DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
Refcards Trend Reports
Events Video Library
Refcards
Trend Reports

Events

View Events Video Library

The Latest Deployment Topics

article thumbnail
Android vs iPhone Development: A Comparison
A few months ago I ventured into the world of Mobile development and created an application (Hudson Helper) for both iPhone and Android. This article is about my experiences, comparing Android and iPhone development with a focus on tools, platform and the developer experience. Before going much further I should note that my comparison is with considerable bias. I’ve spent the past 12+ years in Java development, having spent much of my career building developer tools. Since January of 2004 I’ve been building plug-ins for Eclipse, and before that plug-ins for NetBeans. This bias is somewhat tempered with several years of C and C++ development. With this background I find that I’m very critical of developer tools. Developer productivity is key — anything that takes away from the flow of a developer in the zone is a real problem. Language, Programming Model and Platform Language The language of choice for iPhone development is Objective-C. Objective-C is a language based on C with extensions for object-oriented concepts, such as classes, inheritance, interfaces, messages, dynamic typing, etc. The Java language is used when developing for Android (though it doesn’t actually get compiled to bytecode). Java is a no-brainer. I have to say that it’s nice not to have to learn a new language to target mobile. Existing skillsets don’t come easy — so reuse of expertise is worth a lot. It took a little while to wrap my head around some of the language features available with Objective-C. I soon discovered that I really loved certain language features, such as message passing (instead of calling methods), categories and named arguments. I did find however that the syntax of Objective-C is cumbersome. I’m still not used to ‘+’ and ‘-’ for static and member methods, too many parentheses are required, and in general I just felt like I had to type way to much to express a simple concept. The IDE didn’t help much with this either (more on that later). One thing that really became clear to me is that Objective-C, though it may have been visionary for its time, is really a language of the '80s. Certain issues such as split header and implementation files and violation of DRY are really time-wasters, and not small ones at that. I found myself constantly switching back and forth between files, which not only has a cost in navigation (which file to open?) but with every file opened your sense of context must be recreated (where’s the caret, what’s selected, where am I in the file, how is this file organized). As far as DRY, must I really do 5 things to declare a property?? (declare in the class definition, again to declare getter/settter, initialize in the init method, @synthesize in the implementation, release in dealloc). Here’s what I mean: Server.h @interface Server : Updatable {NSString *name; <-- declare the property }@property (nonatomic,retain) NSString *name; <--- declare the property again Server.m @synthesize name; <-- implement getter/setter-(void) dealloc {[name release]; <-- release memory} If you ask me, everything in Server.m should go away. Another gotcha here is the positional relevance of @synthesize. Java has a similar problem with properties, though not quite so bad — and the IDE helps you write your getter/setter. Pointers in Objective-C, though powerful, are also another time-waster. This is where Java really shines with its garbage collection. I found that I was constantly considering whether allocated objects were freed appropriately. Code flow is poor since application logic is littered with memory management. I only have so many brain cycles available — why do I have to think about this other cruft that’s not really a core concern of the application domain? Of course this gets even worse when trying to figure out where things went wrong if you make a mistake. Zombies help, but still don’t make it obvious if you’ve accessed something that was deallocated. Other issues include deallocating something twice, autoreleasing something twice. I also found it non-intuitive when to retain return values from methods. Another annoyance of Objective-C is the patterns that must be followed: implementing correct init and dealloc methods is non-trivial. @synthesized getters and setters for properties with retain should not be called in these methods. So many conventions and rules to remember! Though I understand why there’s a separation of alloc and init, it’s still overly wordy to specify [[aloc Foo] initWithArg: arg]. Why not just [new Foo arg]? Or how about new Foo(arg) -- oh, wait, that’s just like Java! Objective-C’s imports and forward-declarations (@class) are a pain. Though these issues exist with Java development, Eclipse’s JDT is so good that I’ve almost forgotten what it’s like to write an import. All you have to do is Ctrl+Space to auto-complete a class name or Ctrl+Shift+O to organize imports and voila! Of course Java is not perfect either, however this fact is hidden from me due to the fact that I’ve been living in Java for a very long time. Sometimes I wish that Java were more Groovy-like, however I’m used to it and the tooling is so good. Platform On Android I found that I could readily use the Java runtime classes. Some, but not all, of the standard Java RT classes are available on Android. I didn’t find this a problem, since most of the standard Java IO, network and regex libraries are available. Android RT classes appear to be based on Harmony, which has been around long enough to be stable. With iPhone on the other hand, finding the functionality that I needed was painful. Classes and methods are poorly organized. When to look for a static method versus a class with members was not clear to me. Also depending on the framework used, naming conventions and code organization would differ. I suppose this is the legacy of an older platform. Areas where functionality was lacking that I found painful were regular expressions, string handling and XML parsing. I ended up using the excellent Regex Kit Lite for regular expressions. For XML parsing I implemented a parser abstraction over libxml, only to discover later that I may have had an easier time with NSXMLParser which is a lot more like SAX. On the iPhone when things didn’t work as expected I had to resort to Google and hope that others had encountered the same problem. This technique was hampered by Apple’s earlier NDA policy, which meant that iPhone content is pretty thin on the net. In some cases I would resort to guesswork and experimentation to find a solution. Android has the benefit of being open source. Within minutes I had the full Android platform source code on my system, and had re-built the SDK from sources to ensure that the source I had matched the runtime classes in the emulator. So not only could I see how things were implemented in the Android platform and learn by example, I could step through the platform code in the emulator and discover why my code wasn’t producing the desired results. In general I found the layout, organization, and naming conventions of Android platform classes was consistent and predictable. This made it much easier to learn. Programming Model The iPhone platform does a great job of encouraging an MVC design pattern. With this design pattern built in to the platform, building the UI was simple and I didn’t have to figure out how to organize the UI component design myself. It also means that when looking at sample code, it’s all organized in the same way. Android also does a good job with design patterns, though their concepts varied significantly from the iPhone. With Android’s support for multiple processes and component reuse, the platform itself provides support for Intents and Activities (an Intent is just a variant of a command). The design results in a better user experience, however it does introduce some complexity for the developer: when starting one Activity from another, an Intent is used to communicate any parameters. These parameters cannot be passed by reference — only by value. Where on the iPhone it’s simple to have screens sharing the same data structures, on Android this requires some forethought. Apparently Android applications can manage the back button and have everything occur inside a single Activity, however this is not the norm. Both Android and iPhone provide a way of declaring user preferences in XML. Both platforms provide a default UI for editing those preferences, which is great. Android’s XML format is extensible allowing custom UI components to be integrated, which makes user preferences a breeze. iPhone developers that wish to customize preferences will have to implement a UI from scratch, which is a lot more work. Testing and Continuous Integration I’m of the opinion that every development effort should include unit tests. Teams of size greater than one should also include Continuous Integration. Android developers will be happy to know that they can write JUnit tests. I could even launch these from the Eclipse UI after some classpath fiddling. Though I didn’t try it, I assume that it’s trivial to run these from Ant and your favorite CI server such as Hudson. I did see some iPhone unit test documentation with the iPhone SDK but didn’t take the time to explore it — so I can’t comment there. Resources Apple does an excellent job of providing lots of resources for developers. Important concepts are explained in videos, which makes grasping concepts easy — however I did find that videos progressed slowly and I was watching for what seemed like hours to find information that should have taken minutes. Luckily Apple also provides lots of sample applications and code to demonstrate API usage. Android developers also have access to loads of resources. The guide and API reference are installed with the SDK, so everything is available when offline (which for me is important since I do a lot of my work in transit). I found the Android development resources better organized and spent less time looking and more time finding. In particular the ApiDemos sample app provides a great starting point. I also downloaded many open source Android projects for ideas on architecture and API usage. This is an area where Android has the advantage, with Apple’s previous NDA policy there isn’t much out there in terms of open source for iPhone. Tooling For me tooling was a real shocker. These are the categories of tooling that I’ll cover: IDE, UI builder, debugger, profiler. Almost everything else is related to provisioning, and in that area I didn’t notice much in the way of differences between Android and iPhone. IDE Android development leverages the excellent JDT tools, which are pretty much stock and standard with every Eclipse installation. I’ve used these tools now for many years and they’re excellent. Everything Java is indexed, the IDE has a rich model of the source code, and refactoring is so seamless that it has changed the way that I work. Perhaps the best feature of JDT is its incremental compiler, which provides immediate feedback with errors and warnings as you type. This eliminates the code-compile-wait-for-feedback cycle that was so common in the '80s and '90s. Errors and warnings are updated in the Java editor as I type, giving me instant feedback. I didn’t realize just how valuable this feature is until I was coding Objective-C in XCode — when I became acutely aware at how waiting for compiler feedback can break the flow of programming. Other key features that make Eclipse so amazing to work with are: content assist quick-fixes organize imports open type (CTRL+Shift+T) refactorings Integrated javadoc and content assist is quite possibly the best way to learn an unfamiliar API. In Ecipse not only are all classes and methods immediately available in the context in which you’re writing code, their documentation is presented alongside. Content Assist with Integrated Javadoc XCode is so shockingly bad that I almost don’t know where to start. Here’s a minimum list of things that I think need fixing in order for XCode to become a viable IDE: Content assist that actually works. Content assist provided by XCode is often wrong, and almost always suggests a small subset of what’s actually available. A decent window/editor management system. XCode and it’s associated tools (debugger) like to open lots of windows. Want to open a file? How about a new window for you! Very quickly I found myself in open-window-hell. The operating system’s window management is designed for managing multiple applications, not multiple editors within an IDE. It’s simply not capable of providing management of editors in an environment as sophisticated as an IDE. A project tree view that sorts files alphabetically. Really! Integrated API documentation. I found that I was constantly switching out of the IDE and searching for API documentation using Appkido. This may seem trivial, but it really breaks the flow. One area of Eclipse that simply can’t be matched is Mylyn. Integrated task management and a focused interface introduce huge efficiencies into any project, small or large. If you haven’t yet tried out Mylyn, it’s definitely worth your time to take a look. A good place to start is Mylyn’s Getting Started page. UI Builder iPhone app developers are given a pretty good UI builder. It does a great job of showing the UI as it will actually appear. It’s flexible and can model some pretty sophisticated UIs, so I was impressed. I found that using it was a little tricky — I had to read the documentation two or three times before I could really figure out how to use it properly. The Android UI builder I found pretty useless: it can’t display UIs how they’ll actually appear, and it’s UI is way too inefficient. I found that I coded all of the UIs directly in the XML source view of the UI builder. There the content assist and validation were pretty good, making it the easiest way for me to build a UI. Debugger Having used to the Java debugger in Eclipse I was shocked at the state of the debugger in XCode. With Eclipse I can see and modify variable values. Not so in XCode. Maybe this is simply the state of affairs when debugging native code, but it sure affects the usefulness of the debugger. XCode often seemed confused as to the type of an object and presented me with a pointer value and no detail. This is a sharp contrast to Eclipse, where I can drill down through an object graph with ease. I found the XCode debugger UI extremely difficult to use. Clicking on the stack to show code in an editor caused new windows to open, eventually resulting in dozens of windows open. In addition I found that watch expressions rarely worked for me. Profiler and Heap Analysis An area where Apple development tools excel is in profiling and heap analysis. These tools seemed mature and easy to use. With no prior experience with these specific tools I was able to gain a better understanding of my app within minutes, find and fix several memory leaks and improve performance. XCode Memory Leak Detection Android developers must use Android’s traceview application, which I found worked well but required significantly more effort to configure and operate. I was surprised to find that the source code must be changed in order to get the trace files required for analysis. I’m not sure if Android can provide heap dumps in hprof format. If it can then the awesome MAT tool could be used to analyze heap usage. According to this article Android can produce hprof heap data, though I haven’t tried it. App Store It goes without saying that the iPhone app store is excellent in that you can sell into many countries worldwide with a single setup. I was able to provide my Canadian bank account number, sign a few legal agreements and I was up and running. Getting an app into the store however is frustrating to say the least. Apple must approve every app before it is accepted into the store. Mine got rejected multiple times. Each time it was rejected I was given almost no information about why. When I emailed them to clarify the problem, I received what looked like a canned response indicating that I should refer to previous correspondence. If it weren’t so frustrating I would have found it funny. I highly recommend reading Brian Stormont’s Avoiding iPhone App Rejection from Apple and Dan Grigsby’s Part 2 follow-up. Of course once I started selling Hudson Helper I realized that Apple won’t send me any money unless the payout is greater than $250. This is true not only of the first payout, but every payout. Google market on the other hand requires a minimum of $1 for each payout. Both the iPhone app store and Google market take about %30 of your app selling price. $0.99 applications have to have high volume, or they’re simply not worth your time. The Google market by comparison to the Apple app store is terrible in that you can only sell into a handful of countries. You also can’t see or install apps that cost money on a developer phone. Actually you can, but not if the app has copy protection — which is almost every non-free app. On the other hand when you upload your app to the app store it’s available within minutes, so you don’t have to worry about an approval process. To set up a merchant account with Google market, I had to provide a US address and bank account number, since Google doesn’t support Canada. For me this was a pain, but not too bad since I live within a few kilometers of the US border. I rode my bike down to the US and opened an account with Horizon bank. The bank required a passport and driver’s license, so no problem there. Why Google doesn’t support more countries I don’t know. At the very least Google market should accept alternate payment methods for countries that are not supported by Google checkout. Summary Android’s platform and developer tools are excellent. Leveraging Java and the Eclipse IDE are major winning factors for Android. Apple’s developer tools are shockingly bad by comparison. The Objective-C language and platform APIs are cumbersome and poorly organized. Overall when developing for the iPhone I felt like I was back in 1993. These factors combined in my estimation make application development about three times more expensive when developing for iPhone. The only area where Apple’s developer tools excelled was in profiling and heap analysis. Apple’s app store from a user’s standpoint and from a worldwide coverage standpoint are excellent. In this area Google market for Android is weak. Development for iPhone may improve as tools such as iphonical (MDD for iPhone) and objectiveclipse (Eclipse plug-in for Objective-C) emerge. We may see a shake-up in the mobile market, with at least 18 new Android handsets being released this year. Until that happens, iPhone will remain a market leader and developers will have to put up with XCode and Objective-C. For me, my love is with Android. Sure, the iPhone is great — but can you install a new Linux kernel? From http://greensopinion.blogspot.com/
July 6, 2009
by David Green
· 93,111 Views
article thumbnail
Hibernate Performance Tuning
Hibernate is a powerful, high performance object/relational persistence and query service. Hibernate lets you develop persistent classes following object-oriented idiom - including association, inheritance, polymorphism, composition, and collections. Hibernate allows you to express queries in its own portable SQL extension (HQL), as well as in native SQL, or with an object-oriented Criteria and Example API. Quintessential to using any ORM framework like hibernate is to know how to leverage the various performance tuning methods supported by the framework. In this volume Wings Jiang discusses three performance tuning strategies for hibernate: SQL Optimization Session Management Data Caching SQL Optimization When using Hibernate in your application, you already have been coding HQL (Hibernate Query Language) somewhere. For example, “from User user where user.name = ‘John’”. If issuing your SQL statement like this, Hibernate cannot use the SQL cache implemented by database because name of the user, in most scenarios, is extremely distinct. On the contrary, while using placeholder to achieve this, like “from User user where user.name =?” will be cached by the Database to fulfill the performance improvement. You can also set some Hibernate properties to improve performance, such as setting the number of records retrieved while fetching records via configuring property hibernate.jdbc.fetch_size, setting the batch size when committing the batch processing via configuring property hibernate.jdbc.batch_size and switching off the SQL output via setting property hibernate.show_sql to false in product environments. In addition, the performance tuning of your target Database is also significant, like SQL clauses tuning, reasonable indexes, delicate table structures, data partitions etc. Session Management Undoubtedly, Session is the pith of Hibernate. It manages the Database related attributes, such as JDBC connections, data entities’ states. Managing the Session efficiently is the key to getting high performance in enterprise applications. One of the many commonly used and equally elegant approaches to session management in hibernate is to use ThreadLocal. Threadlocal will create a local copy of session for every thread. Thus synchronization problems are averted, when objects are put in the Threadlocal, . To understand how ThreadLocal variables are used in Java, refer to Sun Java Documentation at http://java.sun.com/j2se/1.5.0/docs/api/java/lang/ThreadLocal.html Data Caching Before accomplishing any data caching, it is essential to set the property hibernate.cache.user_query_cache = true. There are three kinds of commonly used Caching Strategies in Hibernate: Using cache based on Session level (aka Transaction layer level cache). This is also called first-level cache. Using cache based on SessionFactory level (Application layer level cache). This is also called second-level cache. Using cluster cache which is employed in distributed application (in different JVMs). In fact, some techniques, like loading data by id, lazy initialization which betokens loading appropriate data in proper time rather than obtaining a titanic number of useless records, which are fairly useless in the subsequent operations are consummated via data caching. First Level Cache (aka Transaction layer level cache) Fetching an object from database always has a cost associated with it. This can be offset by storing the entities in hibernate session. Next time the entities are required, they are fetched from the session, rather than fetching from the database. To clear an object from the session use: session.evict(object). To clear all the objects from the session use session.clear(). Second Level Cache (aka Application layer level cache) In this approach, if an object is not found in session, it is searched for in the session factory before querying the database for the object. If an object is indeed fetched from database, the selected data should be put in session cache. This would improve the performance when the object is required next time. To remove an entity from session factory use the various overloaded implementations of evict() method of SessionFactory. In fact, Hibernate lets you tailor your own caching implementation by specifying the name of a class that implements org.hibernate.cache.CacheProvider using the property hibernate.cache.provider_class. But it is recommended to employ a few built-in integrations with open source cache providers (listed below). Cache Type Cluster Safe Query Cache Supported Hashtable Memory NO YES EHCache Memory, Disk NO YES OSCache Memory, Disk NO YES SwarmCache Clustered YES (clustered invalidation) NO JBoss TreeCache Clustered YES (replication) YES Terracota Clustered YES YES In order to use second level caching, developers have to append some configurations in hibernate.cfg.xml (for example, using EHCache here). net.sf.ehcache.hibernate.Provider In addition, developers also need to create a cache specific configuration file (Example: ehcache.xml for EHCache). (1) diskStore : Sets the path to the directory where cache .data files are created. The following properties are translated: a.user.home - User's home directory b.user.dir - User's current working directory c.java.io.tmpdir (Default temp file path) maxElementsInMemory : Sets the maximum number of objects that will be created in memory. eternal : Sets whether elements are eternal. If eternal, timeouts are ignored and the element is never expired. timeToIdleSeconds : Sets the time to idle for an element before it expires. Is only used if the element is not eternal. Idle time is now - last accessed time. timeToLiveSeconds : Sets the time to live for an element before it expires. Is only used if the element is not eternal. TTL is now - creation time overflowToDisk : Sets whether elements can overflow to disk when the in-memory cache has reached the maxInMemory limit. Finally the cache concurrency strategy has to be specified in mapping files. For example, the following code fragment shows how to configure your cache strategy. … … Cache Concurrency Strategies There are four kinds of built-in cache concurrency strategies provided by Hibernate. Chosing a right concurrency strategy for your hibernate implementation is the key to cache performance optimization. Besides to ensure data consistency and transaction integrity it is indispensable to master these strategies. read-only If your application needs to read but never modify instances of a persistent class, a read-only cache may be used. This is the simplest and best performing strategy. It's even perfectly safe for use in a cluster. nonstrict-read-write If the application only occasionally needs to update data (For example, if it is extremely unlikely that two transactions would try to update the same item simultaneously) and strict transaction isolation is not required, a nonstrict-read-write cache might be appropriate. read-write If the application needs to update data, a read-write cache might be appropriate. This cache strategy should never be used if serializable transaction isolation level is required. transactional If the application seldom needs to update data and at the same time, application also needs to avoid “dirty read” and “repeatable read”, this kind of concurrency strategy can be employed. The transactional cache strategy provides support for fully transactional cache providers such as JBoss TreeCache. The following table lists cache concurrency strategy supported by various cache providers. Cache Read-only Nonstrict-read-write Read-write Transactional Hashtable YES YES YES N/A EHCache YES YES YES N/A OSCache YES YES YES N/A SwarmCache YES YES N/A N/A JBoss TreeCache YES N/A N/A YES Cluster Cache (in different JVMs) Hibernate also supports cluster caching in disparate JVMs. At present, both SwarmCache and JBoss TreeCache support cluster caching across multiple JVMs. In some situations, especially at the level of enterprise, certain application has to support the concurrency accessing of thousands of users, at that time, cluster cache can help you because the cluster can provide failover and load balancing which improve the performance of application. Points to Note When employing one of the four cache strategies above, pay close attention to the following situation: Data cached almost immutable If data you want to cache is almost constant, you can use data caching which can improve the performance of the application. On the contrary, if the caching data are quiet volatile, Hibernate have to maintain and update the caching over time which extremely leads to performance hit. Data sizes in reasonable range If the size of data you is caching is massive, Hibernate will occupy the most memories of system, which causes the long waiting time of the whole application. Low frequency of data updating If data you are caching needs to be modified frequently, Hibernate have to take an array of time to update and modify the data in caching, which impacts the performance of the application as well. High frequency of data querying If data you are caching is steady, which means that most of the operations are querying, searching, no updating and modifying, making the most use of caching will be affording huge performance improvement. None crucial data Because of existing some incongruities when keeping the data in caching, so if the data you are caching is fairly crucial, do not use caching. By contrast, if the data in caching is insignificant, just use it without any vacillation. Summary Actually, after employing SQL Optimization, Session Management, Data Caching, we will obtain great battalions of performance gains, which make applications achieve acceptable waiting time for the final customers. External Links for Further Study http://www.hibernate.org/hib_docs/reference/en/html/performance.html http://blogs.jboss.com/blog/acoliver/2006/01/23/Hibernate_EJB3_Tuning.txt About Author I am Wings Jiang from BCM China. I have mainly focused on J2EE technologies in recent years and worked in several projects involving Struts/Tapestry, Spring, Hibernate, WebLogic, Websphere, Oracle, DB2 etc. I have experience in design and code of several Java applications. Hibernate performance is one of the areas I pay close heed to in my current working.
June 10, 2009
by Ming Jiang
· 141,811 Views · 4 Likes
article thumbnail
Android: Zip Download of Cupcake Android v1.5 Source Code
a great way to learn about a java library and framework is to browse through their innards (source code) ad hoc-ly during project development. sometimes a method or a class that seems so simple in name might do much more, and end up creating unexpected side-effects which results in hard-to-debug code. in addition, api documentation tends to be vague and brief that does not delve deeply enough into detail. hence, the source code of the java library and framework is an indispensable resource for software development. this following article is written by http://geekycoder.wordpress.com this is especially the case for android mobile application development where it is still relatively new in term of maturity and acceptance. there is currently one android phone available in the market and the forthcoming v1.5 android platform codename cupcake makes android development all the more challenging. hence having the full source code of android can at least assist uou in understanding and learning what is still a new mobile platform. however, the android sdk does not come with source code and it is up to the developer to download it from the google code server. it is quite involving to download this source code so what if someone has already done the hard work of getting and packaging the source code for you? thanks to someone by the name of rgruet in http://androidforums.com/android-developers/1045-source-code-android-jar.html who consolidated the source code of android v1.5 into a single zip file, i packed the sources for android 1.5 (not a piece of cupcake , and made the archive temporarily available at http://rgruet.free.fr/public/android…upcake-src.zip (21.6mb). please mirror it elsewhere before my isp kills me! create a directory sources/ inside your /platforms/android-1.5/ directory, and unzip the archive there. richard there are currently three known sources to download the source code (21.6mb). http://rgruet.free.fr/public/android-1.5-cupcake-src.zip ( rgruet ) http://www.digginmobile.com/android.asp http://www.mediafire.com/download.php?ulnovo4wzde (my mirror) oh yes, download smart, use a download accelerator. if possible, mirror the download.
May 27, 2009
by James Sugrue
· 44,536 Views
article thumbnail
Introduction to the Open eHealth Integration Platform
The Open eHealth Integration Platform (IPF) is an extension of the Apache Camel routing and mediation engine and comes with comprehensive support for message processing and connecting information systems in the healthcare sector. It is available under the Apache License version 2.0. IPF and Camel both focus on a domain-specific language (DSL) to implement and combine Enterprise Integration Patterns (EIPs) in integration solutions. IPF leverages the Groovy programming language for application development and for extending the Apache Camel DSL. One example of a healthcare-related use case of IPF is the implementation of interfaces for transactions specified in IHE profiles. The use of IPF to implement actor interfaces for the IHE PIX and PDQ profiles was tested successfully at the 2009 Connect-a-thon. The actual actors were proprietary systems that were IHE-enabled via IPF-based integration solutions. It is important to note that usage of IPF is not just limited to the healthcare domain. It can also be used to build integration solutions for several other domains. However, this article will focus primarily on the healthcare-specific features of IPF. Riding the Camel IPF is built on top of the Apache Camel routing and mediation engine. This section deals briefly with the concepts behind Camel. For a more detailed overview, read Jonathan Anstey's excellent introductory article Apache Camel: Integration Nirvana. Apache Camel is about Enterprise Integration Patterns (EIPs). EIPs have previously been described by Gregor Hohpe and Bobby Woolf in their book Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions. They represent experiences of integration architects and can be used as building blocks for designing integration solutions. These patterns were published as recommendations without implying a concrete implementation. This is where Apache Camel comes in. Camel was created to provide implementations for EIPs. With Apache Camel, integration solutions are developed by combining integration patterns using a domain-specific language (DSL). In addition to EIP implementations, Camel also provides more than 60 components for connecting to a great variety of transports and APIs. The four major concepts in Camel are components, endpoints, processors and the domain-specific language (DSL). Components provide connectivity to other systems. From components, endpoints are created for sending and receiving messages. Endpoints are uniquely identified by their URIs. Processors are used to route and transform messages between endpoints. To wire endpoints and processors together, Camel provides a DSL for Java. Consider a simple example: from("jms:queue:validated") .filter().xpath("/person[@name='Martin']") .to("http://www.example.com/camel"); In this route definition, messages are read from a JMS queue (identified by the jms:queue:validated endpoint URI) and sent through a filter. The filter criterion is an XPath predicate. Any message that passes the filter will be POSTed to the http://www.example.com/camel endpoint. Camel also supports a Spring-based XML configuration for creating message processing routes (not shown here). Riding IPF Any feature provided by Camel can be used in combination with any other features provided by IPF. IPF makes its features available via extensions to the Camel DSL. These extensions have been implemented via Groovy meta-programming. For these extensions to be used in an IPF application, route definitions must be written in Groovy. Here is an example of a route definition that uses IPF's DSL extensions: from('file:input') // read HL7 message from file .unmarshal().ghl7() // create HL7 message object .validate().ghl7() // validate HL7 message object .filter {exchange -> // filter message using criteria defined by closure def msg = exchange.in.body // use exchange.in.body to access HL7 message object msg.PID[8].value == 'F' // use HL7 DSL to access and compare PID-8 field value } .to('http://...') // send message to destination (via HTTP In this route, an HL7 message is read from a file, validated and then filtered based on the value of the 8th field in the PID segment. To obtain this field value, the filter closure uses IPF's HL7 DSL. This DSL is explained in detail in the next section. If the message passes the filter it is forwarded to its destination via HTTP. The route definition uses the DSL elements from, unmarshal, filter and to from Camel directly, all other DSL elements are extensions provided by IPF, including the use of closures for filter criteria. IPF DSL extensions can be used as if they are native Camel DSL elements. Furthermore, the DSL used in applications is not just limited to the DSL provided by Camel and IPF. Application-specific DSL extensions can also be written using IPF's DSL extension mechanism. This mechanism also supports modularization of DSL definitions. Any component can contribute its own DSL extensions. Consequently, the scope of the overall DSL depends on which components were deployed for the application. Inside an OSGi environment, IPF can even automatically detect and activate DSL extensions provided by different bundles. The following sections will explore the healthcare-specific features of IPF in greater detail. For a detailed description of all IPF features consult the IPF reference documentation. For a more hands-on guide on how to write IPF applications, the IPF tutorials are a good starting point. HL7 message processing HL7 (Health Level 7) is an ANSI-accredited standards developing organization (SDO) in the healthcare sector. Among other standards it focuses on developing messaging standards for the clinical and administrative domain. This standard is often referred to as the HL7 messaging standard. There are several versions of this standard. HL7 version 2.x is widely used, the most recent update was version 2.6 in 2007. It differs significantly from the XML-based HL7 version 3. The following subsections focus on IPF's support for HL7 version 2.x. Support for HL7 version 3 is currently under development. IPF uses the open source HAPI library as its basis for HL7 version 2 message processing. HL7 version 2 at a glance HL7 version 2 messages have a hierarchical structure and are organized into groups, segments, fields and datatypes which can also repeat. Message elements are referenced by their path within the hierarchy (see navigation syntax in the following figure). HL7 DSL The core of IPF's HL7 message processing capabilities is the HL7 DSL. This is a domain-specific language for accessing and manipulating HL7 version 2 messages. The IPF library that implements this DSL (modules-hl7dsl) can also be used standalone (i.e. independent from other IPF components) in any Groovy application. Seamless integration into the IPF DSL is provided as well. The following examples presume a certain degree of familiarity with HL7 version 2 message structures and terms. Constructing messages The entry point to the HL7 DSL is IPF's MessageAdapter. To create a MessageAdapter instance from an HL7 file we use the load method from the MessageAdapters utility class. import org.openehealth.ipf.modules.hl7dsl.MessageAdapter import org.openehealth.ipf.modules.hl7dsl.MessageAdapters MessageAdapter message = MessageAdapters.load('ADT-A01.hl7') This loads the HL7 file ADT-A01.hl7 from the classpath. Accessing message content The following example obtains the PID segment contained in the PATIENT group which itself is contained in the first repetition of the repeatable PATIENT_RESULT group. // repeating elements are indexed from 0 to n def segment = message.PATIENT_RESULT(0).PATIENT.PID The function call operator () is used to refer to an element in a repetition. The element index is passed as argument. Obtaining fields is similar to obtaining groups and segments except that fields are often referred to by index rather than by name. To obtain the MSH-3 field from a message we can write: // fields are indexed from 1 to n def composite = message.MSH[3] If the field is a composite we access the second component with: // components of a composite field are indexed from 1 to n def primitive = message.MSH[3][2] or, equivalently, def primitive = message.MSH.sendingApplication.universalIDType As shown above, navigation is also possible using field names instead of indices. Care must be taken, because along with the change of internal message structures, individual field names change between HL7 versions, even when they refer to the same position of the field in a segment. If the version of the HL7 message is not known in advance, it is better to use the more concise index notation. Fields may also repeat. To obtain a given element of a repeating field the function call operator () is used, just like with groups and segments. In the next example we obtain the first element of the repeating NK1-5 field. Because NK1 is a repeating segment, the function call operator is used on segment-level, too. def field = message.NK1(0)[5](0) def fieldList = message.NK1(0)[5]() Omitting the repetition index returns a list of repeating elements. Omitting the function call operator, the first repetition of a group, segment or field is assumed. This is called smart navigation: assert message.NK1(0)[5](0)[1].value == message.NK1[5](0)[1].value assert message.NK1(0)[5](0)[1].value == message.NK1[5][1].value assert message.PATIENT_RESULT(0).PATIENT.PID[5][1] == message.PATIENT_RESULT.PATIENT.PID[5][1] If a component is omitted, the first component or subcomponent of a composite is assumed assert message.NK1(0)[5](0)[1].value == message.NK1[5].value assert message.NK1(0)[5](1)[1].value == message.NK1[5](1).value assert message.NK1(0)[2][1][1].value == message.NK1[2].value Using smart navigation, the expressions are usually shorter and less error-prone. Moreover, in many cases the same expression can be used for different HL7 versions, making the DSL more portable. Modifying message content A segment of one message can be assigned the segment value of another message using the assigment operator (=). The following example copies the EVN segment from message2 to message1. message1.EVN = message2.EVN To change a field value we navigate to that field (either by name or index, as shown above) and assign it a string or another field value. def msh = message.MSH def nk1 = message.NK1(0) msh[5] = nk1[4][4] msh[5] = 'abc' Composite fields may also be changed by assigning other composite fields. In the following example we copy the composite NK1(0)[4] field from message2 to message1. message1.NK1(0)[4] = message2.NK1(0)[4] Externalizing messages The left-shift operator (<<) appends the string-represenation of a MessageAdapter object to a writer. In the following example, we write an HL7 message to System.out. MessageAdapter message = ... System.out << message To obtain the string-representation directly, we can use the MessageAdapter.toString() method. MessageAdapter message = ... def rendered = message.toString() Usage in route definitions This section shows a few examples how to combine the HL7 DSL with IPF's route definition DSL. The unmarshal().ghl7() extension should be used to create a MessageAdapter object from an external HL7 message representation. The created MessageAdapter object can then be used in subsequent processors. from('file:input') .unmarshal().ghl7() .process {exchange -> MessageAdapter message = exchange.in.body ... } ... The reverse operation marshal().ghl7() marshals a MessageAdapter object into a stream. This is often needed for transmitting HL7 messages over a variety of transports such as JMS, for example. from('file:input') .unmarshal().ghl7() ... .marshal().ghl7() .to(jms:queue:validated) Another usage example is content-based routing. In the following example a message is routed to different destinations depending on the content of the MSH[4] field. Here we use closures in combination with Camel's when DSL element for implementing routing rules. The it variable inside closures represents a message exchange. from(...) .unmarshal().ghl7() ... .choice() .when { it.in.body.MSH[4].value == 'ABC' } .to(...) .when { it.in.body.MSH[4].value == 'DEF' } .to(...) .otherwise() .to(...) HL7 validation IPF also adds support for specifying validation rules in a way that is easy to write and simple to understand. It facilitates the definition of custom validation rules by providing a dedicated validation DSL. Like the HL7 DSL, the validation DSL can also be used standalone but also integrates well into the IPF DSL for defining message processing routes. The IPF component that implements HL7 validation is modules-hl7. Validation rules are defined by extending the ValidationContextBuilder class of IPF. The validation rules DSL is provided by the RuleBuilder class. The following example defines a subset of segments from the HL7 version 2.2 specification. package example import ca.uhn.hl7v2.validation.ValidationContext import org.openehealth.ipf.modules.hl7.validation.builder.RuleBuilder import org.openehealth.ipf.modules.hl7.validation.builder.ValidationContextBuilder class SampleRulesBuilder extends ValidationContextBuilder { RuleBuilder forContext(ValidationContext context) { new RuleBuilder(context) .forVersion('2.2') .message('ADT', 'A01').abstractSyntax( 'MSH', 'EVN', 'PID', [ { 'NK1' } ], 'PV1', [ { INSURANCE( 'IN1', [ 'IN2' ] , [ 'IN3' ] )}] ) } } The sequence and cardinality of groups and segments is defined in a syntax that is very closely related to the HL7 Abstract Message Syntax. The message must contain the segments MSH, EVN, PID and PV1; it may contain zero or more NK1 segments and it may contain a repeatable INSURANCE group. In a next step we configure our SampleRulesBuilder in a Spring application context along with a ValidationContextFactoryBean. The ValidationContextFactoryBean auto-detects any beans of type ValidationContextBuilder and adds their validation rules to a ValidationContext that is used in route definitions. The validate().ghl7() DSL extension, which we have already seen, can be configured with a custom validation profile using the profile() DSL extension. The validation context is looked up from the Spring application context via bean(ValidationContext.class). import ca.uhn.hl7v2.validation.ValidationContext import org.apache.camel.spring.SpringRouteBuilder class SampleRouteBuilder extends SpringRouteBuilder { void configure() { from(...) .unmarshal().ghl7() .validate().ghl7().profile(bean(ValidationContext.class)) ... .to(...) } } Code mapping HL7 message processing often involves mapping between code systems i.e. from one set of codes into a corresponding different set of codes. For example, HL7 version 2 and HL7 version 3 use different code systems for most coded values such as message type, gender, clinical encounter type, marital status codes, address and telecommunication use codes, just to mention a few. IPF defines a mapping service that provides the mapping logic. This may be a simple map but it can also be a facade to a remote mapping or terminology service. IPF's default mapping service implementation, the BidiMappingService, supports bidirectional mappings and reads custom mapping definitions from mapping files. An instance of the BidiMappingService can be created with the following bean definition. The mapping service references a mapping file example.map on the classpath. If there is more than one mapping file, a list can be provided via the mappingScripts property. Here is the content of example.map: mappings = { encounterType(['2.16.840.1.113883.12.4','2.16.840.1.113883.5.4'], E : 'EMER', I : 'IMP', O : 'AMB' ) } The example mapping file is a Groovy script and contains a single mapping with three entries for encounter type codes. Also defined are the ISO Object Identifiers (OIDs) for the key and value code systems. The mapping service can now be accessed either directly or via methods on java.lang.String. The String.map() method maps the codes on the left side to the right side. The identifier for the mapping can either be passed as argument assert 'E'.map('encounterType') == 'EMER' assert 'X'.map('encounterType') == null assert 'X'.map('encounterType', 'DEFAULT') == 'DEFAULT' or as part of a method name. assert 'E'.mapEncounterType() == 'EMER' assert 'X'.mapEncounterType() == null assert 'X'.mapEncounterType('DEFAULT') == 'DEFAULT' A dynamic dispatch is used to select the mapping definition from the method name. The method names must therefore correspond to the registered mappings. Mapping in the reverse direction is equally possible. assert 'EMER'.mapReverse('encounterType') == 'E' assert 'EMER'.mapReverseEncounterType() == 'E' Code systems are often associated with a globally unique identifier, usually in form of an OID. The identifier of both sides of a mapping can be obtained as follows. assert 'encounterType'.keySystem() == '2.16.840.1.113883.12.4' assert 'encounterType'.valueSystem() == '2.16.840.1.113883.5.4' Code mapping methods may also be used in combination with the HL7 DSL. MessageAdapter message = ... assert message.PV1.patientClass.value == 'I' assert message.PV1.patientClass.map('encounterType') == 'IMP' assert message.PV1.patientClass.mapEncounterType() == 'IMP' Response messages HL7 messaging often requires the return of an HL7 response message to the sender. With IPF, positive (ACK) or negative (NAK) acknowledgments to messages can be generated. Acknowledgments are in the same HL7 version as the original message and are populated with arguments to the ack() method. MessageAdapter message = ... def ack = message.ack() def nak1 = message.nak('Reason for failure') def nak2 = message.nak(new HL7Exception('Reason for failure', 204)) Generating acknowledgments is, however, only one special case of generating a response to an original message. For responses other than acknowledgements, a response message prototype can be created via the respond(eventType, triggerEvent) method. The MSH and MSA segments of the response message are then populated as required by the HL7 specification. def rsp = msg.respond('RSP','K21') // generates a RSP_K21 message More features So far, the main focus has been on HL7 message processing. IPF has many more features and services to support the development and the operation of production-quality integration solutions. Some of them are briefly described in the following list. A detailed description would far exceed the scope of this paper. For a complete overview refer to the IPF reference documentation. Core features. Collection of domain-neutral message processors and DSL extensions usable for general-purpose message processing including support for Groovy XML processing and support for using closures with Camel DSL elements. OSGi support. Support for running IPF and its services inside an OSGi environment and for the development of OSGi-ready IPF applications. Flow management. A service for monitoring and managing message flows through IPF applications. The flow manager also supports a replay of messages for e.g. recovery from failures. Large message support. Allows for memory-efficient processing of large messages. Event infrastructure. An infrastructure for publishing and consuming system and application events. Can be used e.g. for separating logging, audit or statistics concerns from application-specific route definitions. Can also be used to integrate with complex event processing (CEP) engines. Outlook Upcoming IPF releases will provide support for CDA (Clinical Document Architecture) and IHE (Integrating the Healthcare Enterprise). CDA is an XML-based document markup standard that specifies the structure and semantics of a clinical document for the purpose of exchange. IHE is an initiative of healthcare professionals and industry to improve the way computer systems in the healthcare sector share information. The goal of IPF is to make it as easy as possible for developers to implement the CDA, IHE (and other clinical) standards in their applications. Here are a few examples of what to expect in the next IPF release. CDA support IPF's CDA support will focus on building CDA documents using a domain-specific language. This DSL supports the creation of structurally correct CDA documents by enforcing CDA-relevant schema definitions but without dealing with low-level XML details. The DSL is implemented by a custom Groovy builder, the CDABuilder. In the following code snippet we use the CDABuilder to create a CDA document using CDA-specific terms such as clinicalDocument, code, title, recordTarget and so on. For printing the created document to stdout we use the left-shift (<<) operator. // Create a CDA builder CDABuilder builder = new CDABuilder() // Create a new CDA document def document = builder.build { clinicalDocument { id(root:'2.16.840.1.113883.19.4', extension:'c266') code( code:'11488-4', codeSystem:'2.16.840.1.113883.6.1', codeSystemName:'LOINC', displayName:'Consultation note' ) title('Good Health Clinic Consultation Note') recordTarget { patientRole { id { extension="12345" root="2.16.840.1.113883.19.5" } patient { name { given('John') family('Doe') } birthTime('19320924') } //... } //... } //... } //... } // Write document XML to stdout System.out << document CDA support will also include support for selected CDA profiles from IHE, HL7/ASTM and HITSP specifications, for example XPHR and CCD. Profile-specific CDA DSL extensions will enforce the constraints imposed by the profile specifications. As an example, predefined CDA sections could then be added without knowing their templateID-OIDs or their exact nested XML structure. DSL support for parsing, validating, transforming and rendering CDA documents will complete the feature set. IHE support IPF's IHE support is a framework for creating actor interfaces as specified in IHE profiles. Most likely, support for the XDS profile will be the first to come. XDS stands for Cross-Enterprise Document Sharing and deals with registration and distribution of, and access to clinical documents across health enterprises. Central to this profile are the actors document registry and document repository. A number of document management systems could in principle act as registry and/or repository in the XDS profile. Most of these, however, do not support the XDS actor interface specifications right out of the box. This is were IPF comes in. It helps developers to build IHE actor interfaces for existing information systems. Consider this example: from('ihe:xds.b:iti-41?port=8080') .process { exchange -> def document = exchange.in.body // do further document processing here ... } // communicate with your document management system .to('http://...') // notify about availability of new document .to('ihe:nav:iti-25:[email protected]') This route starts a server to receive documents according to the ITI-41 transaction of the XDS.b IHE profile. ITI-41 is the Provide and Register Document Set transaction in XDS.b. XDS.b requires documents to be transported via SOAP and ebXML standards. To free developers from having to deal with low-level SOAP/ebXML handling, these communication details are hidden inside an ihe component (eventually there may be more than one). Subsequent processors can access the transported document without having to deal with ITI-41 details. After processing, the incoming document is uploaded to a document management system and, finally, [email protected] is notified about the availability of a new document. Notifications are sent according to the IHE NAV profile where NAV stands for Notification of Document Availability. This example is of course oversimplified (for instance it does not address responses, etc) but it still gives an idea of the abstraction level on which IHE interfaces can be implemented for existing systems. Conclusion Apache Camel is a good answer to many of today's integration problems. It provides a DSL for implementing Enterprise Integration Patterns and offers developers a simple and efficient way to deal with the diversity of applications and transports in distributed systems. IPF brings the power of Apache Camel to the healtcare domain and makes healthcare IT standards usable by means of a domain-specific language that closely resembles the language of domain experts. The DSL extension mechanism permits the evolution of even more specialized healthcare DSLs. IPF's support for DSL modularization makes these DSLs and their implementing components reusable in different integration scenarios. Author Martin Krasser is a software architect and engineer working for InterComponentWare AG. He focuses on distributed systems, application integration and application security. Martin is the founder and project lead of the open source IPF project.
May 11, 2009
by Martin Krasser
· 46,090 Views · 2 Likes
article thumbnail
Enterprise Integration Patterns with Apache Camel Refcard Now Available!
Apache Camel is a powerful open source integration platform based on Enterprise Integration Patterns with Bean Integration. This Refcard provides you with eleven of the most essential patterns that anyone working with integration must know. This Refcard is targeted for software developers and enterprise architects, but anyone in the integration space can benefit as well. Download Now! About the Author: Claus Ibsen is a passionate open-source enthusiast who specializes in the integration space. As an engineer in the FuseSource Open Source Division he works full time on Apache Camel, FUSE Mediation Router (Apache Camel Enterprise) and related projects. Claus is very active in the Apache Camel and Fuse communities, writing blogs, twittering, assisting on the forums, irc channels and is driving the Apache Camel roadmap.
March 30, 2009
by Wei Ling Chen
· 4,854 Views
article thumbnail
Apache Camel: Integration Nirvana
Take any integration project and you have multiple applications talking over multiple transports on multiple platforms. As you can imagine, in large enterprise applications this can get complex very fast. Much of the complexity stems from two issues: 1. dealing with the specifics of applications and transports, and 2. coming up with good solutions to integration problems. Making your applications speak transports and APIs is relatively easy on its own. I'm sure everyone knows how to send JMS messages to their broker of choice; though it still requires in depth knowledge of the JMS specification, which many developers may not have. On top of that, what happens when you want to route that JMS message to another application? You then have to take care of mapping the JMS message to the application plus handle any new concepts related to the application. Add a dozen other applications into the mix and you've got quite a headache on your hands. Ignoring the mechanics of how to connect with multiple transports and APIs, we can focus on the high level design of how applications interact. Fortunately, most solutions to enterprise integration problems have been formalized already. Gregor Hohpe and Bobby Woolfe's book, Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions, boils down years of experience from enterprise architects into a set of sixty five Enterprise Integration Patterns (EIPs). This is great but we still have to hand code all parts of these patterns; these are not packaged solutions, only recommendations. Apache Camel was created with the intention of addressing these two issues. In this article I'll show you how it actually does this. What is Camel? Apache Camel is an open source Java framework that focuses on making integration easier and more accessible to developers. It does this by providing: • concrete implementations of all the widely used EIPs • connectivity to a great variety of transports and APIs • easy to use Domain Specific Language (DSL) to wire EIPs and transports together Figure 1 shows how these three items actually map to Camel concepts. To give you a good understanding of how Camel is organized, we will discuss Components, Endpoints, Processors, and the Domain Specific Language (DSL). There is of course a lot more going on here under the hood but we'll leave that for another discussion. Figure 1: High level view of Camel's architecture. Components are the extension point in Camel to add connectivity to other systems. The core of Camel is very small to keep dependencies low, promote embeddability, etc. and as a result contains only 12 essential components. There are over 60 components outside the core. To expose these systems to the rest of Camel, Components provide an Endpoint interface. By using URIs, you can send or receive messages on Endpoints in a uniform way. For instance, to receive messages from a JMS queue aQueue and send them to a file system directory "c:/tmp", you could use URIs like "jms:aQueue" and "file:c:\tmp". Processors are used to manipulate and mediate messages in between Endpoints. All of the EIPs are defined as Processors or sets of Processors. As of writing, Camel supports 41 patterns from the EIP book, 6 other integration patterns, and many other useful Processors. To wire Processors and Endpoints together, Camel defines a Java DSL. The term DSL is used a bit loosely here as it usually implies the involvement of a compiler or interpreter that can process keywords specific to a particular domain. In Camel, DSL means a fluent Java API that contains methods named like terms from the EIP book. Its best explained with an example from("jms:aQueue") .filter().xpath("/person[@name='Jon']") .to("file:c:\tmp"); Here we define a routing rule in a single Java statement that will consume messages from the "jms:aQueue" Endpoint, send them through a Message Filter Processor, which will then send on messages passing the XPath condition to the "file:c:\tmp" endpoint. Messages failing the condition will be dropped. You can also configure your routes in a XML-based Spring configuration file. This configuration file is a lot more verbose and less auto complete friendly than the Java DSL; many prefer it though because of its direct access to Spring concepts and no requirement for compilation after changes. Here is what the earlier example would look like in Spring: /person[@name='Jon'] These are the concepts that Camel was built upon. Since then many other interesting features have been added. Details of these are left up to the reader to investigate. To get you started, some of these include: • Pluggable data formats and type converters for easy message transformation between Artix Data Services, CSV, EDI, Flatpack, HL7, JAXB, JSON, XmlBeans, XStream, Zip, Camel-bindy, etc. • Pluggable languages to create expressions or predicates for use in the DSL. Some of these languages include: EL, JXPath, Mvel, OGNL, BeanShell, JavaScript, Groovy, Python, PHP, Ruby, SQL, XPath, XQuery, etc. • Support for the integration of beans and POJOs in various places in Camel. • Excellent support for testing distributed and asynchronous systems using a messaging approach • and much more... Example A motorcycle parts business, Rider Auto Parts, supplies parts to motorcycle manufacturers. Over the years they've changed the way they receive orders several times. Initially, orders were placed by uploading CSV files to an FTP server. The message format was later changed to XML. Currently they provide a web site to submit orders as XML messages over HTTP. All of these messages are converted to an internal POJO format before processing. Rider Auto Parts states to any new customers to use the web interface to place orders. However, because of existing agreements with customers, they must keep all the old message formats and interfaces up and running. Solution using EIPs Rider Auto Parts faces a pretty common problem; over years of operation businesses acquire software baggage in the form of transports/data formats that are popular at the time. Using patterns from the EIP book we can envision the solution as something like Figure 2. Figure 2: This shows the solution to Rider Auto Parts integration problem using notation from the Enterprise Integration Patterns book. So we have several patterns in use here. 1. There are two Message Endpoints; one for FTP connectivity and another for HTTP. 2. Messages from these endpoints are fed into the incomingOrderQueue Message Channel 3. The messages are consumed from the incomingOrderQueue and routed by a Content-Based Router to one of two Message Translators. As the EIP name implies, the routing destination depends on the content of the message. In this case we need to route based on whether the content is a CSV or XML file. 4. Both Message Translators convert the message content into a POJO, which is fed into the orderQueue Message Channel. The whole section that uses a Content-Based Router and several Message Translators is referred to as a Normalizer. This composite pattern has a unique graphic to depict it but was left out here in favor of its sub-patterns to make things clearer. Implementation using Camel As mentioned before, Camel has a small core set of components included by default. The rest of the components exist as separate modules. In applications that require many types of connectivity it is useful to figure out what Camel modules to include. Listing 1 shows the dependencies using Apache Maven for the Camel implementation of the Rider Auto Parts example. Of course, you don't need to use Apache Maven for dependencies - it is just the easiest way to rapidly add new dependencies to your applications. The list of dependencies includes support for core Camel, ActiveMQ, JAXB marshaling, CSV marshaling, and HTTP. To make the example easier to try out, I've opted to use the File endpoint instead of the FTP. If we were using the FTP endpoint we would need to add a dependency on the camel-ftp module as well. Listing 1: Maven dependencies for the Camel implementation org.apache.camel camel-core ${camel-version} org.apache.camel camel-spring ${camel-version} org.apache.activemq activemq-camel ${activemq-version} org.apache.camel camel-jaxb ${camel-version} org.apache.camel camel-csv ${camel-version} org.apache.camel camel-jetty ${camel-version} org.apache.activemq activemq-core ${activemq-version} org.apache.xbean xbean-spring ${xbean-spring-version} While it is perfectly legitimate to use Camel as a standalone Java application, it is often useful to embed it in a container. In this case, we will be loading Camel from Spring. The Spring beans XML file is shown in Listing 2. First we start an embedded Apache ActiveMQ broker and connect Camel to it. We also load up some helper beans that we will reference from the DSL. Finally, the camelContext element tells Camel to look for routes in the org.fusesource.camel package. Routes are Java classes that extend the RouteBuilder class in Camel. Listing 2: Spring XML file that configures an embedded ActiveMQ broker, several beans used in the Camel route, and initializes the Camel Context to search for routes in the org.fusesource.camel package. org.fusesource.camel The real meat of the Camel implementation lies in the OrderRouter class (shown in Listing 3). This class extends RouteBuilder, so it will be automatically picked up and loaded by Camel's runtime. Looking back at Figure 2, we need to receive orders from an FTP (substituted with File) and HTTP endpoint, formatted as shown in Listing 4. In the DSL we can specify these incoming endpoints with two from elements. Both from elements are connected to a to("jms:incomingOrderQueue") element, which will send the messages to a queue on the ActiveMQ broker. Listing 3: Route definitions for the example. The routing rules are specified using a fluent API, referred to as Camel's DSL. public class OrderRouter extends RouteBuilder { @Override public void configure() throws Exception { JaxbDataFormat jaxb = new JaxbDataFormat("org.fusesource.camel"); // Receive orders from two endpoints from("file:src/data?noop=true").to("jms:incomingOrderQueue"); from("jetty:http://localhost:8888/placeorder") .inOnly().to("jms:incomingOrderQueue") .transform().constant("OK"); // Do the normalization from("jms:incomingOrderQueue") .convertBodyTo(String.class) .choice() .when().method("orderHelper", "isXml") .unmarshal(jaxb) .to("jms:orderQueue") .when().method("orderHelper", "isCsv") .unmarshal().csv() .to("bean:normalizer") .to("jms:orderQueue"); } } In the case of the HTTP endpoint, there are a couple of extra things to mention. First off the HTTP client will be expecting a response from the application so we have to handle that. In Camel, we have full control over what the client gets back from the HTTP endpoint. Each response is determined by the last method in our current route definition (each Java statement is a route definition). In our case we use the transform method to set the response to the constant string "OK". Since we handle the response ourselves, we don’t want any response to come from the JMS incomingOrderQueue. To send to this queue in a fire-and-forget fashion we add the inOnly modifier. It is important to note at this point that when writing Camel DSL in a modern Java IDE, selection of the next processing step is easy because of auto complete. The auto complete feature basically gives you a list of processors (i.e. EIPs) to choose from at any point in your route. Since fluent APIs chain methods together, the only method you need to remember is the from; all other methods are shown via auto complete. Listing 4: Incoming message formats; XML on top, CSV below. "name", "amount" "brake pad", "2" The next section of DSL in Listing 3 specifies the Normalizer, complete with Content-Based Router and two Message Translators. First we specify that we want to consume messages from the incomingOrderQueue on the ActiveMQ broker. The content based routing of the messages is done with the choice and when methods. In our case, we want to send CSV messages to one Message Translator and XML messages to another. To check what type of message we have we will be using a simple Java bean shown in Listing 5. Of course, this is demonstration code only; for production cases you would want to add more thorough checking of content types. Listing 5: Java bean that contains helper methods to be used in the DSL. public class OrderHelper { public boolean isCsv(String body) { return !body.contains("> body) { List orderHeaders = body.get(0); List orderValues = body.get(1); return new Order(orderValues.get(0), Integer.parseInt(orderValues.get(1))); } } At this point, successfully normalized messages are sent to the orderQueue for processing by some other application at the Rider Auto Parts business. Conclusion In this article I've shown two common problems that an integration developer may face: dealing with the specifics of applications and transports, and coming up with good solutions to integration problems. The Apache Camel project provides a nice answer to both of these problems. As the example has shown, solving integration problems with Camel is straight forward and results in relatively concise code. In my opinion it is the closest thing to integration nirvana that we have today. Links Apache Camel – http://camel.apache.org FUSE Mediation Router (based on Apache Camel) – http://fusesource.com/products/enterprise-camel Enterprise Integration Patterns – http://www.enterpriseintegrationpatterns.com Jon’s Blog – http://janstey.blogspot.com Camel in Action book - http://www.manning.com/ibsen Article source code - http://repo.fusesource.com/maven2/org/fusesource/examples/rider-auto-example/1.0/rider-auto-example-1.0.zip Author Jonathan Anstey is a senior engineer working for Progress Software Corporation specializing in the enterprise integration space. Jon focuses mostly on Apache Camel and its Progress endorsed likeness, FUSE Mediation Router. He also works on the Apache ActiveMQ and Apache ServiceMix projects
March 23, 2009
by Jonathan Anstey
· 223,829 Views · 8 Likes
article thumbnail
Integrate OpenOffice with Java without Installing OpenOffice
Until a few days ago, I've always needed to work with the rather cumbersome Office Bean and UNO Runtime when integrating OpenOffice into a Java application. I also had to configure a whole bunch of things to force OpenOffice to play nicely with the Java integration. Two days ago, however, I found out about ODF Toolkit. It seems to be a relatively new project, independent since last year some time, though I could be wrong. What's especially interesting is the ODFDOM: ''ODFDOM is an OpenDocument (ODF) framework. It's purpose is to provide an easy common way to create, access and manipulate ODF files, without requiring detailed knowledge of the ODF specification. It is designed to provide the ODF developer community an easy lightwork programming API, portable to any object-oriented language.'' Here's a snippet of it in action: public static void main(String[] args) { try { OdfDocument odfDoc = OdfDocument.loadDocument(new File("/home/geertjan/test.ods")); OdfFileDom odfContent = odfDoc.getContentDom(); XPath xpath = odfDoc.getXPath(); DTMNodeList nodeList = (DTMNodeList) xpath.evaluate("//table:table-row/table:table-cell[1]", odfContent, XPathConstants.NODESET); for (int i = 0; i < nodeList.getLength(); i++) { Node cell = nodeList.item(i); if (!cell.getTextContent().isEmpty()) { System.out.println(cell.getTextContent()); } } } catch (Exception ex) { //Handle... } } Let's assume that the 'test.ods' file above has this content: From the above, the code listing would print the following: Cuthbert Algernon Wilbert And, as a second example, here's me reading the first paragraph of an OpenOffice Text document: public static void main(String[] args) { try { OdfDocument odfDoc = OdfDocument.loadDocument(new File("/home/geertjan/chapter2.odt")); OdfFileDom odfContent = odfDoc.getContentDom(); XPath xpath = odfDoc.getXPath(); OdfParagraphElement para = (OdfParagraphElement) xpath.evaluate("//text:p[1]", odfContent, XPathConstants.NODE); System.out.println(para.getFirstChild().getNodeValue()); } catch (Exception ex) { //Handle... } } On my classpath I have "odfdom.jar" and "xerces-2.8.0.jar". I don't necessarily have OpenOffice installed, which means I can very easily process a whole bunch of spreadsheets (or other OpenOffice output) without (a) installing OpenOffice and (b) faster than I would otherwise do, since OpenOffice doesn't need to be started up, via the Office Bean or otherwise. In fact, Aljoscha Rittner from Sepix, who told me about this project and who is using it in his commercial applications, reports that his processing has sped up to a fraction of the original, also because he doesn't need to handle the situation where OpenOffice would crash randomly in the middle of long running processes, such as during the night when there's no human interaction for restarting it.
February 7, 2009
by Geertjan Wielenga
· 50,452 Views
article thumbnail
Generic Repository and DDD - Revisited
Greg Young talks about the generic repository pattern and how to reduce the architectural seam of the contract between the domain layer and the persistence layer. The Repository is the contract of the domain layer with the persistence layer - hence it makes sense to have the contract of the repository as close to the domain as possible. Instead of a contract as opaque as Repository.FindAllMatching(QueryObject o), it is always recommended that the domain layer looks at something self revealing as CustomerRepository.getCustomerByName(String name) that explicitly states out the participating entities of the domain. +1 on all his suggestions. However, he suggests using composition, instead of inheritance to encourage reuse along with encapsulation of the implementation details within the repository itself .. something like the following (Java ized) public class CustomerRepository implements ICustomerRepository { private Repository internalGenericRepository; public IEnumerable getCustomersWithFirstNameOf(string _Name) { internalGenericRepository.fetchByQueryObject( new CustomerFirstNameOfQuery(_Name)); //could be hql or whatever } } Quite some time ago, I had a series of blogs on DDD, JPA and how to use generic repositories as an implementation artifact. I had suggested the use of the Bridge pattern to allow independent evolution of the interface and the implementation hierarchies. The interface side of the bridge will model the domain aspect of the repository and will ultimately terminate at the contracts that the domain layer will use. The implementation side of the bridge will allow for multiple implementations of the generic repository, e.g. JPA, native Hibernate or even, with some tweaking, some other storage technologies like CouchDB or the file system. After all, the premise of the Repository is to offer a transparent storage and retrieval engine, so that the domain layer always has the feel that it is operating on an in-memory collection. // root of the repository interface public interface IRepository { List read(String query, Object[] params); } public class Repository implements IRepository { private RepositoryImpl repositoryImpl; public List read(String query, Object[] params) { return repositoryImpl.read(query, params); } //.. } Base class of the implementation side of the Bridge .. public abstract class RepositoryImpl { public abstract List read(String query, Object[] params); } One concrete implementation using JPA .. public class JpaRepository extends RepositoryImpl { // to be injected through DI in Spring private EntityManagerFactory factory; @Override public List read(String query, Object[] params) { //.. } Another implementation using Hibernate. We can have similar implementations for a file system based repository as well .. public class HibernateRepository extends RepositoryImpl { @Override public List read(String query, Object[] params) { // .. hibernate based implementation } } Domain contract for the repository of the entity Restaurant. It is not opaque or narrow, uses the Ubiquitous language and is self-revealing to the domain user .. public interface IRestaurantRepository { List restaurantsByName(final String name); //.. } A concrete implementation of the above interface. Implemented in terms of the implementation artifacts of the Bridge pattern. At the same time the implementation is not hardwired with any specific concrete repository engine (e.g. JPA or filesystem). This wiring will be done during runtime using dependency injection. public class RestaurantRepository extends Repository implements IRestaurantRepository { public List restaurantsByEntreeName(String entreeName) { Object[] params = new Object[1]; params[0] = entreeName; return read( "select r from Restaurant r where r.entrees.name like ?1", params); } // .. other methods implemented } One argument could be that the query string passed to the read() method is dependent on the specific engine used. But it can very easily be abstracted using a factory that returns the appropriate metadata required for the query (e.g. named queries for JPA). How does this compare with Greg Young's solution ? Some of the niceties of the above Bridge based solution are .. The architecture seam exposed to the domain layer is NOT opaque or narrow. The domain layer works with IRestaurantRepository, which is intention revealing enough. The actual implementation is injected using Dependency Injection. The specific implementation engine is abstracted away and once agian injected using DI. So, in the event of using alternative repository engines, the domain layer is NOT impacted. Greg Young suggests using composition instead of inheritance. The above design also uses composition to encapsulate the implementation within the abstract base class Repository. However in case you do not want to have the complexity or flexibility of allowing switching of implementations, one leg of the Bridge can be removed and the design simplified From http://debasishg.blogspot.com/
January 20, 2009
by Debasish Ghosh
· 40,579 Views · 1 Like
article thumbnail
The Three Pillars of Continuous Integration
Continuous Integration commonly known as CI is a process that consists of continuously compiling, testing, inspecting, and deploying source code. In any typical CI environment, this means running a new build every time code changes within a version control repository. Martin Fowler describes CI as: A software development practice where members of a team integrate their work frequently, usually each person integrates at least daily - leading to multiple integrations per day. Each integration is verified by an automated build to detect integration errors as quickly as possible. Many teams find that this approach leads to significantly reduced integration problems and allows a team to develop cohesive software more rapidly. While CI is actually a process, the term Continuous Integration often is associated with three important tools in particular. As shown in the image the three pillars of CI are: 1. A version control repository like Subversion, or CVS. 2. A CI Server such as Hudson, or Cruise Control 3. An automated build process like Ant or Nant So, let’s look at each of these in detail: Version Control Repository: Version control repositories also known as SCM (source code management) play a crucial role in any software development environment. They also play a very important role for a successful CI process. The SCM is a central place for the team to store every needed artifact for the project. It is mandatory for the teams to put everything needed for a successful build into this repository. This includes the build scripts, property files, database scripts, all the libraries required to build the software and so on. The CI Server: For CI to function properly, we also need to have an automated process that monitors a version control repository and runs a build when any changes are detected. There are several CI servers available, both open source and commercial. Most of them are similar in their basic configuration and monitor a particular version control repository and run builds when any changes are detected. Some of the most commonly used open source CI servers are; Cruise Control, Continuum, and Hudson. Hudson is particularly interesting because of its ease of configuration and compelling plug-ins, which makes integration with test and static analysis tools much easier. Automated Build: The process of CI is about building software often, which is accomplished through the use of a build. A sturdy build strategy is by far the most important aspect of a successful CI process. In the absence of a solid build that does more than compile your code, CI withers. With automated builds, teams can reliably perform (in an automated fashion) otherwise manual tasks like compilation, testing, and even more interesting things like software inspection and deployment. Now that we have seen the important tools in our CI process, let’s see how a typical CI scenario looks like for a developer: CI server is configured to poll the version control repository continuously for changes. Developer commits code to the repository. CI server detects this change, and retrieves the latest code from the repository. This causes the CI server to invoke the build script with the given targets and options. If configured, CI Server will send out an e-mail to the specified recipients when a certain important event occurs. The CI server continues to poll for changes. Why is CI Important? This is one of the most frequently asked questions, and here are a few points to note about this powerful technique: Building software often greatly increases the likelihood that you will spot defects early, when they still are relatively manageable. Extends defect visibility. CI ensures that you have production ready software at every change. CI also ensures that you have reduced the risk of integration issues by building software at every change. CI server can also be configured to run continuous inspection which can assist the development team in finding potential bugs, bad programming practice, automatically check coding standards, and also provide valuable feedback on the quality of code being written. Over the past several months, I have assisted several companies in implementing CI. There was a little bit of resistance from the developers in the early stages when we implemented continuous feedback. But, never heard a single negative comment about this approach. If you already have a version control repository and automated builds, you are very close to the CI process. Download one of the open source CI servers, configure and setup a simple project. It should take less than an hour if you have automated build scripts. Start adding additional features like code inspections, generating reports, metrics, documentation and so on. Most important, send continuous feedback to your team. Give this process a try, you sure will be surprised to see how effective it is. And, as always share your thoughts, concerns or questions.
December 15, 2008
by Meera Subbarao
· 23,868 Views
article thumbnail
A Look Inside the JBoss Microcontainer, Part I -- Component Models
Looking at the current state of Java, we can see that POJOs (Plain Old Java Objects) rule the land yet again. Their dominance stretches from enterprise applications to middleware services. At JBoss we were known for our modular JMX-based kernel. The application server was nothing more than a bunch of flexible MBeans and a powerful MicroKernel in the middle. But, as you could feel the change is coming, we still wanted to be ahead of the pack. We could see different POJO based component models popping up all over the place (EJB3, JPA, Spring, Guice, … to name a few), yet nothing was out there that would bind them all, flattening out the differences on a single component model. Hence the Microcontainer project was born. The JBoss Microcontainer project is about many things. The Microcontainer's features range from reflection abstraction, a virtual file system, a simple state machine to transparent AOP integration, a new classloading layer, a deployment framework and an OSGi framework implementation. I'll try to address them all over a short series of articles that will be published here on DZone. This article will examine the Microcontainer's component models. Read the other parts in DZone's exclusive JBoss Microcontainer Series: Part 1 -- Component Models Part 2 –- Advanced Dependency Injection and IoC Part 3 -- the Virtual File System Part 4 -- ClassLoading Layer Part 5 - the Virtual Deployment Framework Part 6 - The Scanning Library What is a component model? What do we consider a component model? First of all, what do we consider being a component? One abstract way to express this would be that “components are reusable software programs that you can develop and assemble easily to create sophisticated applications.” To consider a bunch of components as an actual model, we also need to declare what kind of interactions we allow. JMX MBeans are one example of a component model. Their interactions include executing MBean operations, referencing attributes, setting attributes and declaring explicit dependencies between named MBeans. As mentioned, we had advanced JMX handling already with the MicroKernel. And as expected, the Microcontainer brought extensive POJO support. The default behavior and interactions in the Microcontainer are what you also normally get from any other IoC container and are similar to the functionality that MBeans provided: plain method invocations for operations, setters/getters for attributes and explicit dependencies. However, having only this functionality would mean we didn't get much further than just relieving the pain of declaring MBeans, hence it was only logical for us to do something more. I'll leave the discussion of these new IoC features for the next article in the series. There are many existing POJO component models out there, Guice and Spring being amongst the most popular. Effective integration with these frameworks was an important goal for us. Demo environment setup Before we begin, I'd like to first describe the various parts that constitute the demo. All the source code can be found at this location of our Subversion repository: • http://anonsvn.jboss.org/repos/jbossas/projects/demos/microcontainer/branches/DZone_1_0/ The project is fully mavenized, so it should be easy to adjust it to your IDE. I will first go over the sub-projects within the demo and describe their usage. At the end of my article series, I will provide a more detailed look at what certain sub-projects do. Below are the JBoss Microcontainer demos and sub-projects that are relevant for this article: • bootstrap (as the name suggests, it bootstraps the Microcontainer with demo code) • jmx (adds the JMX notion to demo's bootstrap) • models (source code of our components / services) The demo has only one variable you need to set - demos home - but even this one can be optional if you checked-out your project into the \projects\demos directory. Otherwise, you need to set the system property demos.home (e.g. -Ddemos.home=). You should now be able to run JMXMain as a main class. Make sure you include the models sub-project in the classpath, since some of the services require additional classes in the classpath, several more then what the jmx sub-project expects. Once the Microcontainer is booted it starts to scan the ${demos.home}/sandbox directory for any changes. Now all we need to do is provide a deployable unit and drop it in there. Models Let’s now turn our attention to the models sub-project. This is where the previously mentioned deployable unit should come from. You can see if everything is in place by building the models sub-project (mvn package) and dropping it into the sandbox. You should get a bunch of debug and info messages on the console log, showing how the Microcontainer got booted. Any error message indicates some problems. Let’s go over exactly what the models sub-project does, its integration code and try to redeploy it. If we look at the models src/main/resources/META-INF directory, we'll see plenty of -beans.xml resource files and one -service.xml. You’ll notice that each has a meaningful name that matches the source code package from models's src/main/java/org/jboss/demos/models directory. Let's dissect them one by one, starting with the ones that have no dependencies. org.jboss.demos.models.plain.PojoFactory This is a simple Micrcocontainer beans descriptor file. Anyone who crossed paths with some other IoC’s configuration file should be familiar with it. And, as I already mentioned, I'll follow up on more advanced usage in the next article. The next file shows what we have done to support Spring integration: Note that this file's namespace is different from the previous Microcontainer bean’s plain-beans.xml file. The urn:jboss:spring-beans:2.0 namespace points to our version of the Spring schema port, meaning you can describe your beans Spring style, but it's the Microcontainer that's going deploy then, not Spring's bean factory notion. public class Pojo extends AbstractPojo implements BeanNameAware { private String beanName; public void setBeanName(String name) { beanName = name; } public String getBeanName() { return beanName; } public void start() { if ("SpringPojo".equals(getBeanName()) == false) throw new IllegalArgumentException("Name doesn't match: " + getBeanName()); } } Although the SpringPojo bean has a dependency on Spring lib via implementing BeanNameAware interface, this dependency is only there to expose and mock some of the Spring's callback behavior (see SpringBeanAnnotationPlugin for more details). Since we introduced Spring integration, let's have a look at Guice integration. As Guice users know, Guice is all about type matching. Configuration of Guice beans is done via Modules which means that in order to generate beans, one must implement a Module. Two important parts to watch from this file are PojoModule and GuiceKernelRegistryEntryPlugin. The first one is where we configure our beans: public class PojoModule extends AbstractModule { private Controller controller; @Constructor public PojoModule(@Inject(bean = KernelConstants.KERNEL_CONTROLLER_NAME) Controller controller) { this.controller = controller; } protected void configure() { bind(Controller.class).toInstance(controller); bind(IPojo.class).to(Pojo.class).in(Scopes.SINGLETON); bind(IPojo.class).annotatedWith(FromMC.class).toProvider(GuiceIntegration.fromMicrocontainer(IPojo.class, "PlainPojo")); } } The second class provides integration with the Microcontainer: public class GuiceKernelRegistryEntryPlugin implements KernelRegistryPlugin { private Injector injector; public GuiceKernelRegistryEntryPlugin(Module... modules) { injector = Guice.createInjector(modules); } public void destroy() { injector = null; } public KernelRegistryEntry getEntry(Object name) { KernelRegistryEntry entry = null; try { if (name instanceof Class) { Class clazz = (Class)name; entry = new AbstractKernelRegistryEntry(name, injector.getInstance(clazz)); } else if (name instanceof Key) { Key key = (Key)name; entry = new AbstractKernelRegistryEntry(name, injector.getInstance(key)); } } catch (Exception ignored) { } return entry; } } Notice how we created an Injector from the Modules and then did a lookup on it for matching beans. In mbeans-service.xml we declare our legacy usage of MBeans: What’s interesting to note here is how we injected a POJO into an MBean. The preceding demonstrated our first interactions between different component models. In order to allow for MBean deployment via the Microcontainer, we had to write entirely new component model handling code. See the system-jmx-beans.xml for more details. The code from this file lives in the JBossAS source code: system-jmx sub-project. One note here, this is currently only possible with JBoss's JMX implementation, since the system-jmx code uses some implementation details. Now what if we wanted to expose our existing POJOs as MBeans, registering them into an Mbean server? @org.jboss.aop.microcontainer.aspects.jmx.JMX(exposedInterface=org.jboss.demos.models.mbeans.PojoMBean.class, registerDirectly=true) As you can see from looking at any of the beans in this file, in order to expose your POJOs as MBeans, it’s simply a matter of annotating them with an @JMX annotation. You can either expose the bean directly or its property: Here we see how you can use any of the injection lookup types by either looking up a plain POJO or getting a handle to an MBean from the MBean server. One of the injection options is to use type injection, which is also sometimes called autowiring: The FromGuice bean injects the Guice bean via type matching, where PlainPojo is injected with a common name injection. We then test if Guice binding works as expected: public class FromGuice { private IPojo plainPojo; private org.jboss.demos.models.guice.Pojo guicePojo; public FromGuice(IPojo plainPojo) { this.plainPojo = plainPojo; } public void setGuicePojo(org.jboss.demos.models.guice.Pojo guicePojo) { this.guicePojo = guicePojo; } public void start() { f (plainPojo != guicePojo.getMcPojo()) throw new IllegalArgumentException("Pojos are not the same: " + plainPojo + "!=" + guicePojo.getMcPojo()); } } This only leaves us with an alias component model. Even though the alias is quite a trivial feature, in order to implement it as a true dependency, it has to be introduced as a new component model inside the Microcontainer. The implementation details for this is part of the AbstractController source code: springPojo Here we’ve mapped the SpringPojo name to the springPojo alias. The beauty of having aliases as true component models is that it doesn't matter when the real bean gets deployed. This means that the alias will wait in a non-installed state until the real bean triggers it. Conclusion We've seen how we can deploy simple Microcontainer beans, legacy MBeans, Guice POJOs, Spring beans and aliases. And since all of this is controlled by the Microcontainer, we saw how easily we can mix and match the different component models. I can easily say, with the level of abstraction we put in our component model design, the sky is the limit on what we can handle. An example of this is the upcoming OSGi services, but that's another story, another article. Stayed tuned for my next article which will provide a detailed look at the Microcontainer's IoC functionality. About the Author Ales Justin was born in Ljubljana, Slovenia and graduated with a degree in mathematics from the University of Ljubljana. He fell in love with Java seven years ago and has spent most of his time developing information systems, ranging from customer service to energy management. He joined JBoss in 2006 to work full time on the Microcontainer project, currently serving as its lead. He also contributes to JBoss AS and is Seam and Spring integration specialist. He represent JBoss on 'JSR-291 Dynamic Component Support for Java SE' and 'OSGi' expert groups.
October 1, 2008
by Ales Justin
· 57,258 Views
article thumbnail
Ant or Gant?
Yes, this is exactly what I am frequently asked by my clients and many developers. It isn't easy to answer this question. There are several projects using Ant. Should you run away from Ant just because there is a new cool tool out there called Gant? Should you switch to Gant just because you dislike XML? Not at all. Let's take a closer look and see what might make you switch to Gant. When to choose Gant? 1. Complicated Build Files. If your ant build files are becoming too complicated, and hard to manage, it's time to see if using Gant can help. Let me explain what I mean by complicated build files. If you have too much of conditional logic within your build files, say something similar on the lines shown below in Listing 1: Code Listing 1: Or even something like this where you might be supporting deployment to different application servers based on some property in your build.properties as shown in listing 2. Code Listing 2: Things get out of hand when you have conditional logic as shown above in your build scripts. The listings I have are just the skeleton, imagine what happens when we start adding the actual deployment logic for all these application servers. It doesn't matter how you refactor this, it is still going to be very complicated. Trust me, I have written build scripts which were several thousand lines, and refactoring them was not a trivial task. 2. Custom Ant Tasks. I myself am guilty of writing many of these. There are many situations which arise in projects where we create custom ant tasks. It is simple once you know how to write one, and than for every complicated task you need to perform, you involuntarily will start writing custom ant tasks. Anyone writing a custom ant task will: a. Create a new class that extends Ant’s org.apache.tools.ant.Task class. b. For each attribute, write a setter method. c. Write an execute()method that does what you want this task to do. There isn't anything wrong in doing the above, but imagine each time you want to make a small change, you will have to make changes within your Java source code, compile, test, and re-package. 3. Scripting. You can extend Ant further by not writing custom ant tasks, but by using small snippets of code written in an interpreted language like JRuby, BeanShell, or Groovy. These code snippets can be placed within your build files or in separate text files. If you are using Groovy's Ant task, your build file might look something like this: Code Listing 3: import some.package import another.package def fullpath = "${.basedir}/${defaulttargetdir}" def somefile = new SomeFile(projectName:"${pname}", buildLabel:"${label}", buildTime:"${new Date()}") def xml = "${fullpath}/dashboard.xml" new File(path).write(somefile.generateReport()) ant.xslt(in:path, out:"${properties.defaulttargetdir}/some.html", style:"${properties.defaulttargetdir}/lib/report-style.xsl") Imagine having several lines of XML in your build files which have many of these small snippets of scripts. I myself don't like mixing and matching build files with code snippets. If you have a team where everyone is in the same page, everything works fine. What if a team member has no clue about any of the Scripting languages? He/She will have no clue how to make minor changes when things go badly. If you have all the above or even one of the above three cases, you seriously need to consider using Gant. To quote Aristotle: For the things we have to learn before we can do them, we learn by doing them." So, lets see how easy it is to learn Gant and see how things can improve. This part covers the very basics of Gant. The next part, will dive deeper into Gant by using it with a sample project to build an application, and we will also see how to use it with our CI Server. What's Gant? Gant is a build tool that uses both Groovy and Ant. With Gant, you describe your build process using Groovy scripts. Stated simply, Gant allows you to specify the build logic using Groovy instead of XML. The next thing you may ask is " Is Gant a competitor to Ant?". Let me quote from the Gant web site to make thing more clear here : Whilst it might be seen as a competitor to Ant, Gant uses Ant tasks for many of the actions, so Gant is really an alternative way of doing builds using Ant, but using a programming language rather than XML to specify the build rules. Download and Install Gant. In order for Gant to work, you should have Groovy installed. You can download and follow the installation instructions for Groovy here. As I said earlier also, in order to use Gant, you should have knowledge of Groovy as well. If you have never written Groovy code before, there are many interesting books on Groovy like: 1. Groovy in Action 2. Groovy Recipes 3. Groocy Refcardz You can also read the getting started guide on the Groovy web site, which should give you a good starting point. Download the latest version of Gant from here. Gant is currently at version 1.4.0. Unzip it to a folder. If you already have your GROOVY_HOME set, that's all you need to use Gant. Getting Started. Open a console, and type gant. You should see a message as shown below: meera-subbaraos-macbook-9:~ meerasubbarao$ gant Cannot open file build.gant meera-subbaraos-macbook-9:~ meerasubbarao$ You are all set at this point to use Gant in your projects. Help Information: Open a console, and type gant -h. This will provide you with all the necessary help information you need as shown below: meera-subbaraos-macbook-9:CodeMetricsProject meerasubbarao$ gant -h usage: gant [option]* [target]* -c,--usecache Whether to cache the generated class and perform modified checks on the file before re-compilation. -n,--dry-run Do not actually action any tasks. -C,--cachedir The directory where to cache generated classes to. -D = Define to have value . Creates a variable named for use in the scripts and a property named for the Ant tasks. -L,--lib Add a directory to search for jars and classes. -P,--classpath Specify a path to search for jars and classes. -T,--targets Print out a list of the possible targets. -V,--version Print the version number and exit. -d,--debug Print debug levels of information. -f,--file Use the named build file instead of the default, build.gant. -h,--help Print out this message. -l,--gantlib A directory that contains classes to be used as extra Gant modules, -p,--projecthelp Print out a list of the possible targets. -q,--quiet Do not print out much when executing. -s,--silent Print out nothing when executing. -v,--verbose Print lots of extra information. Create a new file called build.gant at the root of your project. Did a similarity between Ant and Gant strike you here? Ant build files are usually called build.xml, and they are created as a common practice within the root of your project folder as well. If you have written or even modified Ant build files, you will know that it contains one project element, which in turn contains a name,the default target and the base directory. Code Listing 4: So for example, sayHello target in Ant would look something like this: Lets create the sayHello target, and also see how to set it as the default target in Gant as well. A Gant target has a name and a description: Code Listing 5: target ( target-name : target-description ) { groovy code sequence } The above sayHello target in Gant would translate as shown below: target(sayHello:"Saying hello"){ Ant.echo(message:"Hello Javalobby") } Now, open a command window and type gant at the root of the project where the build.gant file exists. You should be able to see a output like: meera-subbaraos-macbook-9:CodeMetricsProject meerasubbarao$ gant Target default does not exist. Gant is complaining that we haven't set a Default target. Lets see how to do the same: Default target: Within Ant, you define the default target from within the project element as seen in Listing 4. The default target is the target called if no target is specified from the command line. There however is no project tag within Gant. There are two ways of specifying the default target as shown below: 1. You simply create a target whose name is default. target ( 'default' , 'The default target.' ) { aTarget ( ) 2. or even simply: setDefaultTarget ( aTarget ) In order to get our sayHello target working, we need to add one of the above scripts to our build.gant file. Code Listing 6: setDefaultTarget(sayHello) or target ("default": "The default target." ) { sayHello ( ) } Complete listing of build.gant: target(sayHello:"Saying hello"){ Ant.echo(message:"Hello Javalobby") } /* target ("default": "The default target." ) { sayHello ( ) } */ setDefaultTarget(sayHello) And you should be able to see: meera-subbaraos-macbook-9:CodeMetricsProject meerasubbarao$ gant [echo] Hello Javalobby meera-subbaraos-macbook-9:CodeMetricsProject meerasubbarao$ That was easy! If you have build files and it is becoming unmanageable by your team, there is a tool out there which can convert your Ant scripts to Gant scripts as well. I haven't used it, but you can try it here. In this part of the series, we learned when to move over from Ant to Gant, downloaded and installed Gant, and finally wrote a simple gant build file. In the next part of this series, we will see Gant in Action within a simple Java project. And as always, keep us posted here if you are encountering any problems getting started with Gant. Stay tuned.
September 23, 2008
by Meera Subbarao
· 52,172 Views
article thumbnail
Javadoc or Doxygen?
In the last two articles, "Reverse-engineer Source Code into UML Diagrams" and "Visual Documentation of Ant Dependencies in 3 Simple Steps" we saw how easy and valuable it was to automate technical documentation. By using open source tools, we were easily able to provide good technical documentation within a few minutes, and at no cost at all. We were also able to keep this up-to date by adding additional tasks to our Ant build files, and run them from our CI Server(Hudson in our case) on commit and nightly builds, and also publish the results. In this article, I will be showing you how to use yet another tool called Doxygen for generating technical documentation based on your source code. We all have used Javadoc and have been using it for a long time, right? So, you may ask what's the need to have another tool which produces the same HTML documentation? Doxygen has a slight edge over Javadoc and here are a few reasons why you should consider using the same: With Javadoc you have to remember all the HTML tags, you need to embed within your code comments. However, with Doxygen code comments are much more concise and polished, without the need for any HTML. Doxygen can also generate a variety of diagrams, we will take a look at some of them later. Doxygen also provides a structured view on the source code. As I mentioned in 2 above in the form of various diagrams, cross-referenced and syntax highlighted code. You get all the above benefits even if the code does not have any comments at all. Last but not the least, Doxygen is a documentation system not for just Java but also for various other languages like C++, C, Java, Objective-C, Python, IDL (Corba and Microsoft flavors), Fortran, VHDL, PHP, C#. So, without wasting further time, lets see what we need to get started with Doxygen. Step 1. Download, Install Doxygen. Download the binary distribution for Doxygen for the operating system you are using. I downloaded the binary distribution for Mac OS X called Doxygen-1.5.6.dmg. Installation is very simple, just drag the doxygen icon from this folder to the Applications folder, or wherever you want to keep it; as shown. I dropped it within my Applications folder. Just be sure to remember where you dragged it. To uninstall, just delete the file. It is completely self-contained. Step 2: Configure Doxygen. To generate documentation using Doxygen, you will need a configuration file called the Doxyfile. You can generate this file in two ways; either by using the Doxygen wizard or by using the command line option. Lets see how to use both these options to generate the configuration file: a. Command line. Open a command window and type the following as shown below: You should be able to locate the configuration file created within your default user folder. The file looks like this: # Doxyfile 1.5.6 # This file describes the settings to be used by the documentation system # doxygen (www.doxygen.org) for a project # # All text after a hash (#) is considered a comment and will be ignored # The format is: # TAG = value [value, ...] # For lists items can also be appended using: # TAG += value [value, ...] # Values that contain spaces should be placed between quotes (" ") #--------------------------------------------------------------------------- # Project related configuration options #--------------------------------------------------------------------------- # This tag specifies the encoding used for all characters in the config file # that follow. The default is UTF-8 which is also the encoding used for all # text before the first occurrence of this tag. Doxygen uses libiconv (or the # iconv built into libc) for the transcoding. See # http://www.gnu.org/software/libiconv for the list of possible encodings. DOXYFILE_ENCODING = UTF-8 # The PROJECT_NAME tag is a single word (or a sequence of words surrounded # by quotes) that should identify the project. PROJECT_NAME = # The PROJECT_NUMBER tag can be used to enter a project or revision number. # This could be handy for archiving the generated documentation or # if some version control system is used. PROJECT_NUMBER = b. Wizard Option. Launch the Doxygen application, and you should be able to create the configuration file using the wizard approach as shown below. The user interface is quite intuitive so I am going to skip explaining this in detail. The wizard approach was the one I used to get the initial settings for the configuration file. which you can always modify later. A few options in my Doxygen configuration file are as follows: # Doxyfile 1.5.6 #--------------------------------------------------------------------------- # Project related configuration options #--------------------------------------------------------------------------- DOXYFILE_ENCODING = UTF-8 PROJECT_NAME = PetStore PROJECT_NUMBER = 1.0 #--------------------------------------------------------------------------- # Build related configuration options #--------------------------------------------------------------------------- EXTRACT_ALL = NO EXTRACT_PRIVATE = NO EXTRACT_STATIC = NO EXTRACT_LOCAL_CLASSES = YES #--------------------------------------------------------------------------- # configuration options related to the HTML output #--------------------------------------------------------------------------- GENERATE_HTML = YES HTML_OUTPUT = html HTML_FILE_EXTENSION = .html GENERATE_TREEVIEW = YES Step 3. Doxygen and Ant. In order to use Doxygen, we need an Ant task. There is already an Ant task written for Doxygen which you can download from here. As always, since using Mac, when I downloaded the binaries and tried to use them, I got the ever famous error message : java.lang.UnsupportedClassVersionError: Bad version number in .class file So, had to do download the source, compile, and jar it up. Copy this library to your projects folder. Next, lets start making changes to our build file. 3.a: Lets define the Doxygen task. 3.b: To generate HTML documentation: 3.c: Lets combine them in target and run: [doxygen] Exec: /Applications/Doxygen.app reports/Doxyfile BUILD FAILED /CodeMetricsProject/build.xml:91: Doxygen not found on the PATH. Total time: 7 seconds 3.d: So, to launch Doxygen not in the path. we make change to the doxygen task as shown below: Lets run the target again and see if it fixed things.Yes indeed. generate-doxygen-docs: [doxygen] Exec: /Applications/Doxygen.app/Contents/Resources/doxygen reports/Doxyfile BUILD SUCCESSFUL Total time: 8 seconds 4. Integrate with Hudson. 4.a Modify Hudson Job. Once you have an Ant target working, calling this from your CI server is trivial. Within Hudson, select your Job, click on configure and add this new target to be called when running the build. 4.b Publish the reports. 4. c: Sample Reports. Force a build, and take a detailed look at the reports generated by Doxygen as shown below: I have given you a brief overview of Doxygen in this article, how to configure the same, and use it effectively to generate technical documentation on a continuous basis; either on commit builds or nightly builds. The Doxygen web site has lots of information on how to use it with other programming languages and also has tutorials in languages other than English as well. As always, if you are having trouble getting Doxygen to work, leave a comment or check out the Doxygen web site.
September 10, 2008
by Meera Subbarao
· 49,713 Views · 1 Like
article thumbnail
Reverse-Engineer Source Code into UML Diagrams
This article shows how easy and simple it is to include UML diagrams within your Javadoc and also keep them updated with every change in the source code repository.
August 22, 2008
by Meera Subbarao
· 220,891 Views · 1 Like
article thumbnail
Ant Build File Changes for Java Web Projects in NetBeans IDE 6.1
While working with a Java Web Application in NetBeans, I noticed some slight changes in the Ant build file for my project between NetBeans 6.0 and 6.1. This article explores some of the problems these changes caused to help out anyone with similar issues. I started with a Java Web Application that was created in NetBeans 6.0.1. After adding some JSP files and several Java source files, I committed everything in the project to my CVS repository. For some of my projects, I utilize the Hudson continuous integration build server. Using a standard deployment of Hudson, I configured the project to poll the SCM every 60 minutes, check out the code from CVS (if changes had been committed), and trigger the NetBeans project’s Ant build file (calling several specific targets like compile, dist, and so on. My builds have been functioning correctly for several weeks using this standard setup. I recently opened one of those projects in NetBeans 6.1 Beta and have been thoroughly enjoying the new features (faster startup, better JSP parsing in the Source Editor). After adding some JAR files as libraries and making several configuration changes, I committed the entire project (particularly the build-related files in the nbproject directory). Suddenly, my build for that project started failing. The console output reported by Hudson was : -init-check: BUILD FAILED D:/projects/hudson-server/data/jobs/MyWebProjectl/workspace/nbproject/build-impl.xml:149: The Java EE server classpath is not correctly set up. Your active server type is Tomcat55. Either open the project in the IDE and assign the server or setup the server classpath manually. For example like this: ant -Duser.properties.file= (where you put the property “j2ee.platform.classpath” in a .properties file) or ant -Dj2ee.platform.classpath= (where no properties file is used) Total time: 2 seconds finished: FAILURE I undid the configuration changes one by one, but the build failed regardless of what I reset. Apparently the property j2ee.platform.classpath is now required. I did a DIFF on the nbproject/build-impl.xml file and discovered several changes. The -init-check target includes property checks including this new one : The Java EE server classpath is not correctly set up. Your active server type is ${j2ee.server.type}.Either open the project in the IDE and assign the server or setup the server classpath manually.For example like this: ant -Duser.properties.file= (where you put the property “j2ee.platform.classpath” in a .properties file) or ant -Dj2ee.platform.classpath= (where no properties file is used) I hadn’t really taken notice of this property in the build file before, but it is referenced in a number of other targets such as: -init-macrodef-javac, -init-macrodef-junit, -init-macrodef-java, -init-macrodef-nbjpda, -init-macrodef-debug, compile-jsps, -do-compile-single-jsp, connect-debugger, javadoc-build, -do-compile-test, -do-compile-test-single Not being able to find a definition of the property anywhere in the build file, I looked through the project’s project.properties file among the list of defined properties. The property j2ee.platform.classpath was not defined. Thus, I’m assuming this is passed into the build file dynamically by NetBeans? In general I wouldn’t care, but when running the build file via Ant inside Hudson, the property j2ee.platform.classpath is never passed in. Hudson DOES allow you to pass properties and values to the build file, so I suppose I can specify the value manually, but I would like to keep the number of per project customizations to a minimum to maintain a low level of maintenance. Unless this causes some problem with the project properties in the build system, I would suggest the following fix for anyone who is experiencing a similar issue. Open your project’s project.properties file. Navigate to the section that contains these properties: j2ee.platform=1.4 j2ee.server.type=Tomcat55 Add a new line that specifies a blank j2ee.platform.classpath property such as this: j2ee.platform=1.4 j2ee.platform.classpath= j2ee.server.type=Tomcat55 Now, if the project.properties file is committed to CVS, a Hudson build can be triggered, and the FAIL check in the build-impl.xml file will pass. I ran some quick tests with the project, and everything with the project inside NetBeans still seems to work fine. I would propose to the NetBeans team to have the j2ee.platform.classpath property automatically added to the project.properties file.
March 26, 2008
by Adam Myatt
· 15,531 Views
article thumbnail
DJ NativeSwing - reloaded: JWebBrowser, JFlashPlayer, JVLCPlayer, JHTMLEditor.
Today's release of DJ Native Swing 0.9.4 greatly improves stability and brings new components: in addition to the JWebBrowser and JFlashPlayer, there is now the JVLCPlayer and the JHTMLEditor. Here is a summary of what to expect when using this library. 1. Various native components DJ Native Swing was designed to handle all the complexity of native integration, mainly in the form of components with a simple Swing-like API. Here are some screenshots of several components in action (click to enlarge): JWebBrowser: JFlashPlayer: JVLCPlayer: JHTMLEditor: 2. Simple API First, we need to initialize the framework. This needs to happen before any feature is used. A common place for this call is the first line of the main(): public static void main(String[] args) { NativeInterfaceHandler.init(); // Here goes the rest of the initialization. } Now, let's see how to create a JWebBrowser, with its URL set to Google's homepage: JWebBrowser webBrowser = new JWebBrowser(); webBrowser.setURL("http://www.google.com"); myContentPane.add(webBrowser); Note that we set a URL, but we could as well set the HTML text. The JWebBrowser also allows to execute Javascript calls, and we can even propagate notifications from custom pages to our Swing application. Moving to a more practical example, we may want to be notified of URL change events or track window opening events, potentially preventing navigation to occur or open the page elsewhere. This is easily achieved by attaching a listener: webBrowser.addWebBrowserListener(new WebBrowserAdapter() { public void urlChanging(WebBrowserNavigationEvent e) { String newURL = e.getNewURL(); if(newURL.startsWith("http://www.microsoft.com/")) { // Prevent the navigation to happen. e.consume(); } else { // We can consume the event and decide to open this page in a tab. } } public void windowWillOpen(WebBrowserWindowWillOpenEvent e) { // We can prevent, add the URL to a tab, etc. } // There are of course more events that can be received. }); Let's have a look at the JFlashPlayer: JFlashPlayer flashPlayer = new JFlashPlayer(); flashPlayer.setURL(myFlashURL); The JFlashPlayer can open local or remote Flash files, and files from the classpath; the latter being a general capability of the library by proxying files using a minimalistic web server. Of course, the JFlashPlayer allows to retrieve and set Flash variables, and play/pause/stop the execution. The JVLCPlayer and the JHTMLEditor are no exceptions to this simplicity: playlist can be manipulated in the VLC player, HTML can be set and retrieved from the HTML editor, etc. There is also the possibility to integrate Ole controls on Windows, still with a simple Swing-like API. An example is provided in the library in the form of an embedded Windows Media Player. 3. Advanced capabilities The library takes care of most common integration issues. This covers modal dialog handling, Z-ordering, heavyweight/lightweight mix (to a certain extent), invisible native components with regards to focus handling and threading. Here are some more screenshots, showing a lightweight/heavyweight mix, and Z-ordering capability: The demo application that is part of the distribution shows all the features along with the source code, so check it out! 4. Project info and technical notes Webstart demo: http://djproject.sourceforge.net/ns/DJNativeSwingDemo.jnlp Screenshots: http://djproject.sourceforge.net/ns/screenshots Native Swing: http://djproject.sourceforge.net/ns The DJ Project: http://djproject.sourceforge.net The 0.9.4 version has a completely new architecture. It still uses SWT under the hood, but it does not use the SWT_AWT bridge anymore. The JWebBrowser and browser-based components require XULRunner to be installed, except on Windows when using Internet Explorer. The JVLCPlayer requires VLC to be installed. The JHTMLEditor uses the FCKeditor. 5. Conclusions This project finally brings all that is needed to make Java on the desktop a reality. A web browser, a flash player, a multimedia player, and even an HTML editor. So, what next? Yes, what next? For that one, I am waiting for your feedback. So, what do you think? What are your comments and suggestions? -Christopher
March 12, 2008
by Christopher Deckers
· 54,503 Views
article thumbnail
SVNKit: Tame Subversion with Java!
SVNKitis an Open Source pure Java Subversion library. SVNKit literally brings Subversion, popular open source version control system, to the Java world. With SVNKit you can do the following: All standard Subversion operations: For instance, the following snipped checks out project from repository: File dstPath = new File("c:/svnkit"); SVNURL url = SVNURL. parseURIEncoded("http://svn.svnkit.com/repos/svnkit/branches/1.1.x/"); SVNClientManager cm = SVNClientManager.newInstance(); SVNUpdateClient uc = cm.getUpdateClient(); uc.doCheckout(url, dstPath, SVNRevision.UNDEFINED, SVNRevision.HEAD, true); Updates it to the latest revision: uc.doUpdate(dstPath, SVNRevision.HEAD, true); And finally commits local changes in "www" subdirectory if there are any: SVNCommitClient cc = cm.getCommitClient(); cc.doCommit(new File[] {new File(dstPath, "www")}, false, "message", false, true); SVNKit supports all standard Subversion operations and compatible with the latest version of Subversion. Access Subversion repository directly: Some applications will benefit from working with repository directly, without keeping working copy locally. Example below displays list of files in "www" directory. SVNURL url = SVNURL.parseURIEncoded("http://svn.svnkit.com/repos/svnkit/branches/1.1.x/"); SVNRepository repos = SVNRepositoryFactory.create(url); long headRevision = repos.getLatestRevision(); Collection entriesList = repos.getDir("www", headRevision, null, (Collection) null); for (Iterator entries = entriesList.iterator(); entries.hasNext();) { SVNDirEntry entry = (SVNDirEntry) entries.next(); System.out.println("entry: " + entry.getName()); System.out.println("last modified at revision: " + entry.getDate() + " by " + entry.getAuthor()); } Direct repository access API allows to perform operations like update, commit, diff and many other. Additionaly to the performance benefits of the direct access to repository, this API makes it possible to version arbitrary objects or object models within Subevrsion repository, not only files from the file system. Replace JNI Subversion bindings with SVNKit: Native Subversion provides Java interface that works with Subversion binaries through JNI. In case you already using it or would like to use as an option, you may also use SVNKit through exactly the same interface. This way you'll let your application dynamically switch between JNI and SVNKit implementation of the same API or let your application work on the platforms where there are no native Subversion binaries. For example: // pure Java implementation of the standard Subversion Java interface SVNClientInterface jniAPI = SVNClientImpl.newInstance(); byte[] contents = jniAPI.fileContent("http://svn.svnkit.com/repos/svnkit/branches/1.1.x/changelog.txt", Revision.HEAD); SVNKit is widely used in different applications, including IntelliJ IDEA, Eclipse Subversion integrations, SmartSVN, JDeveloper, bug tracking server side applications (e.g. Atlassian JIRA) and repository management and tracking tools (e.g. Atlassian FishEye) and many others. Where to get more information: Recently we've released SVNKit version 1.1.6 which is bugfix release. At http://svnkit.com/ you will find more information on that new version and, of course, downloads, documentation, source code example and articles explaining how to use SVNKit. In case of any questions you're welcome at our mailing list, or just contact us at [email protected] SVNKit is widely used in different applications, including IntelliJ IDEA, Eclipse Subversion integrations, SmartSVN, JDeveloper, bug tracking server side applications (e.g. Atlassian JIRA) and repository management and tracking tools (e.g. Atlassian FishEye) and many others. With best regards, TMate Software, http://svnkit.com/ - Java [Sub]Versioning Library!
February 26, 2008
by Alexander Kitaev
· 11,284 Views · 2 Likes
article thumbnail
Patching from Local History
Using patches is a popular way to share changes between the teammates or supply updates to software products to the customers. With IntelliJ IDEA, creating and applying versioned patches is quite simple and intuitive: you can do it from the main Version Control menu, or from the Changes tool window. However, IntelliJ IDEA suggests an additional way to create and apply your “personal” patches. As we have discussed earlier, numerous changes pass unnoticed by the version control systems, because you just do not check in every change you make to your files while working. You know that IntelliJ IDEA keeps your own “personal version control” – the local history. Besides the possibility to roll back to a certain revision, you can also create a patch on the base of a revision or action, share it with your colleagues, and apply it when necessary. Local history applies to the folders, files, members and fragments of text, but the technique of creating a patch is common in all cases. Let’s see how it’s done. Select a folder in the Project tool window, and choose Local History on its context menu. In the Local History view, right-click the desired revision, and choose Create Patch: [img_assist|nid=1204|title=|desc=|link=none|align=left|width=505|height=357] In the dialog box that opens, specify the name and location of the patch file: [img_assist|nid=1205|title=|desc=|link=none|align=left|width=415|height=136] An interesting possibility is suggested by the Reverse patch checkbox. If you check this option, IntelliJ IDEA will create a patch that rolls back the selected action. For example, it you have created a file, the patch will delete it. Applying your “personal” patch is done as usual, using the Apply Patch command on the main Version Control menu. If a patch file is stored in project, you can invoke this command on the context menu of the patch file in the Project tool window: [img_assist|nid=1206|title=|desc=|link=none|align=left|width=249|height=195]
February 21, 2008
by Irina Megorskaya
· 9,796 Views
  • Previous
  • ...
  • 390
  • 391
  • 392
  • 393
  • 394
  • RSS
  • X
  • Facebook

ABOUT US

  • About DZone
  • Support and feedback
  • Community research

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • Become a Contributor
  • Core Program
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 3343 Perimeter Hill Drive
  • Suite 215
  • Nashville, TN 37211
  • [email protected]

Let's be friends:

  • RSS
  • X
  • Facebook
×