Skip to main content

BlockingQueue to prevent OOM

Saw an interesting hack when a colleague sent me his code for review. We are a cloud storage company and people upload files and if they upload same file again and again it creates a new version. Some examples are quickbooks or outlook files that will generate multiple versions in a day if you have enabled real time sync on that folder where these files are stored. To optimize bandwidth we use rsync and do a  patch on server to reconstruct these large files but as we save the original file the customer gets charged the full size of the file. This is why customers configure version policy that they would allow 5 versions of the file and if a new one is uploaded we move the oldest to trash.  Now if the customer reduced the versions to keep from 5 to 2 then suddenly we have to delete all these versions.

So earlier to offload processing we had written a rest api that in streaming fashion would return list of deletable versions metadata.

/rest/public/getDeletableVersions   GET.

then a python script would call deleteVersions api in batch.

/rest/public/deleteVersions POST

now this was all complex to test so after 2 years we moved it back to tomcat and rewrote this as a quartz job.

so the programmer reused the code and wrote it as

List<DeletableVersionResponse> deletableVersions = storageService.getDeletableVersions(customerId);



 for(List<DeletableVersionResponse> batch: split(deletableVersions) ) {

   storageService.deleteVersions(batch) ;

}

Problem is that for bigger customers that had 10M+ versions this was causing OOM when we were trying to load all deletable versions.

So I asked the engineer to convert it in such a manner that the api would be
int numDeleted;
while((numDeleted=storageService.deleteNextBatchOfDeletableVersions(customerId))>0) {

}



but this required change in all the layers.



Instead the engineer came up with solution to use BlockingQueue.



So  what he did was

        BlockingQueue<DeletableVersionResponse> deletableVersionResponse = new ArrayBlockingQueue<DeletableVersionResponse>(
                eventBatchSize);
        Future future = executorService.submit(new DeletableVersionRequest(deletableVersionResponse, customerId));
        while (!(deletableVersionResponse.isEmpty() && future.isDone())) {
            processDeletableVersionResponse(user, deletableVersionResponse.poll());
        }

This was a creative way to solve OOM without changing a lot of layers of code.

Comments

Popular posts from this blog

RabbitMQ java clients for beginners

Here is a sample of a consumer and producer example for RabbitMQ. The steps are
Download ErlangDownload Rabbit MQ ServerDownload Rabbit MQ Java client jarsCompile and run the below two class and you are done.
This sample create a Durable Exchange, Queue and a Message. You will have to start the consumer first before you start the for the first time.

For more information on AMQP, Exchanges, Queues, read this excellent tutorial
http://blogs.digitar.com/jjww/2009/01/rabbits-and-warrens/

+++++++++++++++++RabbitMQProducer.java+++++++++++++++++++++++++++
import com.rabbitmq.client.Connection; import com.rabbitmq.client.Channel; import com.rabbitmq.client.*; public class RabbitMQProducer { public static void main(String []args) throws Exception { ConnectionFactory factory = new ConnectionFactory(); factory.setUsername("guest"); factory.setPassword("guest"); factory.setVirtualHost("/"); factory.setHost("127.0.0.1"); factory.setPort(5672); Conne…

Logging to Graphite monitoring tool from java

We use Graphite as a tool for monitoring some stats and watch trends. A requirement is to monitor impact of new releases as build is deployed to app nodes to see if things like
1) Has the memcache usage increased.
2) Has the no of Java exceptions went up.
3) Is the app using more tomcat threads.
Here is a screenshot

We changed the installer to log a deploy event when a new build is deployed. I wrote a simple spring bean to log graphite events using java. Logging to graphite is easy, all you need to do is open a socket and send lines of events.
import org.slf4j.Logger;import org.slf4j.LoggerFactory; import java.io.OutputStreamWriter; import java.io.Writer; import java.net.Socket; import java.util.HashMap; import java.util.Map; public class GraphiteLogger { private static final Logger logger = LoggerFactory.getLogger(GraphiteLogger.class); private String graphiteHost; private int graphitePort; public String getGraphiteHost() { return graphiteHost; } public void setGraphite…

What a rocky start to labor day weekend

Woke up by earthquake at 7:00 AM in morning and then couldn't get to sleep. I took a bath, made my tea and started checking emails and saw that after last night deployment three storage node out of 100s of nodes were running into Full GC. What was special about the 3 nodes was that each one was in a different Data centre but it was named same app02.  This got me curious I asked the node to be taken out of rotation and take a heap dump.  Yesterday night a new release has happened and I had upgraded spymemcached library version as new relic now natively supports instrumentation on it so it was a suspect. And the hunch was a bullseye, the heap dump clearly showed it taking 1.3G and full GCs were taking 6 sec but not claiming anything.



I have a quartz job in each jvm that takes a thread dump every 5 minutes and saves last 300 of them, checking few of them quickly showed a common thread among all 3 data centres. It seems there was a long running job that was trying to replicate pending…