Drools DRL: Fewer larger rules vs many smaller rules - drools

I have many rule constraints that can be logically grouped together by "or". For example: 3 rules "r1", "r2" and "r3". I can construct a single LHS as:
(r1 || r2 || r3)
Or I can make each of them a separate rule. I have no critical functional requirement for doing it either way since I can detect their grouping independently outside of Drools.
I wonder if one way is more advantageous than the other from runtime execution perspective (performance, memory, etc.).

A disjunction at pattern level is handled very much like two different rules, so there's not much gained or lost either way.
But from a maintenance and development point of view, two separate rules require two copies of the right hand side, so using a disjunction in a single rule appears to be preferable.
Establishing binding variables used to be a little tricky but I think that recent versions (6.x) of Drools handle that satisfactorily.
Note that disjunctions at constraint level should definitely not be split into separate rules.

Related

Best practice to represent Object tree in Drools

We are working on a monitoring application in which we follow the processing of a task in a set of applications.
Each application task processing is designed as ChainStep, the whole task process is designed as Chain.
Chain contains a tree of ChainSteps, each ChainStep may be parent of others.
We have a set of drools rules matching our needs but we have some performance issues (we may have easily up to 50k objects in session).
We are looking for best practices to improve drools performances.
Currently we represent Chains and ChainSteps as flat objects, each object has Id (GUID), we frequently have rule with conditions such as:
rule "Chain_App1_LinkToParent"
when $app1Step:App1ChainStep(!HasParent )
$app2Step:App2ChainStep($app2Step.ChainId == $app1Step.ChainId)
then
modify($app1Step) {
setParent($app2Step.getId()),
setHasParent(true)
}
end
(App1ChainStep and App2ChainStep both extends ChainStep type)
We tried to use unification but rules processing seems slower
when $app1Step:App1ChainStep(!HasParent, $Id:=ChainId )
$app2Step:App2ChainStep($Id:=ChainId)
We are working now on a non flat representation, but we encounter problems on rules triggering on object modifications.
For example:
rule "SetChainCollectable"
when
$chain:Chain(!Collectable )
not ( exists( $chainStep:ChainStep( !Collectable) from $chain.Steps))
then
modify($chain){
setCollectable(true)
}
end
seems not triggered on ChainStep modification of Collectable flag.
We would like to sure to obtain a better result before to finnish to migrate our rules.
What would be the more efficient way to represent object tree in Drools ?
For designing an efficient fact representation all use cases and their frequencies must be taken into account. (What you've let out in your question is far from the mark.) So I can only point out a few oddities I've observed:
Maintaining a parent and a hasParent could be simplified. Most of the time, IDs have a null value, NULL or 0 etc. Perhaps you should object references rather than ID values.
Unification isn't useful for the rule pattern you have there.
not( exists() ) is redundant - not() is the negative existence quantifier all by itself. (Drools discards the exists in this situation.)
from <expression> iterating over some POJOs (not facts) in a collection creates what I call "temporary facts", which, as facts, are limited to the context of the condition where the from clause is written. Thus, the Engine is not aware of any modification of a ChainStep object. ChainStep objects must be facts if you expect rules to react to their modification.
Basically, representing graphs by nodes as facts and with references to neighbours - up or down, or up and down, perhaps even including siblings, if it is a tree - is the way to go. But I'm not going to say more - see the initial paragraph.

Is that "modify()" or "update()" necessary in a drools rule?

I have two rules, they have same salience,same LHS but different RHS. I want the two rule will be both executed. However, both of them will make the LHS pattern can not be matched again. If I use modify() or update(), there must be one of them can not be executed.
Is there some strategy that making the drools know that the working Memory has been changed after all RHS have been executed?
One could argue that having two rules with the same LHS is poor design. This is especially so if the RHS of one or the other intends to modify one or more of the participating facts.
So the first advice is: combine the right hand sides so that you have a single rule.
The next best would be to make the firing order deterministic. Use salience in both, so that their relative oder is guaranteed. Move all update/modify calls to the rule with lower salience.
Finally, there's no need to use update/modify if the changes need not be "seen" by the rule engine. This (what I call) "dirty update" is handy where information should be accumulated but does not have any influence on LHS logic.

Drools conditions in the consequence: Benefits or Costs?

I am new to drools with a background in java. I have gained a basic undertanding of drools.
I have inherited a large drools project which works, but appears to be hacked together. Most of the rules have many and nested IF and ELSE statements in the "then" (consequence?). I believe this is bad practice. Can anyone confirm, references to materials on the internet would be useful.
Also what are the benefits in correcting this other than readability?
I'd have to dig for references but the general consent among rule programmers is that decisions should be made on the LHS/condition part of a rule. The simple reason is that the Engine is dedicated to the process of "many pattern/many object" pattern match problem. Even if there is one final condition where some action is necessary for both, true and false, Drools syntax provides a good solution, i.e., extending a rule twice, once with the positive and once with the negative condition.
That said, an occasional conditional statement may be tolerated or even fine, e.g., when it merely distinguishes between details in the works of the RHS/consequence part of a rule. But "many and nested" sounds rather bad - but maybe this "distinction of the details" does require such logic.
As for the benefits: nobody can tell without inspection, and then it'll need an experienced judge.
Since you've asked for references: http://www.redhat.com/rhecm/rest-rhecm/jcr/repository/collaboration/sites%20content/live/redhat/web-cabinet/home/resourcelibrary/whitepapers/brms-design-patterns/rh:pdfFile.pdf
One non-readability reasoning for putting as much evaluation in the LHS as possible is performance. For one thing it avoids unnecessary rule activations, but it also makes significant performance gains through caching the results of each of the matches, thereby avoiding re-evaluation.
This caching is not available to conditional logic on the RHS.
This is one reason why you invoke update/modify on a fact when you change it. This effectively instructs the engine that previously cached LHS evaluations relating to that fact can be discarded.
Nested "if/else" statements are generally not bad practice as logical operations are not stressful on the CPU, nor does it require copious amounts of memory.
I'm not a Drools programmer, but I imagine, since you alluded it to Java, it's an obj-oriented high-level prgramming language.
Howver, in the event that multiple if statements can be combined, it's recommended to do so for clear, clean coding, not necessarily performance.

How to start working with a large decision table

Today I've been presented with a fun challenge and I want your input on how you would deal with this situation.
So the problem is the following (I've converted it to demo data as the real problem wouldn't make much sense without knowing the company dictionary by heart).
We have a decision table that has a minimum of 16 conditions. Because it is an impossible feat to manage all of them (2^16 possibilities) we've decided to only list the exceptions. Like this:
As an example I've only added 10 conditions but in reality there are (for now) 16. The basic idea is that we have one baseline (the default) which is valid for everyone and all the exceptions to this default.
Example:
You have a foreigner who is also a pirate.
If you go through all the exceptions one by one, and condition by condition you remove the exceptions that have at least one condition that fails. In the end you'll end up with the following two exceptions that are valid for our case. The match is on the IsPirate and the IsForeigner condition. But as you can see there are 2 results here, well 3 actually if you count the default.
Our solution
Now what we came up with on how to solve this is that in the GUI where you are adding these exceptions, there should run an algorithm which checks for such cases and force you to define the exception more specifically. This is only still a theory and hasn't been tested out but we think it could work this way.
My Question
I'm looking for alternative solutions that make the rules manageable and prevent the problem I've shown in the example.
Your problem seem to be resolution of conflicting rules. When multiple rules match your input, (your foreigner and pirate) and they end up recommending different things (your cangetjob and cangetevicted), you need a strategy for resolution of this conflict.
What you mentioned is one way of resolution -- which is to remove the conflict in the first place. However, this may not always be possible, and not always desirable because when a user adds a new rule that conflicts with a set of old rules (which he/she did not write), the user may not know how to revise it to remove the conflict.
Another possible resolution method is prioritization. Mark a priority on each rule (based on things like the user's own authority etc.), sort the matching rules according to priority, and apply in ascending sequence of priority. This usually works and is much simpler to manage (e.g. everybody knows that the top boss's rules are final!)
Prioritization may also be used to mark a certain rule as "global override". In your example, you may want to make "IsPirate" as an override rule -- which means that it overrides settings for normal people. In other words, once you're a pirate, you're treated differently. This make it very easy to design a system in which you have a bunch of normal business rules governing 90% of the cases, then a set of "exceptions" that are treated differently, automatically overriding certain things. In this case, you should also consider making "?" available in the output columns as well.
One other possible resolution method is to include attributes in each of your conditions. For example, certain conditions must have no "zeros" in order to pass (? doesn't matter). Some conditions must have at least one "one" in order to pass. In other words, mark each condition as either "AND", "OR", or "XOR". Some popular file-system security uses this model. For example, CanGetJob may be AND (you want to be stringent on rights-to-work). CanBeEvicted may be OR -- you may want to evict even a foreigner if he is also a pirate.
An enhancement on the AND/OR method is to provide a threshold that the total result must exceed before passing that condition. For example, putting CanGetJob at a threshold of 2 then it must get at least two 1's in order to return 1. This is sometimes useful on conditions that are not clearly black-and-white.
You can mix resolution methods: e.g. first prioritize, then use AND/OR to resolve rules with similar priorities.
The possibilities are limitless and really depends on what your actual needs are.
To me this problem reminds business rules engine where there is no known algorithm to define outputs from inputs (e.g. using boolean logic) but the user (typically some sort of administrator) has to define all or some the logic itself.
This might sound a bit of an overkill but OTOH this provides virtually limit-less extension capabilities: you don't have to code any new business logic, just define a new rule set.
As I understand your problem, you are looking for a nice way to visualise the editing for these rules. But this all depends on your programming language and the tool you select for this. Java, for example, has JBoss Drools. Quoting their page:
Drools Guvnor provides a (logically
centralized) repository to store you
business knowledge, and a web-based
environment that allows business users
to view and (within certain
constraints) possibly update the
business logic directly.
You could possibly use this generic tool or write your own.
Everything depends on what your actual rules will look like. Rules like 'IF has an even number of these properties THEN' would be painful to represent in this format, whereas rules like 'IF pirate and not geek THEN' are easy.
You can 'avoid the ambiguity' by stating that you'll always be taking the first actual match, in other words your rules have a priority. You'd then want to flag rules which have no effect because they are 'shadowed' by rules higher up. They're not hard to find, so it's something your program should do.
Your interface could also indicate groups of rules where rules within the group can be in any order without changing the outcomes. This will add clarity to what the rules are really saying.
If some of your outputs are relatively independent of the others, you will also get a more compact and much clearer table by allowing question marks in the output. In that design the scan for first matching rule is done once for each output. Consider for example if 'HasChildren' is the only factor relevant to 'Can Be Evicted'. With question marks in the outputs (= no effect) you could be halving the number of exception rules.
My background for this is circuit logic design, not business logic. What you're designing is similar to, but not the same as, a PLA. As long as your actual rules are close to sum of products then it can work well. If your rules aren't, for example the 'even number of these properties' rule, then the grid like presentation will break down in a combinatorial explosion of cases. Your best hope if your rules are arbitrary is to get a clearer more compact presentation with either equations or with diagrams like a circuit diagram. To be avoided, if you can.
If you are looking for a Decision Engine with a GUI, than you can try this one: http://gandalf.nebo15.com/
We just released it, it's open source and production ready.
You probably need some kind of inference engine. Think about doing it in prolog.

Rules Based Database Engine

I would like to design a rules based database engine within Oracle for PeopleSoft Time entry application. How do I do this?
A rules-based system needs several key components:
- A set of rules defined as data
- A set of uniform inputs on which to operate
- A rules executor
- Supervisor hierarchy
Write out a series of use-cases - what might someone be trying to accomplish using the system?
Decide on what things your rules can take as inputs, and what as outputs
Describe the rules from your use-cases as a series of data, and thus determine your rule format. Expand 2 as necessary for this.
Create the basic rule executor, and test that it will take the rule data and process it correctly
Extend the above to deal with multiple rules with different priorities
Learn enough rule engine theory and graph theory to understand common rule-based problems - circularity, conflicting rules etc - and how to use (node) graphs to find cases of them
Write a supervisor hierarchy that is capable of managing the ruleset and taking decisions based on the possible problems above. This part is important, because it is your protection against foolishness on the part of the rule creators causing runtime failure of the entire system.
Profit!
Broadly, rules engines are an exercise in managing complexity. If you don't manage it, you can easily end up with rules that cascade from each other causing circular loops, race-conditions and other issues. It's very easy to construct these accidentally: consider an email program which you have told to move mail from folder A to B if it contains the magic word 'beta', and from B to A if it contains the word 'alpha'. An email with both would be shuttled back and forward until something broke, preventing all other rules from being processed.
I have assumed here that you want to learn about the theory and build the engine yourself. alphazero raises the important suggestion of using an existing rules engine library, which is wise - this is the kind of subject that benefits from academic theory.
I haven't tried this myself, but an obvious approach is to use Java procedures in the Oracle database, and use a Java rules engine library in that code.
Try:
http://www.oracle.com/technology/tech/java/jsp/index.html
http://www.oracle.com/technology/tech/java/java_db/pdf/TWP_AppDev_Java_DB_Reduce_your_Costs_and%20_Extend_your_Database_10gR1_1113.PDF
and
http://www.jboss.org/drools/
or
http://www.jessrules.com/
--
Basically you'll need to capture data events (inserts, updates, deletes), map to them to your rulespace's events, and apply rules.