I have a “listener-container” defined like this:
<listener-container concurrency="1" connection-factory="connectionFactory" prefetch="10"
message-converter="jsonMessageConverter"
error-handler="clientErrorHandler"
mismatched-queues-fatal="true"
xmlns="http://www.springframework.org/schema/rabbit">
<listener ref="clientHandler" method="handleMessage" queue-names="#{marketDataBroadcastQueue.name}" />
</listener-container>
I want to process the messages in sequential order, so I need to set concurrency to 1.
But the bean “clientHandler” has more than one “handleMessage” methods (with diferent java classes as parameters). I can see in the application logs that messages are not processed one by one. I have several messages processed in parallel. Can it be due to having multiple methods with the same name that processes those messages?
Thanks!
Related
I'd like to process a list of custom java objects , split those using camel splitter and like to process it in parallel threads. But the challenge I am facing is ,list of custom objects is ordered based on Id, which has to be written in a file.
As soon as I use parallel processing, the sequence is disturbed. I went through a few articles which asked to use "resequencer" or "single thread".
But using single thread, it takes huge time to process 5k records.
Any leads would be highly helpful.
Thanks
Nitin
I had similar kind of problem while Splitting a XMl request based on a tag "XXX". Then processing the splitted request and Aggregating into a Response.
The order of the Aggregated response is not same as the request.
FIX : The issue has been resolved by using Aggregation "strategyRef" in splitter EIP.
Sample Code:
<route>
<from id="_from1" uri="activemq:DocumentGenerationQueue" />
<split parallelProcessing="true" streaming="false" strategyRef = "AggregateTask" >
<tokenize token="XXX" xml="true" />
<to id="_to71" uri="bean:ProcessorBean" />
<to id="_to72" uri="activemq:SplittedResponseQueue" />
</split>
<to uri="activemq:AggregatedResponseQueue" />
</route>
You can create an instance of AggregationStrategy that compares the results of newExchange and oldExchange and create a resultExchange with sorted list of custom java objects based on id.
But using single thread, it takes huge time to process 5k records.
You have to be careful as you may not want to spin up 5k parallel threads but instead create your own thread pool attach it in the split with executorServiceRef. This way you can control the number of threads and handle what to do when your queue is full.
I have a huge xml that come as an input payload to my Spring integration flow. So I am using claim check in transformer instead of header enricher to retain my payload. I am using an in-memory message store.
Later on in my SI flow, I have a splitter that splits the payload into multiple threads and each thread will invoke different channel based on one of the attribute payload. I am using a router for achieve this. Each flow or each thread uses a claim check out transformer to retrieve the initial payload then us it for building the required response. Each thread will produce a response and I don't have to aggregate them. So I will have multiple responses coming out from my flow which will then be dropped into a queue.
I cannot remove the message during the check out as other thread will also try to check out the same message. What is the best way to remove the message from the message store?
Sample configuration
`<int:chain input-channel="myInputChannel"
output-channel="myOutputchannel">
<int:claim-check-in />
<int:header-enricher>
<int:header name="myClaimCheckID" expression="payload"/>
</int:header-enricher>
</int:chain>`
all the other components in the flow are invoked before the splitter
<int:splitter input-channel="mySplitterChannel" output-channel="myRouterChannel" expression="mySplitExpression">
</int:splitter>
`<int:router input-channel="myRouterChannel" expression="routerExpression"
resolution-required="true">
<int:mapping value="A" channel="aChannel" />
<int:mapping value="B" channel="bChannel" />
<int:mapping value="C" channel="cChannel" />
</int:router>`
Each channel has a claim check out transformer for the initial payload. So how do I make sure the message is removed after all the threads have been processed?
When you know you are done with the message you can simply invoke the message store's remove() method. You could use a service activator with
... expression="#store.remove(headers['myClaimCheckID'])" ...
However, if you are using an in-memory message store there is really no point in using the claim check pattern.
If you simply promote the payload to a header, it will use no more memory than putting it in a store.
Even if it ends up in multiple messages on multiple threads, it makes no difference since they'll all be pointing to the same object on the heap.
I have multiple Queues and I want to use a single Gateway. I have default channel. Is there a simple way to define multiple source of Queues.
In this case "Simple" is defined as simplicity of runtime complexity than configuration.
Looks like you need RecipientListRouter:
<int:recipient-list-router input-channel="routingChannel">
<int:recipient channel="queue1"/>
<int:recipient channel="queue2"/>
</int:recipient-list-router>
I am using Spring Integration and have a large XML file containing a collection of child items, I want to split the file into a set of messages, the payload of each message will be one of the child XML fragments.
Using splitter is the obvious but this requires returning a collection of messages and this will exhaust the memory; I need to split the file into individual messages but process them one at a time (or more likely with a multi threaded task-executor).
Is there a standard way to do this without writing a custom component that writes the sub-messages to a channel programatically.
i have been looking for a similar solution and I have not found either any standard way of doing this.
Here is a rather dirty fix, if anyone needs this behavior implemented:
Split the files manually using a Service Activator or a Splitter with a custom bean.
<int:splitter input-channel="rawChannel" output-channel="splitChannel" id="splitter" >
<bean class="com.a.b.c.MYSplitter" />
</int:splitter>
Your custom bean should implement ApplicationContextAware so the application context can be injected by Spring.
Manually retrieve the output channel and send each sub-message
MessageChannel xsltChannel = (MessageChannel) applicationContext.getBean("splitChannel");
Message<String> message = new GenericMessage<String>(payload));
splitChannel.send(message);
For people coming across this very old question. Splitters can now handle results of type Iterable, Iterator, Stream, and Flux (project reactor). If any of these types are returned, messages are emitted one-at-a-time.
Iterator/Iterable since 4.0.4; Stream/Flux since 5.0.0.
There is also now a FileSplitter which emits file contents a line-at-a-time via an Interator - since 4.1.2.
I have a queue channel, and a service activator with a poller which reads from that queue. I'd like to have configuration to say "I want 50 threads to poll that queue, and each time you poll and get a message back, on this thread, invoke the service the service-activator points to."
The service has no #Async annotations, but is stateless and safe to run in a concurrent fashion.
Will the below do that? Are there other preferred ways of achieving this?
<int:channel id="titles">
<int:queue/>
</int:channel>
<int:service-activator output-channel="resolvedIds" ref="searchService" method="searchOnTitle" input-channel="titles">
<int:poller fixed-delay="100" time-unit="MILLISECONDS" task-executor="taskExecutor"></int:poller>
</int:service-activator>
<task:executor id="taskExecutor" pool-size="50" keep-alive="120" />
Yes I think it does what you want. Once you introduce a QueueChannel the interaction becomes async - you don't need #Async. If you don't explicitly set up a poller it will use the default poller.
What you have outlined is the best way to achieve it. You might also consider putting a limit on the queue size - so that in case there is a lag in keeping up with the producer it doesn't lead to out of memory issue. If a size is specified then the send calls on the channel will block - acting as a throttle.
The configuration you have will work as you expect. The only issue is that once you start creating executors and pollers for each end point it becomes difficult to figure out the optimal configuration for the entire application. It is ok to do this kind of optimization for a few specific steps - but not for all the endpoints (nothing in you questions suggests that you are doing it, just thought that I will raise it anyway.