In this example it has been assumed to use a domain model consisting of a Student who has a Plan of study: a Plan can have zero or more Exams and an Exam zero or more Grades. Note that only the root object of the graph (the Student in this case) needs to be in the working memory in order to make this works.

By borrowing ideas from XPath, this syntax can be made more succinct, as XPath has a compact notation for navigating through related elements while handling collections and filtering constraints. This XPath-inspired notation has been called OOPath since it is explictly intended to browse graph of objects. Using this notation the former example can be rewritten as it follows:

Formally, the core grammar of an OOPath expression can be defined in EBNF notation in this way.

OOPExpr = "/" OOPSegment { ( "/" | "." ) OOPSegment } ;
OOPSegment = [ID ( ":" | ":=" )] ID ["[" Number "]"] ["{" Constraints "}"];

In practice an OOPath expression has the following features.

In this case, since the query is passive, it shouldn't react to the insertion of a String matching the join condition in the query itself. In other words this sequence of commands

KieSession ksession = ...
ksession.insert(1);
ksession.insert("1");
ksession.fireAllRules();

shouldn't cause the rule R to fire because the String satisfying the query condition has been inserted after the Integer and the passive query shouldn't react to this insertion. Conversely the rule should fire if the insertion sequence is inverted because the insertion of the Integer, when the passive query can be satisfied by the presence of an already existing String, will trigger it.

Unfortunately the lazy nature of PHREAK doesn't allow the engine to make any distinction regarding the insertion sequence of the two facts, so the rule will fire in both cases. In circumstances like this it is necessary to evaluate the rule eagerly as done by the old RETEOO-based engine.

In other cases it is required that the propagation is eager, meaning that it is not immedate, but anyway has to happen before the engine/agenda starts scheduled evaluations. For instance this is necessary when a rule has the no-loop or the lock-on-active attribute and in fact when this happens this propagation mode is automatically enforced by the engine.

To cover these use cases, and in all other situations where an immediate or eager rule evaluation is required, it is possible to declaratively specify so by annotating the rule itself with @Propagation(Propagation.Type), where Propagation.Type is an enumeration with 3 possible values:

This means that the following drl:

will make the rule R to fire if and only if the Integer is inserted after the String, thus behaving in accordance with the semantic of the passive query.

The People Perspective is the home page of an user. Showing his infos (including a gravatar picture from user e-mail), user connections (people that user follow) and user recent activities. There is also a way to edit an user info. The search suggestion can be used to navigate to a user profile, follow him and see his updates on your timeline.

The table is used in the following scenarios:

or programmatically using the KieModuleModel.

KieContainers can be dynamically updated to a specific version, and resolved through Maven if KIE-CI is on the classpath. For stateful KieSessions the existing sessions are incrementally updated.

In this example the KieScanner is configured to run with a fixed time interval, but it is also possible to run it on demand by invoking the scanNow() method on it. If the KieScanner finds, in the Maven repository, an updated version of the Kie project used by that KieContainer it automatically downloads the new version and triggers an incremental build of the new project. From this moment all the new KieBases and KieSessions created from that KieContainer will use the new project version.

It is also possible to have a finer grained control on the timed rules that have to be automatically executed. To do this it is necessary to set a FILTERED TimedRuleExectionOption that allows to define a callback to filter those rules, as done in the next example.

The expressions, $d and $p in this case, can use any variable defined in the pattern matching part of the rule and can be any String that can be parsed in a time duration or any numeric value that will be internally converted in a long representing a duration expressed in milliseconds.

Both interval and expression timers can have 3 optional parameters named "start", "end" and "repeat-limit". When one or more of these parameters are used the first part of the timer definition must be followed by a semicolon ';' and the parameters have to be separated by a comma ',' as in the following example:

The value for start and end parameters can be a Date, a String representing a Date or a long, or more in general any Number, that will be transformed in a Java Date applying the following conversion:

new Date( ((Number) n).longValue() )

Conversely the repeat-limit can be only an integer and it defines the maximum number of repetitions allowed by the timer. If both the end and the repeat-limit parameters are set the timer will stop when the first of the two will be matched.

The using of the start parameter implies the definition of a phase for the timer, where the beginning of the phase is given by the start itself plus the eventual delay. In other words in this case the timed rule will then be scheduled at times:

start + delay + n*period

for up to repeat-limit times and no later than the end timestamp (whichever first). For instance the rule having the following interval timer

timer ( int: 30s 1m; start="3-JAN-2010" )

will be scheduled at the 30th second of every minute after the midnight of the 3-JAN-2010. This also means that if for example you turn the system on at midnight of the 3-FEB-2010 it won't be scheduled immediately but will preserve the phase defined by the timer and so it will be scheduled for the first time 30 seconds after the midnight. If for some reason the system is paused (e.g. the session is serialized and then deserialized after a while) the rule will be scheduled only once to recover from missing activations (regardless of how many activations we missed) and subsequently it will be scheduled again in phase with the timer.