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  • Tab Sweep - State of Java EE, Dynamic JPA, Java EE performance, Garbage Collection, ...

    - by alexismp
    Recent Tips and News on Java EE 6 & GlassFish: • Java EE: The state of the environment (SDTimes) • Extend your Persistence Unit on the fly (EclipseLink blog) • Glassfish 3.1 - AccessLog Format (Ralph) • Java Enterprise Performance - Unburdended Applications (Lucas) • Java Garbage Collection and Heap Analysis (John) • Qu’attendez-vous de JMS 2.0? (Julien) • Dynamically registering WebFilter with Java EE 6 (Markus)

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  • JPRT: A Build & Test System

    - by kto
    DRAFT A while back I did a little blogging on a system called JPRT, the hardware used and a summary on my java.net weblog. This is an update on the JPRT system. JPRT ("JDK Putback Reliablity Testing", but ignore what the letters stand for, I change what they mean every day, just to annoy people :\^) is a build and test system for the JDK, or any source base that has been configured for JPRT. As I mentioned in the above blog, JPRT is a major modification to a system called PRT that the HotSpot VM development team has been using for many years, very successfully I might add. Keeping the source base always buildable and reliable is the first step in the 12 steps of dealing with your product quality... or was the 12 steps from Alcoholics Anonymous... oh well, anyway, it's the first of many steps. ;\^) Internally when we make changes to any part of the JDK, there are certain procedures we are required to perform prior to any putback or commit of the changes. The procedures often vary from team to team, depending on many factors, such as whether native code is changed, or if the change could impact other areas of the JDK. But a common requirement is a verification that the source base with the changes (and merged with the very latest source base) will build on many of not all 8 platforms, and a full 'from scratch' build, not an incremental build, which can hide full build problems. The testing needed varies, depending on what has been changed. Anyone that was worked on a project where multiple engineers or groups are submitting changes to a shared source base knows how disruptive a 'bad commit' can be on everyone. How many times have you heard: "So And So made a bunch of changes and now I can't build!". But multiply the number of platforms by 8, and make all the platforms old and antiquated OS versions with bizarre system setup requirements and you have a pretty complicated situation (see http://download.java.net/jdk6/docs/build/README-builds.html). We don't tolerate bad commits, but our enforcement is somewhat lacking, usually it's an 'after the fact' correction. Luckily the Source Code Management system we use (another antique called TeamWare) allows for a tree of repositories and 'bad commits' are usually isolated to a small team. Punishment to date has been pretty drastic, the Queen of Hearts in 'Alice in Wonderland' said 'Off With Their Heads', well trust me, you don't want to be the engineer doing a 'bad commit' to the JDK. With JPRT, hopefully this will become a thing of the past, not that we have had many 'bad commits' to the master source base, in general the teams doing the integrations know how important their jobs are and they rarely make 'bad commits'. So for these JDK integrators, maybe what JPRT does is keep them from chewing their finger nails at night. ;\^) Over the years each of the teams have accumulated sets of machines they use for building, or they use some of the shared machines available to all of us. But the hunt for build machines is just part of the job, or has been. And although the issues with consistency of the build machines hasn't been a horrible problem, often you never know if the Solaris build machine you are using has all the right patches, or if the Linux machine has the right service pack, or if the Windows machine has it's latest updates. Hopefully the JPRT system can solve this problem. When we ship the binary JDK bits, it is SO very important that the build machines are correct, and we know how difficult it is to get them setup. Sure, if you need to debug a JDK problem that only shows up on Windows XP or Solaris 9, you'll still need to hunt down a machine, but not as a regular everyday occurance. I'm a big fan of a regular nightly build and test system, constantly verifying that a source base builds and tests out. There are many examples of automated build/tests, some that trigger on any change to the source base, some that just run every night. Some provide a protection gateway to the 'golden' source base which only gets changes that the nightly process has verified are good. The JPRT (and PRT) system is meant to guard the source base before anything is sent to it, guarding all source bases from the evil developer, well maybe 'evil' isn't the right word, I haven't met many 'evil' developers, more like 'error prone' developers. ;\^) Humm, come to think about it, I may be one from time to time. :\^{ But the point is that by spreading the build up over a set of machines, and getting the turnaround down to under an hour, it becomes realistic to completely build on all platforms and test it, on every putback. We have the technology, we can build and rebuild and rebuild, and it will be better than it was before, ha ha... Anybody remember the Six Million Dollar Man? Man, I gotta get out more often.. Anyway, now the nightly build and test can become a 'fetch the latest JPRT build bits' and start extensive testing (the testing not done by JPRT, or the platforms not tested by JPRT). Is it Open Source? No, not yet. Would you like to be? Let me know. Or is it more important that you have the ability to use such a system for JDK changes? So enough blabbering on about this JPRT system, tell me what you think. And let me know if you want to hear more about it or not. Stay tuned for the next episode, same Bloody Bat time, same Bloody Bat channel. ;\^) -kto

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  • Send SMS text messages for FREE using Java ME

    - by hinkmond
    Here's a way to get around those nasty SMS text messages charges (and maybe a way to get around the Pakistan SMS text censors too!). Use this Java ME SMS text app for your Java ME mobile phone, called JaxtrSMS: See: JaxtrSMS free Java ME SMS Here's a quote: JaxtrSMS lets you send FREE SMS and txt messages to any mobile phone in the world. Best of all, the receiver does not have to have the JaxtrSMS app. International and local SMS/texting can be expensive but with JaxtrSMS you can text anyone in the world for FREE! Great! Now, you can send 2,000 text messages from your phone every month and not worry about a huge bill. You don't send 2,000 text message in a month? Well, get it for your teenage kids then. They certainly send 2,000 text messages in a month... Hinkmond

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  • Java ME SDK 3.0.5 Integrated with NetBeans 7.1.1

    - by SungmoonCho
    NetBeans 7.1.1 now integrates Java ME SDK 3.0.5, so you do not have to download them separately. Java ME SDK was packaged in NetBeans Mobility Pack, a mobile application development toolkit for NetBeans. Therefore, Java ME SDK is no longer a separate menu on NetBeans. For those who have not downloaded Java ME SDK yet, please simply visit NetBeans website and download the latest version. For those who already have Java ME SDK integrated with NetBeans 7.1 or earlier, and want to update NetBeans IDE to 7.1.1, don't worry. They can co-exist. To use NetBeans plug-ins such as Device Selector, profiler, and Internationalization Resource Manager, you have to install "Java ME SDK Tools" from NetBeans. Here is how. 1.  Go to "Tools - Plug-ins" from NetBeans menu. You can find all the plug-ins you can install into NetBeans. Locate "Java ME SDK Tools" from the list. 2. Follow the instruction to install Java ME SDK Plug-ins. 3. Once completed, you will see new menu options. For example, you can find Device Selector under Tools - Java ME. (If you used old version of Java ME, you will notice that there is not 'Java ME' menu any more. This is because all the sub-menus were integrated into appropriate places in NetBeans.) There is one thing to keep in mind; Since NetBeans 7.1.1 already includes Java ME SDK 3.0.5 and Java ME SDK 3.0.5 plug-ins must be installed through NetBeans plug-in menu, you should not download Java ME SDK 3.0.5 separately and try to integrate it with NetBeans. This may cause issues.

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  • java MainServer gives java.lang.UnsupportedClassVersionError: Unsupported major.minor version 51.0

    - by Paradox
    Compiling is easy but when using java to run the programs, it gives Exception found. I am using Ubuntu 12.04 without internet connections. Also, installed Oracle JDK7 and JRE7. Also did the update-alternatives command on java, javac and javaws. Changed the machine java in /etc/profiles. PATH is pointing to oracle java folder. I did many searches on Google about this topic but each time jdk and jre version are different. Also check version of jdk and jre using java -version and javac - version. Both of them are the same. The system also contains OpenJdk6 and OpenJdk7. So, how do I remove these errors?

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  • Conditionally Auto-Executing af:query Search Form Based on User Input

    - by steve.muench
    Due to extreme lack of time due to other work priorities -- working hard on some interesting new ADF features for a future major release -- 2010 has not been a banner year for my production of samples to post to my blog, but to show my heart is in the right place I wanted to close out the year by posting example# 160: 160. Conditionally Auto-Executing af:query Search Form Based on User Input Enjoy. Happy New Year.

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  • Stuff I learned at Innovate 2011

    - by David Dorf
    After returning from the NRF Innovate 2011 conference, I picked up few nuggets I thought I'd share here.  These thoughts are a bit random, but I hope they're useful nonetheless.Kevin Kelly opened the conference with six verbs that represent the future.  They were Screening, Interacting, Sharing, Accessing, Flowing, and Generating.  It struck me that these are all ways in which we merge the digital and physical worlds.  The internet of things continues to gain momentum.Some buzzwords:  deal economy, subscription commerce, discovery (instead of search), curationThat last one, curation, came up over and over.  Retailers, especially those in fashion, are finding value in helping their customers organize and present their own collections.  Social media has made sharing such collections easy, and mobile lets them take those ideas into the stores.  Mannequins are becoming less relevant.I heard from both HauteLook and Gilt Groupe (flash sale retailers) that a large percentage of their visits come from mobile devices, and most of those are iOS devices.  I find it interesting that even though Android has passed iPhone in units shipped (and will eventually pass iOS as a whole), its still the Apple crowd that leads the way.RadioShack mentioned their Holiday Heroes campaigned was very successful.  They asked their Foursquare users to check-in at a gym, coffee shop, and transportation hub as part of being a hero.  For this feat, customers were awarded a special badge that was worth 20% off at their next store visit. They claim a 3.5x increase in ticket size vs. regular check-in customers, and a 5x increase vs those that don't check-in at all.I also learned of RadioShack's #28 campaign, which is apparently one of the largest Twitter trends ever.  Their partnership with LIVESTRONG has gotten them followers, impressions, and credit for supporting the fight against cancer.The guys at Invodo showed the importance of video to e-commerce.  They gave compelling examples of how video can show customers the value of products better than just words.The highlight of the show was Guy Kawasaki's talk on innovation, which was not only informative but also peppered with humor and personality.  Back in the early days of the internet boom, Guy turned down the CEO position at Yahoo! because the commute was too long.  By his calculation, that was a $2B mistake.There are other good accounts of the conference at the NRF Blog.

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  • YouTube: How to Style an AngularJS App on the Device

    - by Geertjan
    I installed the Droid@Screen plugin into NetBeans IDE 8 so that you can see the Android device that I held in my hand while doing the demo below. The demo shows the usage of the Terminal window to create an Ionic Framework application (from "tabs", which is one of the cool templates that the framework provides), i.e., that means I can use AngularJS to create a Cordova application out of the box, with many mobile-oriented components available out of the box. Then I deploy the app to the Chrome browser on Android, which means I can interact with it in NetBeans, e.g., for CSS styling and JavaScript debugging. In this demo, I show how the background color of the deployed app can be changed live from NetBeans. After that, once I'm happy with the styling, I deploy the app again, but this time as a Cordova app, i.e., a hybrid HTML5 application, which means the app is packaged as a native app and deployed directly to the device from NetBeans. All of the above can be viewed here in about 4 minutes in this silent movie: Direct link to the (silent) movie: https://www.youtube.com/watch?v=isP5TNI3kYk

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  • YouTube Scalability Lessons

    - by Bertrand Matthelié
    @font-face { font-family: "Arial"; }@font-face { font-family: "Courier New"; }@font-face { font-family: "Wingdings"; }@font-face { font-family: "Calibri"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }h2 { margin: 12pt 0cm 3pt; page-break-after: avoid; font-size: 14pt; font-family: "Times New Roman"; font-style: italic; }a:link, span.MsoHyperlink { color: blue; text-decoration: underline; }a:visited, span.MsoHyperlinkFollowed { color: purple; text-decoration: underline; }span.Heading2Char { font-family: Calibri; font-weight: bold; font-style: italic; }div.Section1 { page: Section1; }ol { margin-bottom: 0cm; }ul { margin-bottom: 0cm; } Very interesting blog post by Todd Hoff at highscalability.com presenting “7 Years of YouTube Scalability Lessons in 30 min” based on a presentation from Mike Solomon, one of the original engineers at YouTube: …. The key takeaway away of the talk for me was doing a lot with really simple tools. While many teams are moving on to more complex ecosystems, YouTube really does keep it simple. They program primarily in Python, use MySQL as their database, they’ve stuck with Apache, and even new features for such a massive site start as a very simple Python program. That doesn’t mean YouTube doesn’t do cool stuff, they do, but what makes everything work together is more a philosophy or a way of doing things than technological hocus pocus. What made YouTube into one of the world’s largest websites? Read on and see... Stats @font-face { font-family: "Arial"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; } 4 billion Views a day 60 hours of video is uploaded every minute 350+ million devices are YouTube enabled Revenue double in 2010 The number of videos has gone up 9 orders of magnitude and the number of developers has only gone up two orders of magnitude. 1 million lines of Python code Stack @font-face { font-family: "Arial"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; } Python - most of the lines of code for YouTube are still in Python. Everytime you watch a YouTube video you are executing a bunch of Python code. Apache - when you think you need to get rid of it, you don’t. Apache is a real rockstar technology at YouTube because they keep it simple. Every request goes through Apache. Linux - the benefit of Linux is there’s always a way to get in and see how your system is behaving. No matter how bad your app is behaving, you can take a look at it with Linux tools like strace and tcpdump. MySQL - is used a lot. When you watch a video you are getting data from MySQL. Sometime it’s used a relational database or a blob store. It’s about tuning and making choices about how you organize your data. Vitess- a  new project released by YouTube, written in Go, it’s a frontend to MySQL. It does a lot of optimization on the fly, it rewrites queries and acts as a proxy. Currently it serves every YouTube database request. It’s RPC based. Zookeeper - a distributed lock server. It’s used for configuration. Really interesting piece of technology. Hard to use correctly so read the manual Wiseguy - a CGI servlet container. Spitfire - a templating system. It has an abstract syntax tree that let’s them do transformations to make things go faster. Serialization formats - no matter which one you use, they are all expensive. Measure. Don’t use pickle. Not a good choice. Found protocol buffers slow. They wrote their own BSON implementation, which is 10-15 time faster than the one you can download. ...Contiues. Read the blog Watch the video

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  • Change Logging Level for SOA 11g

    - by James Taylor
    I’m sure there are many blogs out there that have this solution. But I seem to get asked this question a lot so I thought I would post it here for my convenience. Login to Enterprise Manager, e.g. http://localhost:7001/em Expand the SOA folder and right-click the soa-infra(soa_server1) folder and select Logs – Log Configuration Navigate to the component you want to monitor and change the log level. It is possible to change at a parent level if required It is not recommended that you set the level to FINIEST at a parent level as it will generate a lot of logging. Make sure you apply the change to take affect. Simple as that.

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  • Is there such a thing as "closure" with software work?

    - by Bobby Tables
    I burned out last year (after a decade of fulltime programming jobs) and am on a sabbatical now. With all the self-examination I've started to figure out some of the root causes of my burnout, and one of the major ones is basically this: there was never any real closure in any of the work I've ever done. It was always a case of getting into an open-ended support/maintenance grind and going stale. When I first entered the industry, I had this image of programming work being very project-based. And I expected projects to have a start, beginning, and END. And then you move on and start on something totally new and fresh. Basically I never expected that a lot (most) of software work involves supporting and maintaining the same code base for open-ended long periods of time - years and even decades. That, combined with generally having itchy feet makes me think that burnout is inevitable for me, after 2-3 years, in ANY fulltime software job. All this sounds like I probably should have been a contractor instead of a fulltimer. But when I discuss this with people, a lot of them say that even THEN you can't really escape having to go back and maintain/support the stuff you worked on, over and over (eg. Coming back on support contracts, for example). The nature of software work is simply like that. There is no project closure, unlike in many other engineering fields. So my question is - Is there ANY programming work out there which is based on short to mid term projects/stints and then moving on cleanly? And is there any particular industry domain or specialization where this kind of project work is typical?

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  • C-states and P-states : confounding factors for benchmarking

    - by Dave
    I was recently looking into a performance issue in the java.util.concurrent (JUC) fork-join pool framework related to particularly long latencies when trying to wake (unpark) threads in the pool. Eventually I tracked the issue down to the power & scaling governor and idle-state policies on x86. Briefly, P-states refer to the set of clock rates (speeds) at which a processor can run. C-states reflect the possible idle states. The deeper the C-state (higher numerical values) the less power the processor will draw, but the longer it takes the processor to respond and exit that sleep state on the next idle to non-idle transition. In some cases the latency can be worse than 100 microseconds. C0 is normal execution state, and P0 is "full speed" with higher Pn values reflecting reduced clock rates. C-states are P-states are orthogonal, although P-states only have meaning at C0. You could also think of the states as occupying a spectrum as follows : P0, P1, P2, Pn, C1, C2, ... Cn, where all the P-states are at C0. Our fork-join framework was calling unpark() to wake a thread from the pool, and that thread was being dispatched onto a processor at deep C-state, so we were observing rather impressive latencies between the time of the unpark and the time the thread actually resumed and was able to accept work. (I originally thought we were seeing situations where the wakee was preempting the waker, but that wasn't the case. I'll save that topic for a future blog entry). It's also worth pointing out that higher P-state values draw less power and there's usually some latency in ramping up the clock (P-states) in response to offered load. The issue of C-states and P-states isn't new and has been described at length elsewhere, but it may be new to Java programmers, adding a new confounding factor to benchmarking methodologies and procedures. To get stable results I'd recommend running at C0 and P0, particularly for server-side applications. As appropriate, disabling "turbo" mode may also be prudent. But it also makes sense to run with the system defaults to understand if your application exhibits any performance sensitivity to power management policies. The operating system power management sub-system typically control the P-state and C-states based on current and recent load. The scaling governor manages P-states. Operating systems often use adaptive policies that try to avoid deep C-states for some period if recent deep idle episodes proved to be very short and futile. This helps make the system more responsive under bursty or otherwise irregular load. But it also means the system is stateful and exhibits a memory effect, which can further complicate benchmarking. Forcing C0 + P0 should avoid this issue.

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  • JavaFX Developer Preview for ARM

    - by sasa
    ARM?Linux??JavaFX (JDK 7) Developer Preview?????????????????????JavaFX??????????????????????? ????????????BeagleBoard xM (Rev. C)?????????????????????????3M M2256PW?Chalkboard Electronics?1024x600 LCD????????????????????????????????????????????????? X?????X11???????????EGL???OpenGL ES 2.0??????????????????????????????Linux??????????????????????????Angstrom 2011.03????????????????????????????????????????Stopwatch(????????)?BouncingBalls(????????)?Calculator(???)?BrickBreaker(??????)?????????????? JavaOne?????????????????Raspberry Pi?Panda Board????????????? CON6094 - JavaFX on Smart Embedded Devices CON5348 - Do You Like Coffee with Your Dessert? Java and the Raspberry Pi CON4538 - Java Embedded Goes Modular: How to Build Your Custom Embedded Java Runtime

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  • CPU Usage in Very Large Coherence Clusters

    - by jpurdy
    When sizing Coherence installations, one of the complicating factors is that these installations (by their very nature) tend to be application-specific, with some being large, memory-intensive caches, with others acting as I/O-intensive transaction-processing platforms, and still others performing CPU-intensive calculations across the data grid. Regardless of the primary resource requirements, Coherence sizing calculations are inherently empirical, in that there are so many permutations that a simple spreadsheet approach to sizing is rarely optimal (though it can provide a good starting estimate). So we typically recommend measuring actual resource usage (primarily CPU cycles, network bandwidth and memory) at a given load, and then extrapolating from those measurements. Of course there may be multiple types of load, and these may have varying degrees of correlation -- for example, an increased request rate may drive up the number of objects "pinned" in memory at any point, but the increase may be less than linear if those objects are naturally shared by concurrent requests. But for most reasonably-designed applications, a linear resource model will be reasonably accurate for most levels of scale. However, at extreme scale, sizing becomes a bit more complicated as certain cluster management operations -- while very infrequent -- become increasingly critical. This is because certain operations do not naturally tend to scale out. In a small cluster, sizing is primarily driven by the request rate, required cache size, or other application-driven metrics. In larger clusters (e.g. those with hundreds of cluster members), certain infrastructure tasks become intensive, in particular those related to members joining and leaving the cluster, such as introducing new cluster members to the rest of the cluster, or publishing the location of partitions during rebalancing. These tasks have a strong tendency to require all updates to be routed via a single member for the sake of cluster stability and data integrity. Fortunately that member is dynamically assigned in Coherence, so it is not a single point of failure, but it may still become a single point of bottleneck (until the cluster finishes its reconfiguration, at which point this member will have a similar load to the rest of the members). The most common cause of scaling issues in large clusters is disabling multicast (by configuring well-known addresses, aka WKA). This obviously impacts network usage, but it also has a large impact on CPU usage, primarily since the senior member must directly communicate certain messages with every other cluster member, and this communication requires significant CPU time. In particular, the need to notify the rest of the cluster about membership changes and corresponding partition reassignments adds stress to the senior member. Given that portions of the network stack may tend to be single-threaded (both in Coherence and the underlying OS), this may be even more problematic on servers with poor single-threaded performance. As a result of this, some extremely large clusters may be configured with a smaller number of partitions than ideal. This results in the size of each partition being increased. When a cache server fails, the other servers will use their fractional backups to recover the state of that server (and take over responsibility for their backed-up portion of that state). The finest granularity of this recovery is a single partition, and the single service thread can not accept new requests during this recovery. Ordinarily, recovery is practically instantaneous (it is roughly equivalent to the time required to iterate over a set of backup backing map entries and move them to the primary backing map in the same JVM). But certain factors can increase this duration drastically (to several seconds): large partitions, sufficiently slow single-threaded CPU performance, many or expensive indexes to rebuild, etc. The solution of course is to mitigate each of those factors but in many cases this may be challenging. Larger clusters also lead to the temptation to place more load on the available hardware resources, spreading CPU resources thin. As an example, while we've long been aware of how garbage collection can cause significant pauses, it usually isn't viewed as a major consumer of CPU (in terms of overall system throughput). Typically, the use of a concurrent collector allows greater responsiveness by minimizing pause times, at the cost of reducing system throughput. However, at a recent engagement, we were forced to turn off the concurrent collector and use a traditional parallel "stop the world" collector to reduce CPU usage to an acceptable level. In summary, there are some less obvious factors that may result in excessive CPU consumption in a larger cluster, so it is even more critical to test at full scale, even though allocating sufficient hardware may often be much more difficult for these large clusters.

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  • Jersey 2 in GlassFish 4 - First Java EE 7 Implementation Now Integrated (TOTD #182)

    - by arungupta
    The JAX-RS 2.0 specification released their Early Draft 3 recently. One of my earlier blogs explained as the features were first introduced in the very first draft of the JAX-RS 2.0 specification. Last week was another milestone when the first Java EE 7 specification implementation was added to GlassFish 4 builds. Jakub blogged about Jersey 2 integration in GlassFish 4 builds. Most of the basic functionality is working but EJB, CDI, and Validation are still a TBD. Here is a simple Tip Of The Day (TOTD) sample to get you started with using that functionality. Create a Java EE 6-style Maven project mvn archetype:generate -DarchetypeGroupId=org.codehaus.mojo.archetypes -DarchetypeArtifactId=webapp-javaee6 -DgroupId=example -DartifactId=jersey2-helloworld -DarchetypeVersion=1.5 -DinteractiveMode=false Note, this is still a Java EE 6 archetype, at least for now. Open the project in NetBeans IDE as it makes it much easier to edit/add the files. Add the following <respositories> <repositories> <repository> <id>snapshot-repository.java.net</id> <name>Java.net Snapshot Repository for Maven</name> <url>https://maven.java.net/content/repositories/snapshots/</url> <layout>default</layout> </repository></repositories> Add the following <dependency>s <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <version>4.10</version> <scope>test</scope></dependency><dependency> <groupId>javax.ws.rs</groupId> <artifactId>javax.ws.rs-api</artifactId> <version>2.0-m09</version> <scope>test</scope></dependency><dependency> <groupId>org.glassfish.jersey.core</groupId> <artifactId>jersey-client</artifactId> <version>2.0-m05</version> <scope>test</scope></dependency> The complete list of Maven coordinates for Jersey2 are available here. An up-to-date status of Jersey 2 can always be obtained from here. Here is a simple resource class: @Path("movies")public class MoviesResource { @GET @Path("list") public List<Movie> getMovies() { List<Movie> movies = new ArrayList<Movie>(); movies.add(new Movie("Million Dollar Baby", "Hillary Swank")); movies.add(new Movie("Toy Story", "Buzz Light Year")); movies.add(new Movie("Hunger Games", "Jennifer Lawrence")); return movies; }} This resource publishes a list of movies and is accessible at "movies/list" path with HTTP GET. The project is using the standard JAX-RS APIs. Of course, you need the trivial "Movie" and the "Application" class as well. They are available in the downloadable project anyway. Build the project mvn package And deploy to GlassFish 4.0 promoted build 43 (download, unzip, and start as "bin/asadmin start-domain") as asadmin deploy --force=true target/jersey2-helloworld.war Add a simple test case by right-clicking on the MoviesResource class, select "Tools", "Create Tests", and take defaults. Replace the function "testGetMovies" to @Testpublic void testGetMovies() { System.out.println("getMovies"); Client client = ClientFactory.newClient(); List<Movie> movieList = client.target("http://localhost:8080/jersey2-helloworld/webresources/movies/list") .request() .get(new GenericType<List<Movie>>() {}); assertEquals(3, movieList.size());} This test uses the newly defined JAX-RS 2 client APIs to access the RESTful resource. Run the test by giving the command "mvn test" and see the output as ------------------------------------------------------- T E S T S-------------------------------------------------------Running example.MoviesResourceTestgetMoviesTests run: 1, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.561 secResults :Tests run: 1, Failures: 0, Errors: 0, Skipped: 0 GlassFish 4 contains Jersey 2 as the JAX-RS implementation. If you want to use Jersey 1.1 functionality, then Martin's blog provide more details on that. All JAX-RS 1.x functionality will be supported using standard APIs anyway. This workaround is only required if Jersey 1.x functionality needs to be accessed. The complete source code explained in this project can be downloaded from here. Here are some pointers to follow JAX-RS 2 Specification Early Draft 3 Latest status on specification (jax-rs-spec.java.net) Latest JAX-RS 2.0 Javadocs Latest status on Jersey (Reference Implementation of JAX-RS 2 - jersey.java.net) Latest Jersey API Javadocs Latest GlassFish 4.0 Promoted Build Follow @gf_jersey Provide feedback on Jersey 2 to [email protected] and JAX-RS specification to [email protected].

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  • What's New & Cool in NetBeans IDE 7.x

    - by Geertjan
    Loads of new features have been added to NetBeans IDE during the NetBeans IDE 7.x release cycle, i.e., 7.0 together with all the minor releases that have come after that, up to 7.4, which was released during the last few days. Hard to keep track of everything added over all those releases, so instead of making a "What's New in NetBeans IDE 7.4" slide deck (which would only cover the highlights of the NetBeans IDE 7.4 Release Notes), as we would normally do, we've instead produced "What's New in NetBeans IDE 7.x", which is around 50 slides presenting all the key features of the IDE, together with all the key newest features. Here it is: If you want to present the wonderful world that is the NetBeans ecosystem to your JUG or school or university or colleagues in your company, just download the above slide deck (either PDF or the PowerPoint sources) here: https://netbeans.org/community/teams/evangelism And happy NetBeans IDE 7.4 to everyone using NetBeans IDE everywhere in the world!

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  • Pragmas and exceptions

    - by Darryl Gove
    The compiler pragmas: #pragma no_side_effect(routinename) #pragma does_not_write_global_data(routinename) #pragma does_not_read_global_data(routinename) are used to tell the compiler more about the routine being called, and enable it to do a better job of optimising around the routine. If a routine does not read global data, then global data does not need to be stored to memory before the call to the routine. If the routine does not write global data, then global data does not need to be reloaded after the call. The no side effect directive indicates that the routine does no I/O, does not read or write global data, and the result only depends on the input. However, these pragmas should not be used on routines that throw exceptions. The following example indicates the problem: #include <iostream extern "C" { int exceptional(int); #pragma no_side_effect(exceptional) } int exceptional(int a) { if (a==7) { throw 7; } else { return a+1; } } int a; int c=0; class myclass { public: int routine(); }; int myclass::routine() { for(a=0; a<1000; a++) { c=exceptional(c); } return 0; } int main() { myclass f; try { f.routine(); } catch(...) { std::cout << "Something happened" << a << c << std::endl; } } The routine "exceptional" is declared as having no side effects, however it can throw an exception. The no side effects directive enables the compiler to avoid storing global data back to memory, and retrieving it after the function call, so the loop containing the call to exceptional is quite tight: $ CC -O -S test.cpp ... .L77000061: /* 0x0014 38 */ call exceptional ! params = %o0 ! Result = %o0 /* 0x0018 36 */ add %i1,1,%i1 /* 0x001c */ cmp %i1,999 /* 0x0020 */ ble,pt %icc,.L77000061 /* 0x0024 */ nop However, when the program is run the result is incorrect: $ CC -O t.cpp $ ./a.out Something happend00 If the code had worked correctly, the output would have been "Something happened77" - the exception occurs on the seventh iteration. Yet, the current code produces a message that uses the original values for the variables 'a' and 'c'. The problem is that the exception handler reads global data, and due to the no side effects directive the compiler has not updated the global data before the function call. So these pragmas should not be used on routines that have the potential to throw exceptions.

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  • SOA Suite 11g: Unable to start domain (Error occurred during initialization of VM)

    - by Chris Tomkins
    If you have recently installed SOA Suite, created a domain and then tried to start it only to find it fails with the error: Error occurred during initialization of VM Could not reserve enough space for object heap Could not create the Java virtual machine. the solution is to edit the file <domain home>\bin\setSOADomainEnv.cmd/sh (depending on your platform) and modify the line: set DEFAULT_MEM_ARGS=-Xms512m -Xmx1024m to something like: set DEFAULT_MEM_ARGS=-Xms512m -Xmx768m Save the file and then try to start your domain again. Everything should now work at least it does on the Dell Latitude 630 laptop with 4Gb RAM that I have. Technorati Tags: soa suite,11g,java,troubleshooting,problems,domain

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  • QotD: Heather Vancura-Chilson on 2012 JCP EC Election Ballot

    - by $utils.escapeXML($entry.author)
    The JCP Executive Committee (EC) Election ballot is now open and all of the candidates' nominations materials are now available on JCP.org -- note that two new candidates were nominated late last week: Liferay and North Sixty-One. It is shaping up to be an exciting election this year!The ratified candidates are: Cinterion, Credit Suisse, Fujitsu and HP.The elected candidates are (9 candidates, 2 open seats): Cisco Systems, CloudBees, Giuseppe Dell'Abate, Liferay, London Java Community, MoroccoJUG, North Sixty-One, Software AG, and Zero Turnaround.Heather Vancura-Chilson in a post on the JCP Program Office blog.

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  • ZFS Basics

    - by user12614620
    Stage 1 basics: creating a pool # zpool create $NAME $REDUNDANCY $DISK1_0..N [$REDUNDANCY $DISK2_0..N]... $NAME = name of the pool you're creating. This will also be the name of the first filesystem and, by default, be placed at the mountpoint "/$NAME" $REDUNDANCY = either mirror or raidzN, and N can be 1, 2, or 3. If you leave N off, then it defaults to 1. $DISK1_0..N = the disks assigned to the pool. Example 1: zpool create tank mirror c4t1d0 c4t2d0 name of pool: tank redundancy: mirroring disks being mirrored: c4t1d0 and c4t2d0 Capacity: size of a single disk Example 2: zpool create tank raidz c4t1d0 c4t2d0 c4t3d0 c4t4d0 c4t5d0 Here the redundancy is raidz, and there are five disks, in a 4+1 (4 data, 1 parity) config. This means that the capacity is 4 times the disk size. If the command used "raidz2" instead, then the config would be 3+2. Likewise, "raidz3" would be a 2+3 config. Example 3: zpool create tank mirror c4t1d0 c4t2d0 mirror c4t3d0 c4t4d0 This is the same as the first mirror example, except there are two mirrors now. ZFS will stripe data across both mirrors, which means that writing data will go a bit faster. Note: you cannot create a mirror of two raidzs. You can create a raidz of mirrors, but to do that requires trickery.

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  • Virtual Grocery Store

    - by David Dorf
    Because South Korean's are so busy, Tesco decided that its Homeplus grocery chain should offer a virtual alternative in subways.  As you can see in the video below, shoppers passing through a subway station can see a virtual representation of the store and scan items with their mobile phones.  This builds a shopping list which is delivered to their homes later that day. This is a very cool example of leveraging technology to offer a shopping experience that's different from bricks and clicks.

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  • JavaFX Makeover for JFugue Music NotePad

    - by Geertjan
    Bengt-Erik Fröberg from Sweden, one of the developers working on ProSang, the leading Scandinavian blood bank system (and based on the NetBeans Platform), is reworking the user interface of the JFugue Music NotePad. In particular, the Score window (named ScoreFX window below) contains components that are now quite clearly JavaFX, instead of Swing. Looks a lot better and also performs better. The sliders in the Keyboard window are candidates for being similarly redone to use JavaFX instead of Swing. Want to do something similar? Here's all the info you need: http://platform.netbeans.org/tutorials/nbm-javafx.html

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  • Generalist Languages: Dying or Alive and Well?

    - by dsimcha
    Around here, it seems like there's somewhat of a consensus that generalist programming languages (that try to be good at everything, support multiple paradigms, support both very high- and very low-level programming), etc. are a bad idea, and that it's better to pick the right tool for the job and use lots of different languages. I see three major areas where this is flawed: Interfacing multiple languages is always at least a source of friction and is sometimes practically impossible. How severe a problem this is depends on how fine-grained the interfacing is. Near the boundary between the two languages, though, you're basically limited to the intersection of their features, and you have to care about things like binary interfaces that you usually wouldn't. Passing complex data structures (i.e. not just primitives and arrays of primitives) between languages is almost always a hassle. Furthermore, shifting between different syntaxes, different conventions, etc. can be confusing and annoying, though this is a fairly minor complaint. Requirements are never set in stone. I hate picking a language thinking it's the right tool for the job, then realizing that, when some new requirement surfaces, it's actually a terrible choice for that requirement. This has happened to me several times before, usually when working with languages that are very slow, very domain specific and/or has very poor concurrency/parallelism support. When you program in a language for a while, you start to build up a personal toolbox of small utility functions/classes/programs. The value of these goes drastically down if you're forced to use a different language than the one you've accumulated all this code in. What am I missing here? Why shouldn't more focus be placed on generalist languages? Are generalist languages as a category dying or alive and well?

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