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• Solaris 11 LKSF

  - by nospam(at)example.com (Joerg Moellenkamp)

  After having some discussions i now made my mind about it: In the next weeks you will see many republications of old articles in the blog as i will republish all articles in the LKSF, however checked and updated for Solaris 11 (some Opensolaris based stuff in the lksf is working slightly different, and if it's just for different package names). However this will take time, as i will do this on weekends and evenings. At the end i will just recollect them and create a Solaris LKSF pdf again.

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• ADF for Beehive Developers

  Mapping the UI and Controller technologies

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• HTTP Session Invalidation in Servlet/GlassFish

  - by reza_rahman

  HTTP session invalidation is something most of us take for granted and don't think much about. However for security and performance sensitive applications it is helpful to have at least a basic understanding of how it works in Servlets. In a brief code centric blog post Servlet specification lead Shing Wai Chan introduces the APIs for session invalidation and explains how you can fine tune the underlying reaper thread for session invalidation when it is needed in GlassFish 4. Don't hesitate to post a question here if the blog is not clear, this is a relatively esoteric topic...

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• The Minimalist Approach to Content Governance - Request Phase

  - by Kellsey Ruppel

  Originally posted by John Brunswick. For each project, regardless of size, it is critical to understand the required ownership, business purpose, prerequisite education / resources needed to execute and success criteria around it. Without doing this, there is no way to get a handle on the content life-cyle, resulting in a mass of orphaned material. This lowers the quality of end user experiences.     The good news is that by using a simple process in this request phase - we will not have to revisit this phase unless something drastic changes in the project. For each of the elements mentioned above in this stage, the why, how (technically focused) and impact are outlined with the intent of providing the most value to a small team. 1. Ownership Why - Without ownership information it will not be possible to track and manage any of the content and take advantage of many features of enterprise content management technology. To hedge against this, we need to ensure that both a individual and their group or department within the organization are associated with the content. How - Apply metadata that indicates the owner and department or group that has responsibility for the content. Impact - It is possible to keep the content system optimized by running native reports against the meta-data and acting on them based on what has been outlined for success criteria. This will maximize end user experience, as content will be faster to locate and more relevant to the user by virtue of working through a smaller collection. 2. Business Purpose Why - This simple step will weed out requests that have tepid justification, as users will most likely not spend the effort to request resources if they do not have a real need. How - Use a simple online form to collect and workflow the request to management native to the content system. Impact - Minimizes the amount user generated content that is of low value to the organization. 3. Prerequisite Education Resources Needed Why - If a project cannot be properly staffed the probability of its success is going to be low. By outlining the resources needed - in both skill set and duration - it will cause the requesting party to think critically about the commitment needed to complete their project and what gap must be closed with regard to education of those resources. How - In the simple request form outlined above, resources and a commitment to fulfilling any needed education should be included with a brief acceptance clause that outlines the requesting party's commitment. Impact - This stage acts as a formal commitment to ensuring that resources are able to execute on the vision for the project. 4. Success Criteria Why - Similar to the business purpose, this is a key element in helping to determine if the project and its respective content should continue to exist if it does not meet its intended goal. How - Set a review point for the project content that will check the progress against the originally outlined success criteria and then determine the fate of the content. This can even include logic that will tell the content system to remove items that have not been opened by any users in X amount of time. Impact - This ensures that projects and their contents do not live past their useful lifespans. Just as with orphaned content, non-relevant information will slow user's access to relevant materials for the jobs. Request Phase Summary With a simple form that outlines the ownership of a project and its content, business purpose, education and resources, along with success criteria, we can ensure that an enterprise content management system will stay clean and relevant to end users - allowing it to deliver the most value possible. The key here is to make it straightforward to make the request and let the content management technology manage as much as possible through metadata, retention policies and workflow. Doing these basic steps will allow project content to get off to a great start in the enterprise! Stay tuned for the next installment - the "Create Phase" - covering security access and workflow involved in content creation, enabling a practical layer of governance over our enterprise content repository.

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• Coherence Data Guarantees for Data Reads - Basic Terminology

  - by jpurdy

  When integrating Coherence into applications, each application has its own set of requirements with respect to data integrity guarantees. Developers often describe these requirements using expressions like "avoiding dirty reads" or "making sure that updates are transactional", but we often find that even in a small group of people, there may be a wide range of opinions as to what these terms mean. This may simply be due to a lack of familiarity, but given that Coherence sits at an intersection of several (mostly) unrelated fields, it may be a matter of conflicting vocabularies (e.g. "consistency" is similar but different in transaction processing versus multi-threaded programming). Since almost all data read consistency issues are related to the concept of concurrency, it is helpful to start with a definition of that, or rather what it means for two operations to be concurrent. Rather than implying that they occur "at the same time", concurrency is a slightly weaker statement -- it simply means that it can't be proven that one event precedes (or follows) the other. As an example, in a Coherence application, if two client members mutate two different cache entries sitting on two different cache servers at roughly the same time, it is likely that one update will precede the other by a significant amount of time (say 0.1ms). However, since there is no guarantee that all four members have their clocks perfectly synchronized, and there is no way to precisely measure the time it takes to send a given message between any two members (that have differing clocks), we consider these to be concurrent operations since we can not (easily) prove otherwise. So this leads to a question that we hear quite frequently: "Are the contents of the near cache always synchronized with the underlying distributed cache?". It's easy to see that if an update on a cache server results in a message being sent to each near cache, and then that near cache being updated that there is a window where the contents are different. However, this is irrelevant, since even if the application reads directly from the distributed cache, another thread update the cache before the read is returned to the application. Even if no other member modifies a cache entry prior to the local near cache entry being updated (and subsequently read), the purpose of reading a cache entry is to do something with the result, usually either displaying for consumption by a human, or by updating the entry based on the current state of the entry. In the former case, it's clear that if the data is updated faster than a human can perceive, then there is no problem (and in many cases this can be relaxed even further). For the latter case, the application must assume that the value might potentially be updated before it has a chance to update it. This almost aways the case with read-only caches, and the solution is the traditional optimistic transaction pattern, which requires the application to explicitly state what assumptions it made about the old value of the cache entry. If the application doesn't want to bother stating those assumptions, it is free to lock the cache entry prior to reading it, ensuring that no other threads will mutate the entry, a pessimistic approach. The optimistic approach relies on what is sometimes called a "fuzzy read". In other words, the application assumes that the read should be correct, but it also acknowledges that it might not be. (I use the qualifier "sometimes" because in some writings, "fuzzy read" indicates the situation where the application actually sees an original value and then later sees an updated value within the same transaction -- however, both definitions are roughly equivalent from an application design perspective). If the read is not correct it is called a "stale read". Going back to the definition of concurrency, it may seem difficult to precisely define a stale read, but the practical way of detecting a stale read is that is will cause the encompassing transaction to roll back if it tries to update that value. The pessimistic approach relies on a "coherent read", a guarantee that the value returned is not only the same as the primary copy of that value, but also that it will remain that way. In most cases this can be used interchangeably with "repeatable read" (though that term has additional implications when used in the context of a database system). In none of cases above is it possible for the application to perform a "dirty read". A dirty read occurs when the application reads a piece of data that was never committed. In practice the only way this can occur is with multi-phase updates such as transactions, where a value may be temporarily update but then withdrawn when a transaction is rolled back. If another thread sees that value prior to the rollback, it is a dirty read. If an application uses optimistic transactions, dirty reads will merely result in a lack of forward progress (this is actually one of the main risks of dirty reads -- they can be chained and potentially cause cascading rollbacks). The concepts of dirty reads, fuzzy reads, stale reads and coherent reads are able to describe the vast majority of requirements that we see in the field. However, the important thing is to define the terms used to define requirements. A quick web search for each of the terms in this article will show multiple meanings, so I've selected what are generally the most common variations, but it never hurts to state each definition explicitly if they are critical to the success of a project (many applications have sufficiently loose requirements that precise terminology can be avoided).

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• Implementing a Custom Coherence PartitionAssignmentStrategy

  - by jpurdy

  A recent A-Team engagement required the development of a custom PartitionAssignmentStrategy (PAS). By way of background, a PAS is an implementation of a Java interface that controls how a Coherence partitioned cache service assigns partitions (primary and backup copies) across the available set of storage-enabled members. While seemingly straightforward, this is actually a very difficult problem to solve. Traditionally, Coherence used a distributed algorithm spread across the cache servers (and as of Coherence 3.7, this is still the default implementation). With the introduction of the PAS interface, the model of operation was changed so that the logic would run solely in the cache service senior member. Obviously, this makes the development of a custom PAS vastly less complex, and in practice does not introduce a significant single point of failure/bottleneck. Note that Coherence ships with a default PAS implementation but it is not used by default. Further, custom PAS implementations are uncommon (this engagement was the first custom implementation that we know of). The particular implementation mentioned above also faced challenges related to managing multiple backup copies but that won't be discussed here. There were a few challenges that arose during design and implementation: Naive algorithms had an unreasonable upper bound of computational cost. There was significant complexity associated with configurations where the member count varied significantly between physical machines. Most of the complexity of a PAS is related to rebalancing, not initial assignment (which is usually fairly simple). A custom PAS may need to solve several problems simultaneously, such as: Ensuring that each member has a similar number of primary and backup partitions (e.g. each member has the same number of primary and backup partitions) Ensuring that each member carries similar responsibility (e.g. the most heavily loaded member has no more than one partition more than the least loaded). Ensuring that each partition is on the same member as a corresponding local resource (e.g. for applications that use partitioning across message queues, to ensure that each partition is collocated with its corresponding message queue). Ensuring that a given member holds no more than a given number of partitions (e.g. no member has more than 10 partitions) Ensuring that backups are placed far enough away from the primaries (e.g. on a different physical machine or a different blade enclosure) Achieving the above goals while ensuring that partition movement is minimized. These objectives can be even more complicated when the topology of the cluster is irregular. For example, if multiple cluster members may exist on each physical machine, then clearly the possibility exists that at certain points (e.g. following a member failure), the number of members on each machine may vary, in certain cases significantly so. Consider the case where there are three physical machines, with 3, 3 and 9 members each (respectively). This introduces complexity since the backups for the 9 members on the the largest machine must be spread across the other 6 members (to ensure placement on different physical machines), preventing an even distribution. For any given problem like this, there are usually reasonable compromises available, but the key point is that objectives may conflict under extreme (but not at all unlikely) circumstances. The most obvious general purpose partition assignment algorithm (possibly the only general purpose one) is to define a scoring function for a given mapping of partitions to members, and then apply that function to each possible permutation, selecting the most optimal permutation. This would result in N! (factorial) evaluations of the scoring function. This is clearly impractical for all but the smallest values of N (e.g. a partition count in the single digits). It's difficult to prove that more efficient general purpose algorithms don't exist, but the key take away from this is that algorithms will tend to either have exorbitant worst case performance or may fail to find optimal solutions (or both) -- it is very important to be able to show that worst case performance is acceptable. This quickly leads to the conclusion that the problem must be further constrained, perhaps by limiting functionality or by using domain-specific optimizations. Unfortunately, it can be very difficult to design these more focused algorithms. In the specific case mentioned, we constrained the solution space to very small clusters (in terms of machine count) with small partition counts and supported exactly two backup copies, and accepted the fact that partition movement could potentially be significant (preferring to solve that issue through brute force). We then used the out-of-the-box PAS implementation as a fallback, delegating to it for configurations that were not supported by our algorithm. Our experience was that the PAS interface is quite usable, but there are intrinsic challenges to designing PAS implementations that should be very carefully evaluated before committing to that approach.

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• JHeadstart search with default values

  - by christian.bischof

  JHeadstart has a powerful generator for ADF Faces pages. One of the features of the generator is the generation of search functionality into a page. The search functionality offers a "Quicksearch" with a single search item and an "Advanced Search" for multiple search criteria. Sometimes it would be nice to have initial values for the search criteria, but this is not supplied by JHeadstart by default.

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• Grails project structure

  - by Martin Janicek

  Good news everyone! I've changed the structure of the Grails project as requested in the issue 160028 and it should be much more user friendly than before. There are actually two things I've fixed/implemented. First of all the source folders are finally represented in the same way as for the Java projects (which means instead of the folder based structure it uses package based structure). The difference can be seen on pictures bellow:    Folder based structure:                                                 Package based structure: Second, minor and quite related change could be seen on those pictures too. There are different icons for different structures. For example Views and Layouts items are folder based, Domain Classes are package based and so on.

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• Attending MySQL Connect? Your Opinion Matters.

  - by Monica Kumar

  Take the MySQL Connect 2012 Survey Thanks to everyone who is at the first ever MySQL Connect Conference in San Francisco this weekend! Don't forget to take your Conference and Session Surveys. Your opinions help shape next year's conference. Take a survey for each of the sessions you attend and be entered into a drawing for one prize for $200 American Express Gift Certificate. Fill in the daily conference survey and be entered into a drawing for one prize for a $500 American Express Gift Card Surveys are located here. Make your opinion count! Take the survey now. Congratulations to Robin Schumacher from DataStax as he is the winner of the Saturday survey!

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• My Obligatory IPad Post

  - by mark.wilcox

  I've had my IPad for about a week now. So I thought I'd write some thoughts down based on my initial experiences. Here are my initial take-aways: 1 - Netflix OnDemand - I'm a movie junkie. I'm now more apt to just start a movie as background sound for my workday (I telecommute - so except for the occasional bark from my dog, it's awfully quiet here if I don't have something going). 2 - The Email Client is really nice and I'm as fast or faster typing when I have the wireless keyboard engaged. Even with onscreen keyboard - I'm already close to 75% of desktop speed 3 - The battery life is incredible - I think this is the first case where a mobile device actually under-promised on battery 4 - It totally has killed the notion of using a normal PC for my wife and mother-in-law - neither of which had wanted an iPhone/iPod Touch or really any Apple device until they got to play with my iPad. The concept of - instant on, easy to hold and touch-based navigation has them hooked. Heck, it has me hooked. My ultimate goal is to be able to have it at least replace the need to take my netbook with me on the road. I haven't had a chance to complete my testing on that front yet - between work, my wife traveling (for a change) and now my wife home sick - I haven't had time to just play with it. But so far my only regret - that I haven't already bought two more for everyone else in my family who wants to use mine. Posted via email from Virtual Identity Dialogue

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• Concurrency Utilities for Java EE 6: JSR 236 Rebooting

  - by arungupta

  JSR 166 added support for concurrency utilities in the Java platform. The JSR 236's, a.k.a Concurrency Utilities for Java EE, goal was to extend that support to the Java EE platform by adding asynchronous abilities to different application components. The EG was however stagnant since Dec 2003. Its coming back to life with the co-spec lead Anthony Lai's message to the JSR 236 EG (archived here). The JSR will be operating under JCP 2.8's transparency rules and can be tracked at concurrency-spec.java.net. All the mailing lists are archived here. The final release is expected in Q1 2013 and the APIs will live in the javax.enterprise.concurrent package. Please submit your nomination if you would like to join this EG.

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• SPARC Architecture 2011

  - by Darryl Gove

  With what appears to be minimal fanfare, an update of the SPARC Architecture has been released. If you ever look at SPARC disassembly code, then this is the document that you need to bookmark. If you are not familiar with it, then it basically describes how a SPARC processor should behave - it doesn't describe a particular implementation, just the "generic" processor. As with all revisions, it supercedes the SPARC v9 book published back in the 90s, having both corrections, and definitions of new instructions. Anyway, should be an interesting read

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• Employee Engagement: Drive Business Value

  - by Kellsey Ruppel

  As we’ve been discussing this week, employee engagement is extremely important and you’ve probably realized that effectively engaging your employees is essential to driving business value. Your employees are the ones responsible for executing on the business’ objectives. Your employees (in the sales & service departments) are the ones interacting with your customers the most, so delivering on customer expectations and attaining high levels of customer engagement are simply not possible without successfully empowering these this stakeholder group. High employee and partner engagement can have many benefits including: Higher levels of employee productivity Longer employee retention Stronger, more enduring and more successful relationships Serving as ambassadors for an organization’s brand More likely to deliver excellent customer service Referring others for hire Recommending the organization’s products and services Sharing feedback with their colleagues In a way, engagement is a measure of employee investment in an organization’s mission and brand. And then you have the enablement piece of this as well.  It’s hard to imagine a high level of engagement existing among employees who don’t feel that they’ve been enabled to do their jobs very efficiently or effectively. You’re just not going to find high engagement among people if the everyday processes and technologies  they work with make it a challenge for them to access, share and manage the information  they need do their jobs or if they’re unable to effectively collaborate around the projects they’re working on. How does your organization measure on the employee engagement spectrum? We’ve got a number of different resources to help you get started! Portal Resource Center Video: Got a minute? WebCenter in Action Webcast Series Portal Engagement Webcast 

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• Don't Miss OPN Exchange @ OpenWorld: Register NOW!

  - by Cinzia Mascanzoni

  Don't miss the opportunity to register to OPN Exchange @ OpenWorld at Early Bird pricing : $ 595. The promotion will end September 7th. OPN Exchange is the only pass that gives you access to more than 40 Partner dedicated sessions, held Monday-Thursday, to OPN Lounge and OPN Test Fest. If you have registered with Full Conference pass, here is what you can do to add OPN Exchange to your registration: Go to My Account and add (add-on section) the OPN Exchange pass for $ 100. If you have registered for a Discover Pass: contact the registration team and ask for the upgrade at Tel: +1.650.226.0812 (International) Monday through Friday, 6:00 a.m. to 6:00 p.m. (Pacific time) or Email: [email protected].

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• Yet another GlassFish 3.1.1 promoted build

  - by alexismp

  Promoted build #9 for GlassFish 3.1.1 is available from the usual location. This is the "soft code freeze" build with only the "hard code freeze" build left before the release candidate. So if you have bugs you'd like to see fixed, voice your opinion *now*. As a quick reminder, GlassFish offers Web Profile or Full Platform distributions in ZIP or installer flavors (some more details in this blog post from last year but still relevant). If you've installed previous promoted builds or simply have the "dev" repository defined, then the Update Center will simply update the existing installed bits. In addition to the earlier update on 3.1.1 it's probably safe to say that this version was carefully designed to be highly compatible with the previous 3.x versions, thus leaving you with little reasons not to upgrade as soon as it comes out this summer.

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• PL/SQL Practices: "On Avoiding Termination"

  Continue PL/SQL execution beyond exceptions.

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• Fun tips with Analytics

  - by user12620172

  If you read this blog, I am assuming you are at least familiar with the Analytic functions in the ZFSSA. They are basically amazing, very powerful and deep. However, you may not be aware of some great, hidden functions inside the Analytic screen. Once you open a metric, the toolbar looks like this: Now, I’m not going over every tool, as we have done that before, and you can hover your mouse over them and they will tell you what they do. But…. Check this out. Open a metric (CPU Percent Utilization works fine), and click on the “Hour” button, which is the 2nd clock icon. That’s easy, you are now looking at the last hour of data. Now, hold down your ‘Shift’ key, and click it again. Now you are looking at 2 hours of data. Hold down Shift and click it again, and you are looking at 3 hours of data. Are you catching on yet? You can do this with not only the ‘Hour’ button, but also with the ‘Minute’, ‘Day’, ‘Week’, and the ‘Month’ buttons. Very cool. It also works with the ‘Show Minimum’ and ‘Show Maximum’ buttons, allowing you to go to the next iteration of either of those. One last button you can Shift-click is the handy ‘Drill’ button. This button usually drills down on one specific aspect of your metric. If you Shift-click it, it will display a “Rainbow Highlight” of the current metric. This works best if this metric has many ‘Range Average’ items in the left-hand window. Give it a shot. Also, one will sometimes click on a certain second of data in the graph, like this:  In this case, I clicked 4:57 and 21 seconds, and the 'Range Average' on the left went away, and was replaced by the time stamp. It seems at this point to some people that you are now stuck, and can not get back to an average for the whole chart. However, you can actually click on the actual time stamp of "4:57:21" right above the chart. Even though your mouse does not change into the typical browser finger that most links look like, you can click it, and it will change your range back to the full metric. Another trick you may like is to save a certain view or look of a group of graphs. Most of you know you can save a worksheet, but did you know you could Sync them, Pause them, and then Save it? This will save the paused state, allowing you to view it forever the way you see it now.  Heatmaps. Heatmaps are cool, and look like this:  Some metrics use them and some don't. If you have one, and wish to zoom it vertically, try this. Open a heatmap metric like my example above (I believe every metric that deals with latency will show as a heatmap). Select one or two of the ranges on the left. Click the "Change Outlier Elimination" button. Click it again and check out what it does.  Enjoy. Perhaps my next blog entry will be the best Analytic metrics to keep your eyes on, and how you can use the Alerts feature to watch them for you. Steve 

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• Skynet Big Data Demo Using Hexbug Spider Robot, Raspberry Pi, and Java SE Embedded (Part 4)

  - by hinkmond

  Here's the first sign of life of a Hexbug Spider Robot converted to become a Skynet Big Data model T-1. Yes, this is T-1 the precursor to the Cyberdyne Systems T-101 (and you know where that will lead to...) It is demonstrating a heartbeat using a simple Java SE Embedded program to drive it. See: Skynet Model T-1 Heartbeat It's alive!!! Well, almost alive. At least there's a pulse. We'll program more to its actions next, and then finally connect it to Skynet Big Data to do more advanced stuff, like hunt for Sara Connor. Java SE Embedded programming makes it simple to create the first model in the long line of T-XXX robots to take on the world. Raspberry Pi makes connecting it all together on one simple device, easy. Next post, I'll show how the wires are connected to drive the T-1 robot. Hinkmond

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• JCP.Next Progress Updates

  - by heathervc

  JSR 355, JCP Executive Committee Merge, is currently nearing the end of the Public Review period.  Review the current draft here and provide feedback here.  The review closes on 12 June 2012.  The JCP Executive Committee met face to face in Sao Paulo, Brazil earlier in May, and has published a revision (version 2.1) of the EC Standing Rules.  The EC Standing Rules were introduced in October 2011 with the launch of JCP version 2.8 (JSR 348).  Version 2.1 of the EC Standing Rules will modify rules for attendance at EC face-to-face meetings. Remote observers will be permitted in "read-only" mode but unless a member attends in person they will be counted as absent.  The review period for these changes will close on June 30 2012.  Please comment on the proposed changes by logging an issue in the JCP EC issue tracker.

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• MySQL Workbench 5.2.43 GA released

  - by Alfredo Kojima

  The MySQL developer tools team announces the availability of version 5.2.43 of the MySQL Workbench GUI tool. This version contains various fixes and minor enhancements and includes 53 resolved bugs. With this version, Fedora 15 packages are replaced with Fedora 17. Also, Gatekeeper in Mac OS X Mountain Lion is now properly handled. For a full list of issues fixed in this release, see http://dev.mysql.com/doc/workbench/en/changes-5.2.x.html Please get your copy from our Downloads site. In Windows, you can also use the MySQL Windows Installer to update Workbench. Sources and binary packages are available for several platforms, including Windows, Mac OS X and Linux. http://dev.mysql.com/downloads/workbench/ Workbench Documentation can be found here. http://dev.mysql.com/doc/workbench/en/index.html Utilities Documentation can be found here. http://dev.mysql.com/doc/workbench/en/mysql-utilities.html If you need any additional info or help please get in touch with us. Post in our forums or leave comments on our blog pages. - The MySQL Workbench Team

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• JCP Open EC Meeting on 30 September 2012

  - by heathervc

  The JCP program office and Executive Committee invites all Java Community members to attend the OPEN EC Meeting on Sunday, 30 September at the Clift Hotel in San Francisco.  The meeting is adjacent to The Zone at JavaOne, but no JavaOne (or any other kind) of pass is required to attend.  It is OPEN to all!  Agenda topics include: JCP.Next status/overview of JSRs 355 and 358, improving communications between the EC and the community; Open Q&A and reminders of JCP events at JavaOne & Annual awards.  Any other suggestions?  This meeting is for you.  Let us know your questions pmo at jcp.org. Or bring them with you.  Details below. JCP Public Executive Committee Face-to-Face Meeting Open to Executive Committee Members and the Java Developer Community Location: Clift Hotel, 495 Geary Street, San Francisco - Rita Room (downstairs from Lobby) Date and Time: 9/30/12, 2:00 PM - 3:30 PM See you there.  Check out all of the JCP @ JavaOne events.

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• Frameworks: "Embracing Extends"

  Simplifying development via inheritance

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• Non-blocking I/O using Servlet 3.1: Scalable applications using Java EE 7 (TOTD #188)

  - by arungupta

  Servlet 3.0 allowed asynchronous request processing but only traditional I/O was permitted. This can restrict scalability of your applications. In a typical application, ServletInputStream is read in a while loop. public class TestServlet extends HttpServlet {    protected void doGet(HttpServletRequest request, HttpServletResponse response)         throws IOException, ServletException {     ServletInputStream input = request.getInputStream();       byte[] b = new byte[1024];       int len = -1;       while ((len = input.read(b)) != -1) {          . . .        }   }} If the incoming data is blocking or streamed slower than the server can read then the server thread is waiting for that data. The same can happen if the data is written to ServletOutputStream. This is resolved in Servet 3.1 (JSR 340, to be released as part Java EE 7) by adding event listeners - ReadListener and WriteListener interfaces. These are then registered using ServletInputStream.setReadListener and ServletOutputStream.setWriteListener. The listeners have callback methods that are invoked when the content is available to be read or can be written without blocking. The updated doGet in our case will look like: AsyncContext context = request.startAsync();ServletInputStream input = request.getInputStream();input.setReadListener(new MyReadListener(input, context)); Invoking setXXXListener methods indicate that non-blocking I/O is used instead of the traditional I/O. At most one ReadListener can be registered on ServletIntputStream and similarly at most one WriteListener can be registered on ServletOutputStream. ServletInputStream.isReady and ServletInputStream.isFinished are new methods to check the status of non-blocking I/O read. ServletOutputStream.canWrite is a new method to check if data can be written without blocking.  MyReadListener implementation looks like: @Overridepublic void onDataAvailable() { try { StringBuilder sb = new StringBuilder(); int len = -1; byte b[] = new byte[1024]; while (input.isReady() && (len = input.read(b)) != -1) { String data = new String(b, 0, len); System.out.println("--> " + data); } } catch (IOException ex) { Logger.getLogger(MyReadListener.class.getName()).log(Level.SEVERE, null, ex); }}@Overridepublic void onAllDataRead() { System.out.println("onAllDataRead"); context.complete();}@Overridepublic void onError(Throwable t) { t.printStackTrace(); context.complete();} This implementation has three callbacks: onDataAvailable callback method is called whenever data can be read without blocking onAllDataRead callback method is invoked data for the current request is completely read. onError callback is invoked if there is an error processing the request. Notice, context.complete() is called in onAllDataRead and onError to signal the completion of data read. For now, the first chunk of available data need to be read in the doGet or service method of the Servlet. Rest of the data can be read in a non-blocking way using ReadListener after that. This is going to get cleaned up where all data read can happen in ReadListener only. The sample explained above can be downloaded from here and works with GlassFish 4.0 build 64 and onwards. The slides and a complete re-run of What's new in Servlet 3.1: An Overview session at JavaOne is available here. Here are some more references for you: Java EE 7 Specification Status Servlet Specification Project JSR Expert Group Discussion Archive Servlet 3.1 Javadocs

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• JCP 2012 Award Nominations are now open!

  - by heathervc

  The 10th JCP Annual Awards Nominations are now open until 16 July 2012. Submit nominations to [email protected] or use form here. The Java Community Process (JCP) program celebrates success. Members of the community nominate worthy participants, Spec Leads, and Java Specification Requests (JSRs) in order to cheer on the hard work and creativity that produces ground-breaking results for the community and industry in the Java Standard Edition (SE), Java Enterprise Edition (EE), or Java Micro Edition (ME) platforms. The community gets together every year at the JavaOne conference to applaud in person the winners of three awards: JCP Member/Participant of the Year, Outstanding Spec Lead, and Most Significant JSR. This year’s unveiling will occur Tuesday evening, 2 October, at the Annual JCP Community Party held in San Francisco.  Nominate today...descriptions of the award categories for this year: JCP Member/Participant Of The Year - This award recognizes the corporate or individual member (either Member or Participant) who has made the most significant positive impact on the community in the past year. Leadership, investment in the community, and innovation are some of the qualities that EC Members look for in voting for this award. Outstanding Spec Lead - The role of Spec Lead is not an easy one, and the person who takes that responsibility must be, among other things, technically savvy, able to build consensus in spite of diverse corporate goals, and focused on efficiency and execution. This award recognizes the person who has brought together these qualities the best in the past year, in leading a JSR for the Java community (Java SE, Java EE or Java ME). Most Significant JSR - Specification development is key to the success of the JCP program and helps ensure we remain a fresh and vibrant community. This award recognizes the Spec Lead and Expert Group that have contributed (either in progress or final) the most significant JSR for the Java community (Java SE, Java EE or Java ME) in the past year.

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• Nashorn in the Twitterverse

  - by jlaskey

  I have been following how often Nashorn has been showing up on the net.  Nashorn got a burst of tweets when we announced Project Nashorn and I was curious how Nashorn was trending per day, maybe graph the result.  Counting tweets manually seemed mindless, so why not write a program to do the same. This is where Nashorn + Java came shining through.  There is a very nice Java library out there called Twitter4J https://github.com/yusuke/twitter4j that handles all things Twitter.  After running bin/getAccessToken.sh to get a twitter4j.properties file with personal authorization, all I had to do to run my simple exploratory app was; nashorn -cp $TWITTER4J/twitter4j-core-3.0.1.jar GetHomeTimeline.js The content of GetHomeTimeline.js is as follows; var twitter4j      = Packages.twitter4j; var TwitterFactory = twitter4j.TwitterFactory; var Query          = twitter4j.Query; var twitter = new TwitterFactory().instance; var query   = new Query("nashorn OR nashornjs"); query.count = 100; do {     var result = twitter.search(query);     var tweets = result.tweets;     for each (tweet in tweets) {         print("@" + tweet.user.screenName + "\t" + tweet.text);     } } while (query = result.nextQuery()); How easy was that?  Now to hook it up to the JavaFX graphing library... 

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