84.8. Event streams and entry points

The decision engine can process high volumes of events in the form of event streams. In DRL rule declarations, a stream is also known as an entry point. When you declare an entry point in a DRL rule or Java application, the decision engine, at compile time, identifies and creates the proper internal structures to use data from only that entry point to evaluate that rule.

Facts from one entry point, or stream, can join facts from any other entry point in addition to facts already in the working memory of the decision engine. Facts always remain associated with the entry point through which they entered the decision engine. Facts of the same type can enter the decision engine through several entry points, but facts that enter the decision engine through entry point A can never match a pattern from entry point B.

Event streams have the following characteristics:

  • Events in the stream are ordered by time stamp. The time stamps may have different semantics for different streams, but they are always ordered internally.
  • Event streams usually have a high volume of events.
  • Atomic events in streams are usually not useful individually, only collectively in a stream.
  • Event streams can be homogeneous and contain a single type of event, or heterogeneous and contain events of different types.

84.8.1. Declaring entry points for rule data

You can declare an entry point (event stream) for events so that the decision engine uses data from only that entry point to evaluate the rules. You can declare an entry point either implicitly by referencing it in DRL rules or explicitly in your Java application.

Procedure

Use one of the following methods to declare the entry point:

  • In the DRL rule file, specify from entry-point "<name>" for the inserted fact:

    Authorize withdrawal rule with "ATM Stream" entry point

    rule "Authorize withdrawal"
when
  WithdrawRequest($ai : accountId, $am : amount) from entry-point "ATM Stream"
  CheckingAccount(accountId == $ai, balance > $am)
then
  // Authorize withdrawal.
end

    Apply fee rule with "Branch Stream" entry point

    rule "Apply fee on withdraws on branches"
when
  WithdrawRequest($ai : accountId, processed == true) from entry-point "Branch Stream"
  CheckingAccount(accountId == $ai)
then
  // Apply a $2 fee on the account.
end

    Both example DRL rules from a banking application insert the event WithdrawalRequest with the fact CheckingAccount, but from different entry points. At run time, the decision engine evaluates the Authorize withdrawal rule using data from only the "ATM Stream" entry point, and evaluates the Apply fee rule using data from only the "Branch Stream" entry point. Any events inserted into the "ATM Stream" can never match patterns for the "Apply fee" rule, and any events inserted into the "Branch Stream" can never match patterns for the "Authorize withdrawal rule".

  • In the Java application code, use the getEntryPoint() method to specify and obtain an EntryPoint object and insert facts into that entry point accordingly:

    Java application code with EntryPoint object and inserted facts

    import org.kie.api.runtime.KieSession;
import org.kie.api.runtime.rule.EntryPoint;

// Create your KIE base and KIE session as usual.
KieSession session = ...

// Create a reference to the entry point.
EntryPoint atmStream = session.getEntryPoint("ATM Stream");

// Start inserting your facts into the entry point.
atmStream.insert(aWithdrawRequest);

    Any DRL rules that specify from entry-point "ATM Stream" are then evaluated based on the data in this entry point only.