I have been reading about the articles on the web about the benefits of graphql but so far I have not been able to find a single benefit of it.
One of the most common benefits mentioned in those articles are below?
No Overfetching with GraphQL.
Reducing number of calls made from client side.
Data Load Control Granularity
Evolve your API without versions.
Those above all makes sense but it is not the graphql itself that provides these benefits. Any second layer api written in java/python or any other language would be able to provide this benefits too. It is basically introducing another layer of abstraction above the data retrieval systems, rest or whatever, and decoupling the client side from that layer. After you do that everything you can do with graphql can also be done with any other language too.
Anyone can implement a say scala server that retrieves the data from various api's integrates them, create objects internally and feeds the client with only the relevant part of the data with total control on the data. This api can be easily versioned and released accordingly. Considering the syntax of graphql and how cumbersome it is and difficulty of creating a good cache around it, I can't see why would you use it really.
So the overall question is there any benefits of graphql that is provided to the application because of the graphql itself and not because you implement another layer of abstraction between your applications and your api's?
Best practices known as REST existed earlier, too.
GraphQL is more standarized than REST, safer (no injections) and syntax gives great flexibility in the area of quickly changing client needs.
It's just a good standard of best practices.
I feel GrapgQL is another example of overengineering. I would say "Best standards and practices" are "Keeping It Simple."
Breaking down and object and building a custom one before sending it to the client is very basic.
I understand that both xsodata and xsjs are used for exposing data but why there are two ways? Which one should one use and how the use of xsodata is different from xsjs data.?
Good Question, I will try to give you a little overview. I will describe three SAPUI5 ways of backend implementation.
XSODATA
Let's assume, you have something like a Checklist. You may want to add items to your list, edit or delete them and - obvious - you want to display them. These simple tasks are called CRUD (create, read, update, delete) operations. These Operations are the simplest way of dealing with data. There are no real "hard" queries to get work done and you may operate on very less JOIN's. This can be easyly done with XSODATA. It's a simple REST-Interface.
XSJS
Okay, you have your checklist, but you want to log every single entry, or do analysis or something not-so-easy with it. This is, where XSJS comes into play. With XSJS you have a better control (and much more work needs to be done) of your data. But keep in mind, that you need to code every single step. XSJS is not a real interface, but it's a sapui5 way of handling data, like you would do in any other vanilla-programming-language without a framework.
Node.JS / custom backend
Another, newly (2017) introduced way of handling data at sapui5 is the usage of Node.JS. Node.JS let you write your own RESTful API (node.js is much more powerful than that, but this information must be enough for now). Node.JS is something like the intersection between XSODATA and XSJS: you are able to use a RESTful API (implemented by yourself) with 100% datacontrol. I don't want to go too much into detail, but Node.JS is for advanced applications the state-of-the-art at early '17.
Conclusion
What you might use really depends on your application itself. Personally, I think the best way to start is with XSODATA. If you can't solve certain tasks with only oData, use XSJS for those single cases. In a real-world application with tons of data and complex queries, you might consider Node.JS as your backend-wizard.
useful informations:
OData vs XSJS in SAP Hana Development
https://archive.sap.com/discussions/thread/3688095
http://saphanatutorial.com/sap-hana-xsjs-service/
https://blogs.sap.com/2015/12/08/sap-hana-sps-11-new-developer-features-nodejs/
https://nodejs.org/en/
I am building simple REST deployable using Spring Boot. Decided to create it by using failing acceptance test first followed with TDD until its green.
My module is pretty simple, I have 3 API's:
Retrieving list of data from datastore.
Adds item to datastore.
Deletes item from datastore.
I feel like it is good idea to abstract datastore and have maybe backed by Map data structure for testing purposes and use it with either NoSQL or SQL db if I want to for deployments/releases and end to end testing.
On the service layer side I am unsure since it would just delegate call to repository with no logic.
So standard approach would be controller->service->repository. In my case service does not do much(possible some exception handling but not more) and I will end up with interface and implementation as an extra as well as few more lines of code. I fell like going for controller->repository solution in my situation but it is not a practice I have seen and not sure how others would see it.
What's the best way to implement this sort of system?
I feel like it is good idea to abstract datastore
You are right. The abstraction is called 'Repository' in DDD (Domain Driven Design) for example.
On the service layer side I am unsure since it would just delegate call to repository with no logic.
I'm pretty sure there are data that you want to validate. So you should have a layer in the middle (e.g. the domain layer) which will be in charge of this validation.
Even so, if you feel like your application is simple and doesn't require such layers, go without. You will have less supple design, but more simplicity at first. Be careful: while evolving your app, you could run into trouble.
Hope this will help.
This is rather an opinion based question, but if you are asking whether a 3 layer architecture is a must, to that I say no. Be pragmatic, if you don' see a reason for a class/layer/module to exist, it does not need to exist.
A repository has a purpose (to store/retrieve), and the api layer has a purpose, to offer those things through HTTP.
Here is an article for building small services with the sparkframework: https://dzone.com/articles/building-simple-restful-api
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.
I would like to make a small program that scrapes information from a 3rd-party GWT-enabled website. Is it possible to somehow call this RPC directly? What would I need to reverse-engineer to do this (i.e. hopefully not the entire low-level protocol).
I am hoping I could somehow just call this from within my own server-side GWT or Servlet app.
It is possible... but you would have to go through their code to understand how the serialization/deserialization works.
Classes of interest are
RPC.java
ClientSerializationStreamWriter -> ServerSerializationStreamReader are the classes involved in making a GWT request.
ServerSerializationStreamWriter -> ClientSerializationStreamReader are the classes involved in creating and interpreting a response.
I am trying out a similar thing as an academic project, and I will add more information if I can decipher these classes.
I'm pretty sure GWT makes it difficult to do cross-site requests, for the sake of security.
Any solution you come up with will probably be hacky (and not flexible to future changes), and since you're presumably doing it without the consent of the site in question, probably a bad idea to begin with.
Is there some reason you can't ask the site to publish their data using a REST API?