This chapter is from the book
This chapter is from the book
This chapter is from the book
6.8 Aggregator
Aggregator [EIP] is a special Filter that collects related messages until some completeness condition has been reached, at which point it processes the related messages to obtain a single aggregated message that is then passed on to the next component.
An Aggregator must be able to correlate related messages, store related messages until ready to process, determine when the completeness condition is met, and implement the aggregation logic.
Java CAPS eInsight engine is a convenient tool to use for building Aggregators, as it inherently supports correlations and transparently stores related messages. The specific eInsight Business Process must only implement the completeness condition and the aggregation logic in order to become a specific Aggregator.
At the heart of every Aggregator is correlation logic, logic that determines which messages are related and therefore are subject to aggregation. Chapter 11 discusses at length the topic of message correlation with references to a number of specific examples presented in Part II (located on the accompanying CD-ROM). Chapter 11, section 11.10, discusses in detail a number of correlation implementations that incorporate an Aggregator.
Implementing an Aggregator without the benefit of eInsight is much harder. In addition to having to implement a completeness condition and aggregation logic, the solution designer must also do all the work related to storing and correlating messages. Chapter 11, section 11.11, discusses this topic and presents an example of how to accomplish the task of storing and correlating messages using just eGate and the Sun SeeBeyond JMS Message Server.
[EIP] discusses a number of completeness conditions an Aggregator might implement: Wait for All, Timeout, First Best, Timeout with Override, and External Event. Variants of these completeness conditions are discussed in Chapter 11, section 11.10. Implementing these conditions using eInsight with correlations is rather trivial. Implementing most of them using just eGate is much more difficult.
[EIP] also discusses a number of aggregation algorithms, including Select Best, Condense, and Collect for Later. Variants of these are also discussed in Chapter 11, section 11.10. Since aggregation will not start until all related messages are collected—that is, until the completeness condition has been satisfied—implementing aggregation logic is equally simple whether eInsight or eGate is used.