Additional SOA Patterns –Supporting Composition Controllers - Applied SOA Patterns on the Oracle Platform - page 577

Some may say that CQL processors (or bean processors) are not completely aligned with
the classic ESB pattern. Well, you will not find OSB XQuery in the Canonical ESB pat-
terns catalog either; it's just a tool that supports ESB VETRO operations in this matter. In
ESB, we can also call Java Beans when it's necessary for message processing (we demon-
strated this in Chapter 4 , From Traditional Integration to Composition - Enterprise Busi-
ness Services ); for instance, doing complex sorts in Java Collections is far easier than in
XML/XSLT, and it is worth the serialization/deserialization efforts. In a similar way, EDN
extends the classic ESB by providing the following functionalities:
• Continuous Query Language
• It operates on multiple streams of disparate data
• It joins the incoming data with persisted data
• It has the ability to plug in to any type of adapter
• It has the ability to plug to any type of adapters
Combined together, all these features can cover almost any range of practical challenges,
and the logistics example we used here in this chapter is probably too insignificant for
such a powerful event-driven platform; however, for a more insightful look at Oracle CEP,
refer to Getting Started with Oracle Event Processing 11g , Alexandre Alves , Robin J.
Smith, Lloyd Williams , Packt Publishing . Using exactly the same principles and patterns,
you can employ the already existing tools in your arsenal in the way we demonstrated in
Chapter 6 , Finding the Compromise - the Adapter Framework (exactly as we did for this
shipping company). The world is apparently bigger, and this tool can demonstrate all its
strength in the following use cases:
• As already mentioned, Cablecom Enterprise strives to improve the overall cus-
tomer experience (not only for VOD). It does so by gathering and aggregating in-
formation about user preferences through the purchasing history, watch lists,
channel switching, activity in social networks, search history and used meta tags
in search, other user experiences from the same target group, upcoming related
public events (shows, performances, or premieres), and even the duration of the
cursor's position over certain elements of corporate web portals. The task is com-
plex and comprises many activities, including meta tag updates in metadata stor-
age that depend on new findings for predicting trends and so on; however, here
we can tolerate (to some extent) the events that aren't processed or are not re-
ceived.
• For bank transaction monitoring, we do not have such a luxury. All online events
must be accounted and processed with the maximum speed possible. If the last
transaction with your credit card was at Bond Street in London, (ATM cash with-
drawal) and 5 minutes later, the same card is used to purchase expensive jew-