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From "Claus Ibsen (JIRA)" <>
Subject [jira] Commented: (CAMEL-3337) Aggregator using an unbounded queue, can use up all heap
Date Sun, 14 Nov 2010 07:55:24 GMT


Claus Ibsen commented on CAMEL-3337:

If you set core pool size and max pool size to 0 then Camel will created a synchronous queue,
eg using the same thread.
 <threadPoolProfile id="myAgg" poolSize="0" maxPoolSize="0"/>

And then refer to it from the aggregator
<aggregate strategyRef="myAggregationStrategy" executorServiceRef="myAgg">

> Aggregator using an unbounded queue, can use up all heap
> --------------------------------------------------------
>                 Key: CAMEL-3337
>                 URL:
>             Project: Apache Camel
>          Issue Type: Improvement
>          Components: camel-core
>    Affects Versions: 2.5.0
>         Environment: JDK 1.6.0_22 (Windows 7 64-bit and OS X 10.6.5)
>            Reporter: Bryan Keller
>            Priority: Minor
> My app is having memory issues due to the use of an aggregator. My app is fairly straightforward.
It reads from a CSV using streaming, tokenizes it by line, passes the result to a processor,
aggregates the result, then puts this on a JMS queue. Here is the route definition (for Spring):
> {code:xml}
> <route>
>   <from "file:in" />
>   <split streaming="true">
>     <tokenize token="\n" regex="false" />
>     <unmarshal><csv /></unmarshal>
>     <bean ref="myBean" method="translate" />
>     <aggregate strategyRef="myAggregationStrategy">
>     <correlationExpression><constant>true</constant></correlationExpression>
>     <completionTimeout><simple>1000</simple></completionTimeout>
>     <completionSize><simple>100</simple></completionSize>
>     <to uri="activemq:queue:myQueue"/>   		
>   </aggregate>
>   </split>
> </route>
> {code}
> The problem happens when the consumer of "myQueue" is not as fast as the file reading
and parsing. With a slow consumer, ActiveMQ will eventually throttle the producer so the message
queue doesn't use up all memory and/or disk space.
> As messages are passed to the aggregator, it internally submits jobs to an executor which
will then put the message in the queue. This executor uses an unbounded queue. If the message
producer has been throttled, then the process jobs cannot queue the messages quickly enough,
and the executor's queue will continue to back up until all memory is used.
> As a workaround, I am thinking I could implement my own executor service which is synchronous
or at least blocks when the queue size reaches a certain size. I haven't yet firgured out
how to configure this however.

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