Yes, dividing it into chunks is a good practice. This adheres to
message-based systems in general, not specific to Camel.
Let's discuss both ways of processing messages:
1. One big message
Say the message is 100 GB+ and this is processed by some integration
software on a server, you need to scale the server
for that amount. This means both memory and CPU must be capable of doing
processing so amount of data. When you want to perform
EIP's (like filters or transformation) this will be difficult, because the
needed resources to match that.
Say this big message comes one's a week, then you have a very big server
basically run for nothing.
2. Many small messages
Because of 1 it's generally the best practice to have fixed sized smaller
messages. When possible, directly on the source.
If this is somehow not possible, you can split them and move it back to a
Kafka topic, then you use streaming the messages
and do the actual EIP's on the small message. Some advantages are:
1. Predictable: Every message is of the same size, so you load test this
and match resources.
2. Resources: A small message needs less resources (CPU/Memory) to process
3. Load: The load is spread over time (you can use a smaller server).
4. Realtime: You don't need to wait until all data is gathered and then
send it in batch, but
you can process it when it happens.
5. Scaling: When the load is high, you may add multiple threads or even
multiple pods/containers to scale, when you
don't need it anymore, you can scale back.
Raymond
On Thu, Jan 25, 2024 at 2:32 PM Ghassen Kahri <ghassen.ka...@codeonce.fr>
wrote:
> Hello community,
>
> I am currently working on a feature within the Camel project that involves
> processing Kafka messages (String) and performing a query based on that
> message. Initially, I implemented a classic route that called a service
> method responsible for executing the query. However, I encountered an issue
> with the size of the query result, as the memory couldn't handle such a
> massive amount of data.
>
> In response to this challenge, I devised an alternative solution that might
> be considered unconventional. The approach involves querying the database
> multiple times and retrieving the results in manageable chunks.
> Consequently, the route needs to be executed multiple times. The current
> structure of my route is as follows:
>
>
> from(getInput())
> .routeId(getRouteId())
>
> .bean(Service.class, "extractDataInChunks")
>
> .choice()
>
> .when(header(PAGINATION_END_FLAG).isEqualTo(true)).to(getOutput())
>
>
> .when(header(PAGINATION_END_FLAG).isEqualTo(false)).to(getOutput(),directUri(getRouteId()));
> //re-execute the route with offset = offset+limit
>
>
> The extractDataInChunks method queries the database with a parameterized
> limit (chunk size) and an offset that ranges from 0 to X * limit. The
> PAGINATION_END_FLAG is a Camel header, initially set to false, and is
> switched to true by the extractDataInChunks method if the size of the query
> result is 0.
>
> I would appreciate feedback on whether this solution adheres to good Camel
> practices, specifically the consideration of implementing business logic at
> the route level. Additionally, I am curious if there are any built-in
> Enterprise Integration Patterns (EIPs) in Camel that might be more suitable
> for my business requirements.
>
> Thank you for your insights.
>
