Hello, I am looking for feedback on a computation design.
Im designing a scoring engine for a large set of entities stored in some datastore. a request comes in with the computation parameters, and those parameters need to be applied to the entities stored as rows in the datastore. the computation computes a score for each row, and we need to return the top scoring row. and it needs to be snappy to respond to a user application. some in-memory database is one approach. however, the only data that really changes is the request parameters. therefore, I was looking to have one actor hold the data for a single row, to be uploaded from a disk-based db when the server is started. this means 10,000 to 100,000 data worker actors, which are routees of comparator actors, which are routees of request serving actors. request comes in, and its passed down (broadcasted) to the workers, they calculate a score on the data they hold, and send the score along with the rowID back up the chain. is this a viable approach? or is the message passing overhead way too high in this case? -- >>>>>>>>>> Read the docs: http://akka.io/docs/ >>>>>>>>>> Check the FAQ: >>>>>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html >>>>>>>>>> Search the archives: https://groups.google.com/group/akka-user --- You received this message because you are subscribed to the Google Groups "Akka User List" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at http://groups.google.com/group/akka-user. For more options, visit https://groups.google.com/d/optout.
