We have reqmt. where we need to expose drools 5 with ESB and similteniously with the web application.Although i have figured out ways to run drools with eclipse,however finding it difficult to configure Drools 5 with same web-app at the moment and shift it esb in future.
Guvnor and Drool-Server are not just sufficient to help me out neither does googling it helps
,even spring support is also not available.
Any help will be highly appreciated...Thanks
At what level do you need to "expose" Drools within the ESB? I use Drools in an Enterprise solution that uses asynchronous web services; many of my workflows are extremely long running (2 weeks to a month). The key is to temporarily persist the StatefulKnowledgeSession between calls. There is a JPAStatefulKnowledgeSession that serializes the session and stores it as a blob in a relational database. I decided not to use this solution because many of my asynchronous tasks finish within a second of being called. The performance cost of persisting the process in a RDBMS was too much for my needs. My solution was to store the session in an in-memory cache. Infinispan was ridiculously simple to configure and use, and I haven't had a single issue with the framework.
Do you need to have the ESB and Web Application use the same KnowledgeSession? Does it have to be a StatefulKnowledgeSession? If you need to maintain state, you should consider a queue-based system and fireAllRules() at some interval. If your actions are command based (insert object, start process, etc), I believe Drools already has an API for the pattern (I believe this is what Drools Server does under the hood). You could also make the KnowledgeSession a singleton; but consider using a ReentrantLock to prevent concurrent calls on the object. If you are isolating sessions, creating your own repository works best. Infinispan's Cache implements the ConcurrentHashMap, so you could use the ID of the session as the key and KnowledgeSession as the value.
Related
Knowing that drools work with in memory data. Is there a way to distribute horizontally on different drools instances to enhance performance when performing CRUD operations on rules, fact types, etc? I guess the instances would need to be on sync with each other in some way, so they all have the same data in memory or share in some way a knowledge base. I'm kinda new on drools and trying to research on a way to move a monolith on a cloud environment (gcp) so it can take advantage on load balancing, scaling, etc. Want to know if there is any feature on drools itself that supports this or if there is any way to implement this myself, thanks in advance for any information/documentation/use case on this matter.
Currently I haven't tried a way to do this, but my goal is to improve performance and availability by using automatic scaling or support multiple instances of my app.
I'm not sure what kind of "CRUD" you're doing on Drools (or how). But if you just want to deploy new rules (for example), then this is identical to pushing any data or application changes to your deployment in a distributed system -- either your nodes are gradually updated, so during the upgrade process you have some mix of old and new logic/code; or you deploy new instances with the new logic/code and then transition traffic to your new instances and away from the old ones -- either all at once or in a controlled blue/green (or similar) fashion.
If you want to split a monolith, I think the best approach for you would be to consider Kogito [1] and microservice architecture. With microservices, you could even consider using the Function as a service approach - having small immutable service instances, that are just executed and disposed. Kogito mainly targets Quarkus platform, but there are also some Spring Boot examples. There is also OpenShift operator available.
As far as sharing the working memory, there was a project in the KIE community called HACEP [2]. Unfortunately that is now deprecated and we are researching other solutions to make the working memory persisted.
[1] https://kogito.kie.org/
[2] https://github.com/kiegroup/openshift-drools-hacep
The term "entry point" is related to the fact that we have multiple partitions in a Working Memory and you can choose which one you are inserting into. If you can organize your business logic to work with different entry points you can process 'logical partitions' on different machines in parallel safely. At a glance drools entry points gives you something like table partitioning in Oracle which implies the same options.
Use load balancer with sticky sessions if you can (from business point of view) partition 'by client'
you question looks more like an architecture question.
As a start, I would have a look into the Kie Execution Server component provided with Drools that helps you to create microservice decisions based on Drools rulesets.
Kie Execution Server (used in stateless mode by clients) could be embedded in different pods/instances/servers to ensure horizontal scalability.
As mentioned by #RoddyoftheFrozenPeas , one of the problem you'll face will be the simultaneous hot deploy of new rulesets on the "swarm" of kieserver that hosts your services.
That would have to be handled using a proper devops strategy.
Best
Emmanuel
I currently use Jpa via Hibernate in my application. Since spring security oauth2 provides JdbcTokenStore, I started using it. But the problem with that is, I cannot use cache (which all my entities in the application currently share).
It hits the database in a separate flow.
I am thinking implementing JpaTokenStore thats backed by Jpa & leverage the cache advantages that comes with it.
Did anyone try implementing this/see any downsides using this approach?
In one project I've implmented org.springframework.security.oauth2.client.token.ClientTokenServices with JPA and didn't notice any problems. I was able to use all standard features of JPA including #Transactional for JPAClientTokenServices#saveAccessToken
There is nothing stopping you from doing it, and plenty of people do use JPA for all sorts of things, but IMO JPA is not ideal for handling storage of identity data. JPA is designed and optimized for cacheing data for the duration of a JDBC connection (a transaction basically), while identity data have a typically different and much longer lifetime. If you store long lived data using JPA, you have to deal with the consequences of what happens when you access it outside its normal lifetime, e.g. use DTOs, which ends up negating the benefits of using it in the first place to some extent.
I have a WCF Service ServiceA.
That in turn has to call two individual WCF services ServiceB and ServiceC which do two different things, but if the call to ServiceC fails I want to rollback what ServiceB did.
I did implement it using TransactionScope (I am using EF 6.0) however without enabling MSDTC it is not working. Is there a workaround for this? I really do not want to go through the MSDTC route because I am afraid that would cause a lot of performance issues and the web admins are strongly against it.
What you want is a distributed transaction, because your transaction contains cross boundary participants. To the best of my knowledge, the only solution for a distributed transaction in windows platform is MSDTC, there is no way around this.
I would, however, recommend that you try to seek a more eventual consistent solution, rather than strictly transactional, because your solution will most likely perform and scale better. Granted, you will have to deal with special cases where your data is not consistent, which will lead to more complex code.
From my experience, it will be worth it, but its up to you.
I want to exchange data between two applications JEE6/JSF2.0 and i'm looking for the best solution. I thought of the below solutions :
by using a JSON file.
by using XML file.
by using GSON file.
by using Remote interface (EJB 3.0).
For you, what's the best solution to use ?
edit : This two applications will be always running on the same network (but can not be on the same JVM)
I want to provide an alternative to David's answer, as I feel that there are some drawbacks to RMI that he underplayed.
This is a Java specific technology. If a third server needs to be introduced and it is a Microsoft Reporting Services server for example, then it cannot talk in the same language.
RMI is an OLD technology and doesn't particularly look well on a CV. Web services are the future. Experienced RMI developers are more uncommon than experienced web service developers.
Cumbersome and heavy framework
A better solution in my opinion would be to use SOAP XML based web services. Here are some advantages to this approach:
Universal acceptance in nearly any development framework. No matter the technology, nearly all have helpful libraries for interacting with web services.
Java has good support for object serialization into XML. This means objects can be quickly serialized into a SOAP XML request, sent to the other server, and deserialized back into a Java object by the other application server for processing.
A service layer can give you the decoupling interface between the two applications just as RMI can.
I hope you reconsider the use of SOAP XML based web services in your application.
There's two options really as you yourself stated.
Using RMI to connect to a EJB or using a webservice and communicating by JSON/XML etc...
From my experience RMI can be favorable if your applicaitons are on the same network, if not then you might get problems with firewalls etc and be forced to tunnel the RMI using HTTPS... which pretty much makes the RMI calls webservice calls.
If your on two different machines then webservices are nice as they dont cause as much trouble with firewalls. Also as they use the HTTP protocol you dont have to worry about the data being transfered.
These examples are kinda generalised but should give you some insight.
GSON vs XML vs JSON is a completely different subject... Non is superiour to the other, and all are fairly easily read by the human eye.
UPDATE
From what I've understod you wont have to worry about firewalls and such, I would recommend using RMI. It usually results in cleaner code and somewhat better performance.
Since I have seen both in action, I can make a comparison between the two technologies, EJB and WebServices. I can confirm that EJB is way more efficient, has support of transactions (including distributed transactions, if that is your requirement), exception handling, and binary streaming out of the box. In terms of performance EJB may exceed SOAP by a factor of 5 times in speed, and REST for about 3 times.
However, EJB is not an integration technology. In fact, it has never thought to do so. The biggest flaw of EJB is that it is very coupled to the Java Platform. Therefore, both endpoints must be written in Java and should use the same Java EE version.
Another problem is that EJB is not a protocol per se, so the implementations from two containers/vendors is probably different. If you need to access a remote EJB from JBoss AS on an Oracle WebLogic server, you must bring JBoss EJB client implementation with you.
Another big problem related to integration with EJB is a lack of data exchange format. Since it uses Java Serialized objects for communication, the data types must be shared on both ends. If you create a new exception type on the server that is classified as an Application Exception, if the client who consumes this service triggers the exception, his code will break. Note that, in this case the remote API was not violated, but another unknown type was introduced.
And, of course, by depending solely on the class type as an exchange format, you are giving the programmers opportunity for doing very stupid things. If you have many different teams in large projects using EJB as integration technology using different versions of Java EE, prepare yourself to experience uttermost pain. I've seem a programmer including a JPA entity on the client, who was annotated with named queries, the table which was accessing, its columns, etc, essentially giving away all the database layout to the service consumer. But it can get even worse. I've already seem a programmer returning a data structure that belonged to a dependency, namely Eclipselink 1.0. However, if you access this from a JBoss server, Eclipselink is also a JPA implementation technology, which conflicts with JBoss' hibernate. So, now you have to include Eclipselink jar in your JBoss APP classpath and configure the container for not loading JPA related packages, which otherwise will break your application completely. Even so, it can get WORSE than before: some other service you need to connect had also the bright idea of using the same datastructure, but now from Eclipselink 1.1.1, that has a different implementation, but the same class signature. Now you are in a very bad situation.
The bottom line: NEVER, EVER, use EJB as an integration technology. Use SOAP using a contract-first approach, where you define a canonical data model for the application, mapping java datastructures to a XML exchange format that can be used by any client, be it written in any language or using different stacks. Or use REST implementing a resource based, using HATEOAS principles. These days I rarely seem a reason for using EJB at all, since CDI is now on the market, support many features that EJB does and does not include any RPC related technology.
I am trying to figure out if I should migrate my gwt-rpc calls to the new GWT2.1 RequestFactory cals.
Google documentation vaguely mentions that RequestFactory is a better client-server communication method for "data-oriented services"
What I can distill from the documentation is that there is a new Proxy class that simplifies the communication (you don't pass back and forth the actual entity but just the proxy, so it is lighter weight and easier to manage)
Is that the whole point or am I missing something else in the big picture?
The big difference between GWT RPC and RequestFactory is that the RPC system is "RPC-by-concrete-type" while RequestFactory is "RPC-by-interface".
RPC is more convenient to get started with, because you write fewer lines of code and use the same class on both the client and the server. You might create a Person class with a bunch of getters and setters and maybe some simple business logic for further slicing-and-dicing of the data in the Person object. This works quite well until you wind up wanting to have server-specific, non-GWT-compatible, code inside your class. Because the RPC system is based on having the same concrete type on both the client and the server, you can hit a complexity wall based on the capabilities of your GWT client.
To get around the use of incompatible code, many users wind up creating a peer PersonDTO that shadows the real Person object used on the server. The PersonDTO just has a subset of the getters and setters of the server-side, "domain", Person object. Now you have to write code that marshalls data between the Person and PersonDTO object and all other object types that you want to pass to the client.
RequestFactory starts off by assuming that your domain objects aren't going to be GWT-compatible. You simply declare the properties that should be read and written by the client code in a Proxy interface, and the RequestFactory server components take care of marshaling the data and invoking your service methods. For applications that have a well-defined concept of "Entities" or "Objects with identity and version", the EntityProxy type is used to expose the persistent identity semantics of your data to the client code. Simple objects are mapped using the ValueProxy type.
With RequestFactory, you pay an up-front startup cost to accommodate more complicated systems than GWT RPC easily supports. RequestFactory's ServiceLayer provides significantly more hooks to customize its behavior by adding ServiceLayerDecorator instances.
I went through a transition from RPC to RF. First I have to say my experience is limited in that, I used as many EntityProxies as 0.
Advantages of GWT RPC:
It's very easy to set-up, understand and to LEARN!
Same class-based objects are used on the client and on the server.
This approach saves tons of code.
Ideal, when the same model objects (and POJOS) are used on either client and server, POJOs == MODEL OBJECTs == DTOs
Easy to move stuff from the server to client.
Easy to share implementation of common logic between client and server (this can turn out as a critical disadvantage when you need a different logic).
Disadvatages of GWT RPC:
Impossible to have different implementation of some methods for server and client, e.g. you might need to use different logging framework on client and server, or different equals method.
REALLY BAD implementation that is not further extensible: most of the server functionality is implemented as static methods on a RPC class. THAT REALLY SUCKS.
e.g. It is impossible to add server-side errors obfuscation
Some security XSS concerns that are not quite elegantly solvable, see docs (I am not sure whether this is more elegant for RequestFactory)
Disadvantages of RequestFactory:
REALLY HARD to understand from the official doc, what's the merit of it! It starts right at completely misleading term PROXIES - these are actually DTOs of RF that are created by RF automatically. Proxies are defined by interfaces, e.g. #ProxyFor(Journal.class). IDE checks if there exists corresponding methods on Journal. So much for the mapping.
RF will not do much for you in terms of commonalities of client and server because
On the client you need to convert "PROXIES" to your client domain objects and vice-versa. This is completely ridiculous. It could be done in few lines of code declaratively, but there's NO SUPPORT FOR THAT! If only we could map our domain objects to proxies more elegantly, something like JavaScript method JSON.stringify(..,,) is MISSING in RF toolbox.
Don't forget you are also responsible for setting transferable properties of your domain objects to proxies, and so on recursively.
POOR ERROR HANDLING on the server and - Stack-traces are omitted by default on the server and you re getting empty useless exceptions on the client. Even when I set custom error handler, I was not able to get to low-level stack traces! Terrible.
Some minor bugs in IDE support and elsewhere. I filed two bug requests that were accepted. Not an Einstein was needed to figure out that those were actually bugs.
DOCUMENTATION SUCKS. As I mentioned proxies should be better explained, the term is MISLEADING. For the basic common problems, that I was solving, DOCS IS USELESS. Another example of misunderstanding from the DOC is connection of JPA annotations to RF. It looks from the succinct docs that they kinda play together, and yes, there is a corresponding question on StackOverflow. I recommend to forget any JPA 'connection' before understanding RF.
Advantages of RequestFactory
Excellent forum support.
IDE support is pretty good (but is not an advantage in contrast with RPC)
Flexibility of your client and server implementation (loose coupling)
Fancy stuff, connected to EntityProxies, beyond simple DTOs - caching, partial updates, very useful for mobile.
You can use ValueProxies as the simplest replacement for DTOs (but you have to do all not so fancy conversions yourself).
Support for Bean Validations JSR-303.
Considering other disadvantages of GWT in general:
Impossible to run integration tests (GWT client code + remote server) with provided JUnit support <= all JSNI has to be mocked (e.g. localStorage), SOP is an issue.
No support for testing setup - headless browser + remote server <= no simple headless testing for GWT, SOP.
Yes, it is possible to run selenium integration tests (but that's not what I want)
JSNI is very powerful, but at those shiny talks they give at conferences they do not talk much about that writing JSNI codes has some also some rules. Again, figuring out how to write a simple callback was a task worth of true researcher.
In summary, transition from GWT RPC to RequestFactory is far from WIN-WIN situation,
when RPC mostly fits your needs. You end up writing tons conversions from client domain objects to proxies and vice-versa. But you get some flexibility and robustness of your solution. And support on the forum is excellent, on Saturday as well!
Considering all advantages and disadvantages I just mentioned, it pays really well to think in advance whether any of these approaches actually brings improvement to your solution and to your development set-up without big trade-offs.
I find the idea of creating Proxy classes for all my entities quite annoying. My Hibernate/JPA pojos are auto-generated from the database model. Why do I now need to create a second mirror of those for RPC? We have a nice "estivation" framework that takes care of "de-hibernating" the pojos.
Also, the idea of defining service interfaces that don't quite implement the server side service as a java contract but do implement the methods - sounds very J2EE 1.x/2.x to me.
Unlike RequestFactory which has poor error handling and testing capabilities (since it processes most of the stuff under the hood of GWT), RPC allows you to use a more service oriented approach. RequestFactory implements a more modern dependency injection styled approach that can provide a useful approach if you need to invoke complex polymorphic data structures. When using RPC your data structures will need to be more flat, as this will allow your marshaling utilities to translate between your json/xml and java models. Using RPC also allows you to implement more robust architecture, as quoted from the gwt dev section on Google's website.
"Simple Client/Server Deployment
The first and most straightforward way to think of service definitions is to treat them as your application's entire back end. From this perspective, client-side code is your "front end" and all service code that runs on the server is "back end." If you take this approach, your service implementations would tend to be more general-purpose APIs that are not tightly coupled to one specific application. Your service definitions would likely directly access databases through JDBC or Hibernate or even files in the server's file system. For many applications, this view is appropriate, and it can be very efficient because it reduces the number of tiers.
Multi-Tier Deployment
In more complex, multi-tiered architectures, your GWT service definitions could simply be lightweight gateways that call through to back-end server environments such as J2EE servers. From this perspective, your services can be viewed as the "server half" of your application's user interface. Instead of being general-purpose, services are created for the specific needs of your user interface. Your services become the "front end" to the "back end" classes that are written by stitching together calls to a more general-purpose back-end layer of services, implemented, for example, as a cluster of J2EE servers. This kind of architecture is appropriate if you require your back-end services to run on a physically separate computer from your HTTP server."
Also note that setting up a single RequestFactory service requires creating around 6 or so java classes where as RPC only requires 3. More code == more errors and complexity in my book.
RequestFactory also has a little bit more overhead during the request processing, as it has to marshal serialization between the data proxies and actual java models. This added interface adds extra processing cycles which can really add up in an enterprise or production environment.
I also do not believe that RequestFactory services are serialization like RPC services.
All in all after using both for some time now, i always go with RPC as its more lightweight, easier to test and debug, and faster then using a RequestFactory. Although RequestFactory might be more elegant and extensible then its RPC counter part. The added complexity does not make it a better tool necessary.
My opinion is that the best architecture is to use two web apps , one client and one server. The server is a simple lightweight generic java webapp that uses the servlet.jar library. The client is GWT. You make RESTful request via GWT-RPC into the server side of the client web application. The server side of the client is just a pass though to apache http client which uses a persistant tunnel into the request handler you have running as a single servlet in your server servlet web application. The servlet web application should contain your database application layer (hibernate, cayenne, sql etc..) This allows you to fully divorce the database object models from the actual client providing a much more extensible and robust way to develop and unit test your application. Granted it requires a tad bit of initial setup time, but in the end allows you to create a dynamic request factory sitting outside of GWT. This allows you to leverage the best of both worlds. Not to mention being able to test and make changes to your server side without having to have the gwt client compiled or build.
I think it's really helpful if you have a heavy pojo on the client side, for example if you use Hibernate or JPA entities.
We adopted another solution, using a Django style persistence framework with very light entities.
The only caveat I would put in is that RequestFactory uses the binary data transport (deRPC maybe?) and not the normal GWT-RPC.
This only matters if you are doing heavy testing with SyncProxy, Jmeter, Fiddler, or any similar tool that can read/evaluate the contents of the HTTP request/response (like GWT-RPC), but would be more challenging with deRPC or RequestFactory.
We have have a very large implementation of GWT-RPC in our project.
Actually we have 50 Service interfaces with many methods each, and we have problems with the size of TypeSerializers generated by the compiler that turns our JS code huge.
So we are analizing to move towards RequestFactory.
I have been read for a couple of days digging into the web and trying to find what other people are doing.
The most important drawback I saw, and maybe I could be wrong, is that with RequestFactory your are no longer in control of the communication between your Server Domain objects and your client ones.
What we need is apply the load / save pattern in a controlled way. I mean, for example client receive the whole object graph of objects belonging to a specific transaction, do his updates and them send the whole back to the server. The server will be responsible for doing validation, compare old with new values and do persistance. If 2 users from different sites gets the same transaction and do some updates, the resulting transaction shouldn't be the merged one. One of the updates should fail in my scenario.
I don't see that RequestFactory helps supporting this kind of processing.
Regards
Daniel
Is it fair to say that when considering a limited MIS application, say with 10-20 CRUD'able business objects, and each with ~1-10 properties, that really it's down to personal preference which route to go with?
If so, then perhaps projecting how your application is going to scale could be the key in choosing your route GWT RPC or RequestFactory:
My application is expected to stay with that relatively limited number of entities but will massively increase in terms of their numbers. 10-20 objects * 100,000 records.
My application is going to increase significantly in the breadth of entities but the relative numbers involved of each will remain low. 5000 objects * 100 records.
My application is expected to stay with that relatively limited number of entities AND will stay in relatively low numbers of e.g. 10-20 objects * 100 records
In my case, I'm at the very starting point of trying to make this decision. Further complicated by having to change UI client side architecture as well as making the transport choice. My previous (significantly) large scale GWT UI used the Hmvc4Gwt library, which has been superseded by the GWT MVP facilities.