in the above scenario. The functions are usually long running tasks, such as analysing GPS paths, encoding videos and downloading files or internal web site analytics (where we just want to get things logged and not wait for the actual logging to complete). The web application submits a request to gearmand as soon as a file has been received, with a payload of the path to the file to be processed. The workers perform their function and then store the information back into the database or to disk, then usually call a web service to tell the web application that the work has been performed and any internal state can be updated to include (and show) the result of the task.

Message queues (such as Gearman) has become one of the core technologies behind many modern web applications (and non-web applications for that matter), so there’s really no reason to avoid at least playing around a bit with it and adding another possible tool to your future options.

Solr: Replication not starting?

July 20th, 2011

After upgrading our Solr-servers from 1.4.1 to 4.0-trunk (to be sure we were ready for the next version), I had trouble with getting replication to start again. It worked perfectly back with 1.4.1, but after upgrading to 4.0-trunk, it simply wouldn’t start.

I had to upgrade the machines individually (to allow the current index to continue serve requests), I removed the replication and then directed all the traffic to the slave. After updating the master (which worked after actually remembering to clean out the old webapps from Tomcat and adding a few new settings) and reindexing, most of the traffic were directed to it, and the slave were upgraded to the new Solr-version. I turned on replication again, updated the configuration file with the needed settings and started the slave. Nothing happened. Weird.

Time to debug!

On any slaves there’s a “replication.properties” file in the data directory ($SOLRHOME/data) which contain information about the current replication status. This file were created, indicating that at least the replication was attempting to run. If you open the file in a text editor (or just cat it), you should be able to read a bit of meta information about the replication state.

replicationFailedAtList=1311072270004,1311072240006..
timesFailed=11

Seems like it’s trying, but for some reason it doesn’t work. First thing to check would be to grep for replication in the log on both the master and the slave, and see if there’s any requests being made at all. There might be, but the replication still doesn’t start.

Try fetching the current state yourself to see what response the master is serving. You can do this by using “GET” or “wget” or “curl” to make an HTTP request to the master Solr-server from the slave together with the URL from “masterUrl” in the requestHandler for /replication from solrconfig.xml:

  1. GET http://example.com/solr/replication?command=indexversion

This should respond with something close to:

  1. <?xml version="1.0" encoding="UTF-8"?>
  2. <response>
  3.   <lst name="responseHeader">
  4.     <int name="status">0</int>
  5.     <int name="QTime">0</int>
  6.   </lst>
  7.   <long name="indexversion">1310994445934</long>
  8.   <long name="generation">2</long>
  9. </response>

If “indexversion” is 0, this means that the master hasn’t triggered a replication yet, which may seem weird if you’ve just started the server and the slave doesn’t have any data at all.

The reason might be that the master has not been instructed to actually trigger a replication event (and unless a replication event has been triggered, the indexversion will be 0):

  1. <requestHandler name="/replication" class="solr.ReplicationHandler">
  2.   <lst name="master">
  3.     <str name="replicateAfter">commit</str>
  4.     <str name="replicateAfter">startup</str>
  5.     <str name="replicateAfter">optimize</str>

If you only have “commit” in the above list, a replication event will not be triggered unless you’ve actually performed a commit after the slave has connected for the first time. If you add “startup”, the replication will also be triggered when the master starts up (so that any connecting slaves will start replicating right away).

To fix the issue without restarting any nodes, issue a single commit to the master and watch as the slaves start replicating. To issue a commit through curl:

  1. curl http://example.com/solr/update -H "Content-Type: text/xml" –data-binary '<commit />'

nginx and rewriting based on GET-parameter (URL-parameters/arguments)

July 12th, 2011

When rewriting URLs in Apache through mod_rewrite, you have the possibility of using RewriteCond to only apply rewrites if the original resource has been called with a particular argument in the URL (such as “/file?oid=..”).

The solution in nginx was however a bit different, but thanks to Rewriting URL-params in nginx I got on the right track from the start.

In nginx this information is available through the $args variable, which will contain the complete query string. In Will’s example above he’ll replace the query string, but I were interested in inserting a specific parameter instead (and include the previous query string, so I couldn’t just do the “set $args ..” that he does in the example).

My first try was to simply use $1 in the rewrite destination, but this didn’t work – as rewrite will reset the captured patterns from the previous regular expression (since the rewrite source also is a regular expression). But by introducing my own, temporary variable I were able to save the value from the matching regular expression (for the GET parameter) and use it in my rewrite destination.

The following example shows how I ended up solving the issue. This will rewrite the URL only if the “oid” parameter is found at the beginning of the query string when the URL is requested, and the location = /oldURL limits the rewrite to requests for the old resource.

location = /oldURL {
    if ($args ~ "^oid=(\d+)") {
        set $key1 $1;
        rewrite ^.*$  /newURL?param1=foo&param2=bar&key1=$key1 last;
    }
}

This will rewrite a request for /oldURL?oid=123&what=cheese to /newURL?param1=foo&param2=bar&key1=123&oid=123&what=cheese — if you want to exclude the previous arguments, you can either just set $args directly to key1=$1 and just use param1=foo and param2=bar in the rewrite destination:

        set $args key1=$1;
        rewrite ^.*$  /newURL?param1=foo&param2=bar last;

This might be cleaner, depending on what you’re trying to do.