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  • The Benefits of Upgrading to PeopleSoft 9.0

    Doris Wong, Vice President and General Manager of PeopleSoft Enterprise speaks with Fred about how PeopleSoft 9.0 fits into Applications Unlimited, what the key enhancements are in release 9.0 and why PeopleSoft customers should consider upgrading to this new release.

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  • Essbase - FormatString

    - by THE
    A look at the documentation for "Typed Measures" shows:"Using format strings, you can format the values (cell contents) of Essbase database members in numeric type measures so that they appear, for query purposes, as text, dates, or other types of predefined values. The resultant display value is the cell’s formatted value (FORMATTED_VALUE property in MDX). The underlying real value is numeric, and this value is unaffected by the associated formatted value."To actually switch ON the use of typed measures in general, you need to navigate to the outline properties: open outline select properties change "Typed Measures enable" to TRUE (click to enlarge) As an example, I created two additional members in the ASOSamp outline. - A member "delta Price" in the Measures (Accounts) Dimension with the Formula: ([Original Price],[Curr_year])-([Original Price],[Prev_year])This is equivalent to the Variance Formula used in the "Years" Dimension. - A member "Var_Quickview" in the "Years" Dimension with the same formula as the "Variance" Member.This will be used to simply display a second cell with the same underlying value as Variance - but formatted using Format String hence enabling BOTH in the same report. (click to enlarge) In the outline you now select the member you want the Format String associated with and change the "associated Format String" in the Member Properties.As you can see in this example an IIF statement reading:MdxFormat(IIF(CellValue()< 0,"Negative","Positive" ) ) has been chosen for both new members.After applying the Format String changes and running a report via SmartView, the result is: (click to enlarge) reference: Essbase Database Admin Guide ,Chapter 12 "Working with Typed Measures "

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  • YouTube: CoffeeScript Rocks (in NetBeans IDE)

    - by Geertjan
    CoffeeScript is a handy preprocessor for JavaScript, as shown in a quick demo below on YouTube, using the CoffeeScript plugin for NetBeans IDE. Right now, the NetBeans Plugin Portal doesn't have a CoffeeScript plugin for NetBeans IDE 7.4, but not to worry, the NetBeans IDE 7.3 plugin works just fine. http://plugins.netbeans.org/plugin/39007/coffeescript-netbeans Here's a small YouTube clip I made today showing how it all works: Also read this very handy and detailed NetBeans tutorial, on which I based the demo above: https://netbeans.org/kb/docs/web/js-toolkits-jquery.html Related info: http://www.youtube.com/watch?v=QgqVh_KpVKY http://www.ibm.com/developerworks/library/wa-coffee1/ http://blog.sethladd.com/2012/01/vanilla-dart-ftw.html http://api.jquery.com/fadeOut/

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  • Friday Stats

    - by jjg
    As some of you may have noticed, we've recently opened a new repository in the Code Tools project for small utilities which can be used to gather info about the OpenJDK code base and builds. 1 The latest addition is a utility for analyzing the class file versions in a collection of class files. I've posted an example set of results from analyzing the class files in an OpenJDK build on Linux. 2. Most of the files are version 52 files as you would expect, but there is a surprising number of version 51 and 50 files, as well as a handful of v45.3 files as well. Digging deeper, it turns out that Nashorn is still using version 51 class files, and the Serviceability Agent is still using version 50 class files and one 45.3 class file, leaving the remainder of the 45.3 class files coming from RMI. For more info on the different class file versions, see Joe Darcy's class file version decoder rIng. Thanks to Stuart Marks for planting the seed for the class file version tool. See the project page, repo, and mail archive. http://cr.openjdk.java.net/~jjg/cfv-summary/open/

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  • PostgreSQL, Ubuntu, NetBeans IDE (Part 1)

    - by Geertjan
    While setting up PostgreSQL from scratch, with the aim to use it in NetBeans IDE, I found the following resources helpful: http://railskey.wordpress.com/2012/05/19/postgresql-installation-in-ubuntu-12-04/ http://ohdevon.wordpress.com/2011/09/17/postgresql-to-netbeans-1/ http://ohdevon.wordpress.com/2011/09/19/postgresql-to-netbeans-2/ For quite a while I had problems relating to  "/var/run/postgresql/.s.PGSQL.5432", which had something to do with "postmaster.pid", which I somehow solved via a link I can't find anymore, and which may not have been a problem to begin with. A key moment was this one, which was useful for setting the password of a new user I'd created: http://stackoverflow.com/questions/7695962/postgresql-password-authentication-failed-for-user-postgres This was useful for setting up a table in my database, which I did by pasting in the below into NetBeans after I made the connection there: http://use-the-index-luke.com/sql/example-schema/postgresql/where-clause Now I have a database set up with all permissions everywhere (which turned out to be the hard part) correct: The next step will be to create a NetBeans Platform application based on this database. I'm assuming it shouldn't be any different to what's described in the NetBeans Platform CRUD Tutorial.

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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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  • NetBeans 7.2 RC1 is published

    - by Ondrej Brejla
    NetBeans 7.2 RC1 was today published. You can download it here. You could read about the PHP features added to the NetBeans 7.2 release here on the blog, but the main features added or improved are: Support for PHP 5.4 PHP editing: Fix Uses action, annotations support, editing of Neon and Apache Config files and more Support for Symfony2, Doctrine2 and ApiGen frameworks FTP remote synchronization Support for running PHP projects on Hudson For more information, just look at New and Noteworthy page for NetBeans 7.2. And as obvious you can help us to test the build. Just try it and if you find an issue / error, please report it. Thanks for your help.

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  • Performance triage

    - by Dave
    Folks often ask me how to approach a suspected performance issue. My personal strategy is informed by the fact that I work on concurrency issues. (When you have a hammer everything looks like a nail, but I'll try to keep this general). A good starting point is to ask yourself if the observed performance matches your expectations. Expectations might be derived from known system performance limits, prototypes, and other software or environments that are comparable to your particular system-under-test. Some simple comparisons and microbenchmarks can be useful at this stage. It's also useful to write some very simple programs to validate some of the reported or expected system limits. Can that disk controller really tolerate and sustain 500 reads per second? To reduce the number of confounding factors it's better to try to answer that question with a very simple targeted program. And finally, nothing beats having familiarity with the technologies that underlying your particular layer. On the topic of confounding factors, as our technology stacks become deeper and less transparent, we often find our own technology working against us in some unexpected way to choke performance rather than simply running into some fundamental system limit. A good example is the warm-up time needed by just-in-time compilers in Java Virtual Machines. I won't delve too far into that particular hole except to say that it's rare to find good benchmarks and methodology for java code. Another example is power management on x86. Power management is great, but it can take a while for the CPUs to throttle up from low(er) frequencies to full throttle. And while I love "turbo" mode, it makes benchmarking applications with multiple threads a chore as you have to remember to turn it off and then back on otherwise short single-threaded runs may look abnormally fast compared to runs with higher thread counts. In general for performance characterization I disable turbo mode and fix the power governor at "performance" state. Another source of complexity is the scheduler, which I've discussed in prior blog entries. Lets say I have a running application and I want to better understand its behavior and performance. We'll presume it's warmed up, is under load, and is an execution mode representative of what we think the norm would be. It should be in steady-state, if a steady-state mode even exists. On Solaris the very first thing I'll do is take a set of "pstack" samples. Pstack briefly stops the process and walks each of the stacks, reporting symbolic information (if available) for each frame. For Java, pstack has been augmented to understand java frames, and even report inlining. A few pstack samples can provide powerful insight into what's actually going on inside the program. You'll be able to see calling patterns, which threads are blocked on what system calls or synchronization constructs, memory allocation, etc. If your code is CPU-bound then you'll get a good sense where the cycles are being spent. (I should caution that normal C/C++ inlining can diffuse an otherwise "hot" method into other methods. This is a rare instance where pstack sampling might not immediately point to the key problem). At this point you'll need to reconcile what you're seeing with pstack and your mental model of what you think the program should be doing. They're often rather different. And generally if there's a key performance issue, you'll spot it with a moderate number of samples. I'll also use OS-level observability tools to lock for the existence of bottlenecks where threads contend for locks; other situations where threads are blocked; and the distribution of threads over the system. On Solaris some good tools are mpstat and too a lesser degree, vmstat. Try running "mpstat -a 5" in one window while the application program runs concurrently. One key measure is the voluntary context switch rate "vctx" or "csw" which reflects threads descheduling themselves. It's also good to look at the user; system; and idle CPU percentages. This can give a broad but useful understanding if your threads are mostly parked or mostly running. For instance if your program makes heavy use of malloc/free, then it might be the case you're contending on the central malloc lock in the default allocator. In that case you'd see malloc calling lock in the stack traces, observe a high csw/vctx rate as threads block for the malloc lock, and your "usr" time would be less than expected. Solaris dtrace is a wonderful and invaluable performance tool as well, but in a sense you have to frame and articulate a meaningful and specific question to get a useful answer, so I tend not to use it for first-order screening of problems. It's also most effective for OS and software-level performance issues as opposed to HW-level issues. For that reason I recommend mpstat & pstack as my the 1st step in performance triage. If some other OS-level issue is evident then it's good to switch to dtrace to drill more deeply into the problem. Only after I've ruled out OS-level issues do I switch to using hardware performance counters to look for architectural impediments.

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  • Reusing Web Forms across BPM Roles

    - by Mona Rakibe
    Recently Varsha(another BPM Product Manager) approached me with a requirement where she wanted to reuse same Web Form for different task activity.We both knew this is easily achievable.The human task outcomes can differ to distinguish the submission based on roles.Her requirement was slightly more than this, she wanted to hide some data based on the logged in user. If you have worked on Web Form rules, dynamically showing and hiding data is common requirement and easily achievable using Form Rules. In this case the challenge was accessing BPM role inside the Web Form. Although, will be addressing this requirement in future release she wanted a immediate solution(Aha, after all customers are not the only one's who can not wait). Thankfully we managed to come-up with a solution and I hope this will be helpful to larger audience. Solution has 3 steps : Step 1: We added a hidden attribute in our form (Role). The purpose of this attribute is just to store the current logged in user's role and we pass the value during data association. Step 2 : In your data association step, pass the role value based on the Swimlane Step 3 : Now use this hidden attribute value in your Web Form rule for dynamic behavior Detailed steps and sample can be downloaded from Java.net.

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  • ZFS for Database Log Files

    - by user12620111
    I've been troubled by drop outs in CPU usage in my application server, characterized by the CPUs suddenly going from close to 90% CPU busy to almost completely CPU idle for a few seconds. Here is an example of a drop out as shown by a snippet of vmstat data taken while the application server is under a heavy workload. # vmstat 1  kthr      memory            page            disk          faults      cpu  r b w   swap  free  re  mf pi po fr de sr s3 s4 s5 s6   in   sy   cs us sy id  1 0 0 130160176 116381952 0 16 0 0 0 0  0  0  0  0  0 207377 117715 203884 70 21 9  12 0 0 130160160 116381936 0 25 0 0 0 0 0  0  0  0  0 200413 117162 197250 70 20 9  11 0 0 130160176 116381920 0 16 0 0 0 0 0  0  1  0  0 203150 119365 200249 72 21 7  8 0 0 130160176 116377808 0 19 0 0 0 0  0  0  0  0  0 169826 96144 165194 56 17 27  0 0 0 130160176 116377800 0 16 0 0 0 0  0  0  0  0  1 10245 9376 9164 2  1 97  0 0 0 130160176 116377792 0 16 0 0 0 0  0  0  0  0  2 15742 12401 14784 4 1 95  0 0 0 130160176 116377776 2 16 0 0 0 0  0  0  1  0  0 19972 17703 19612 6 2 92  14 0 0 130160176 116377696 0 16 0 0 0 0 0  0  0  0  0 202794 116793 199807 71 21 8  9 0 0 130160160 116373584 0 30 0 0 0 0  0  0 18  0  0 203123 117857 198825 69 20 11 This behavior occurred consistently while the application server was processing synthetic transactions: HTTP requests from JMeter running on an external machine. I explored many theories trying to explain the drop outs, including: Unexpected JMeter behavior Network contention Java Garbage Collection Application Server thread pool problems Connection pool problems Database transaction processing Database I/O contention Graphing the CPU %idle led to a breakthrough: Several of the drop outs were 30 seconds apart. With that insight, I went digging through the data again and looking for other outliers that were 30 seconds apart. In the database server statistics, I found spikes in the iostat "asvc_t" (average response time of disk transactions, in milliseconds) for the disk drive that was being used for the database log files. Here is an example:                     extended device statistics     r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 2053.6    0.0 8234.3  0.0  0.2    0.0    0.1   0  24 c3t60080E5...F4F6d0s0     0.0 2162.2    0.0 8652.8  0.0  0.3    0.0    0.1   0  28 c3t60080E5...F4F6d0s0     0.0 1102.5    0.0 10012.8  0.0  4.5    0.0    4.1   0  69 c3t60080E5...F4F6d0s0     0.0   74.0    0.0 7920.6  0.0 10.0    0.0  135.1   0 100 c3t60080E5...F4F6d0s0     0.0  568.7    0.0 6674.0  0.0  6.4    0.0   11.2   0  90 c3t60080E5...F4F6d0s0     0.0 1358.0    0.0 5456.0  0.0  0.6    0.0    0.4   0  55 c3t60080E5...F4F6d0s0     0.0 1314.3    0.0 5285.2  0.0  0.7    0.0    0.5   0  70 c3t60080E5...F4F6d0s0 Here is a little more information about my database configuration: The database and application server were running on two different SPARC servers. Storage for the database was on a storage array connected via 8 gigabit Fibre Channel Data storage and log file were on different physical disk drives Reliable low latency I/O is provided by battery backed NVRAM Highly available: Two Fibre Channel links accessed via MPxIO Two Mirrored cache controllers The log file physical disks were mirrored in the storage device Database log files on a ZFS Filesystem with cutting-edge technologies, such as copy-on-write and end-to-end checksumming Why would I be getting service time spikes in my high-end storage? First, I wanted to verify that the database log disk service time spikes aligned with the application server CPU drop outs, and they did: At first, I guessed that the disk service time spikes might be related to flushing the write through cache on the storage device, but I was unable to validate that theory. After searching the WWW for a while, I decided to try using a separate log device: # zpool add ZFS-db-41 log c3t60080E500017D55C000015C150A9F8A7d0 The ZFS log device is configured in a similar manner as described above: two physical disks mirrored in the storage array. This change to the database storage configuration eliminated the application server CPU drop outs: Here is the zpool configuration: # zpool status ZFS-db-41   pool: ZFS-db-41  state: ONLINE  scan: none requested config:         NAME                                     STATE         ZFS-db-41                                ONLINE           c3t60080E5...F4F6d0  ONLINE         logs           c3t60080E5...F8A7d0  ONLINE Now, the I/O spikes look like this:                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1053.5    0.0 4234.1  0.0  0.8    0.0    0.7   0  75 c3t60080E5...F8A7d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1131.8    0.0 4555.3  0.0  0.8    0.0    0.7   0  76 c3t60080E5...F8A7d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1167.6    0.0 4682.2  0.0  0.7    0.0    0.6   0  74 c3t60080E5...F8A7d0s0     0.0  162.2    0.0 19153.9  0.0  0.7    0.0    4.2   0  12 c3t60080E5...F4F6d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1247.2    0.0 4992.6  0.0  0.7    0.0    0.6   0  71 c3t60080E5...F8A7d0s0     0.0   41.0    0.0   70.0  0.0  0.1    0.0    1.6   0   2 c3t60080E5...F4F6d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1241.3    0.0 4989.3  0.0  0.8    0.0    0.6   0  75 c3t60080E5...F8A7d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1193.2    0.0 4772.9  0.0  0.7    0.0    0.6   0  71 c3t60080E5...F8A7d0s0 We can see the steady flow of 4k writes to the ZIL device from O_SYNC database log file writes. The spikes are from flushing the transaction group. Like almost all problems that I run into, once I thoroughly understand the problem, I find that other people have documented similar experiences. Thanks to all of you who have documented alternative approaches. Saved for another day: now that the problem is obvious, I should try "zfs:zfs_immediate_write_sz" as recommended in the ZFS Evil Tuning Guide. References: The ZFS Intent Log Solaris ZFS, Synchronous Writes and the ZIL Explained ZFS Evil Tuning Guide: Cache Flushes ZFS Evil Tuning Guide: Tuning ZFS for Database Performance

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  • Reading a ZFS USB drive with Mac OS X Mountain Lion

    - by Karim Berrah
    The problem: I'm using a MacBook, mainly with Solaris 11, but something with Mac OS X (ML). The only missing thing is that Mac OS X can't read my external ZFS based USB drive, where I store all my data. So, I decided to look for a solution. Possible solution: I decided to use VirtualBox with a Solaris 11 VM as a passthrough to my data. Here are the required steps: Installing a Solaris 11 VM Install VirtualBox on your Mac OS X, add the extension pack (needed for USB) Plug your ZFS based USB drive on your Mac, ignore it when asked to initialize it. Create a VM for Solaris (bridged network), and before installing it, create a USB filter (in the settings of your Vbox VM, go to Ports, then USB, then add a new USB filter from the attached device "grey usb-connector logo with green plus sign")  Install a Solaris 11 VM, boot it, and install the Guest addition check with "ifconfg -a" the IP address of your Solaris VM Creating a path to your ZFS USB drive In MacOS X, use the "Disk Utility" to unmount the USB attached drive, and unplug the USB device. Switch back to VirtualBox, select the top of the window where your Solaris 11 is running plug your ZFS USB drive, select "ignore" if Mac OS invite you to initialize the disk In the VirtualBox VM menu, go to "Devices" then "USB Devices" and select from the dropping menu your "USB device" Connection your Solaris VM to the USB drive Inside Solaris, you might now check that your device is accessible by using the "format" cli command If not, repeat previous steps Now, with root privilege, force a zpool import -f myusbdevicepoolname because this pool was created on another system check that you see your new pool with "zpool status" share your pool with NFS: share -F NFS /myusbdevicepoolname Accessing the USB ZFS drive from Mac OS X This is the easiest step: access an NFS share from mac OS Create a "ZFSdrive" folder on your MacOS desktop from a terminal under mac OS: mount -t nfs IPadressofMySoalrisVM:/myusbdevicepoolname  /Users/yourusername/Desktop/ZFSdrive et voila ! you might access your data, on a ZFS USB drive, directly from your Mountain Lion Desktop. You might play with the share rights in order to alter any read/write rights as needed. You might activate compression, encryption inside the Solaris 11 VM ...

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  • Kostenlose MySQL Seminare im Mai

    - by A&C Redaktion
    Im Mai führen wir für Sie zahlreiche MySQL Seminare mit unterschiedlichen Themenschwerpunkten durch. Vom „Skalierbarkeitstag“ über einen praxisorienterten MySQL Enterprise Workshop bis hin zum Überblick über die Hochverfügbarkeitslösungen für MySQL mit Anwendungsbeispiel aus der Praxis. Wir würden uns sehr freuen, Sie bei einem dieser Seminare begrüßen zu dürfen. Die einzelnen Termine und Anmeldungslinks finden Sie hier. Wir freuen uns auf Ihre Teilnahme!

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  • Einstieg in Solaris 11

    - by Stefan Hinker
    Fuer alle die, die jetzt mit Solaris 11 anfangen wollen, gibt es eine gute Zusammenfassung der Neuerungen und Aenderungen gegenueber Solaris 10.  Zu finden als Support Dokument 1313405.1.Auch in OTN gibt es ein ganzes Portal zu Solaris 11.  Besonders hervorheben moechte ich hier die umfangreiche "How-To" Sammlung. Und nicht zuletzt gibt es natuerlich die "ganz normalen" Admin Guides.

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  • Welcome To The Nashorn Blog

    - by jlaskey
    Welcome to all.  Time to break the ice and instantiate The Nashorn Blog.  I hope to contribute routinely, but we are very busy, at this point, preparing for the next development milestone and, of course, getting ready for open source. So, if there are long gaps between postings please forgive. We're just coming back from JavaOne and are stoked by the positive response to all the Nashorn sessions. It was great for the team to have the front and centre slide from Georges Saab early in the keynote. It seems we have support coming from all directions. Most of the session videos are posted. Check out the links. Nashorn: Optimizing JavaScript and Dynamic Language Execution on the JVM. Unfortunately, Marcus - the code generation juggernaut,  got saddled with the first session of the first day. Still, he had a decent turnout. The talk focused on issues relating to optimizations we did to get good performance from the JVM. Much yet to be done but looking good. Nashorn: JavaScript on the JVM. This was the main talk about Nashorn. I delivered the little bit of this and a little bit of that session with an overview, a follow up on the open source announcement, a run through a few of the Nashorn features and some demos. The room was SRO, about 250±. High points: Sam Pullara, from Twitter, came forward to describe how painless it was to get Mustache.js up and running (20x over Rhino), and,  John Ceccarelli, from NetBeans came forward to describe how Nashorn has become an integral part of Netbeans. A healthy Q & A at the end was very encouraging. Meet the Nashorn JavaScript Team. Michel, Attila, Marcus and myself hosted a Q & A. There was only a handful of people in the room (we assume it was because of a conflicting session ;-) .) Most of the questions centred around Node.jar, which leads me to believe, Nashorn + Node.jar is what has the most interest. Akhil, Mr. Node.jar, sitting in the audience, fielded the Node.jar questions. Nashorn, Node, and Java Persistence. Doug Clarke, Akhil and myself, discussed the title topics, followed by a lengthy Q & A (security had to hustle us out.) 80 or so in the room. Lots of questions about Node.jar. It was great to see Doug's use of Nashorn + JPA. Nashorn in action, with such elegance and grace. Putting the Metaobject Protocol to Work: Nashorn’s Java Bindings. Attila discussed how he applied Dynalink to Nashorn. Good turn out for this session as well. I have a feeling that once people discover and embrace this hidden gem, great things will happen for all languages running on the JVM. Finally, there were quite a few JavaOne sessions that focused on non-Java languages and their impact on the JVM. I've always believed that one's tool belt should carry a variety of programming languages, not just for domain/task applicability, but also to enhance your thinking and approaches to problem solving. For the most part, future blog entries will focus on 'how to' in Nashorn, but if you have any suggestions for topics you want discussed, please drop a line.  Cheers. 

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  • APEX-Berichte automatisch aktualisieren

    - by carstenczarski
    Einen Bericht auf einer Anwendungsseite in regelmäßigen Abständen zu aktualisieren, ist recht einfach: Seit APEX 4.0 muss man noch nicht einmal JavaScript-Code dafür programmieren; mit einem einfach zu nutzenden Plugin des APEX-Entwicklerteams setzt man das in kürzester Zeit um. In diesem Tipp gehen wir noch etwas weiter: Für eine Tabelle, die eine Spalte mit dem Zeitpunkt der letzten Änderung enthält, wollen wir die zuletzt geänderten Werte hervorheben, so dass man sie leichter erkennen kann.

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  • Schema Based Code Completion for NetBeans Platform Applications

    - by Geertjan
    Toni's recent blog entry provides, among several other interesting things, instructions for something I've been wanting to cover for a long time, which is schema based code completion: The above is a sample I created via Toni's tutorial, using the schema described here: http://www.w3schools.com/schema/schema_example.asp The support for the Navigator ain't bad either, especially considering I didn't do any coding at all to get all this: And here's where you can find the whole sample: http://java.net/projects/nb-api-samples/sources/api-samples/show/versions/7.2/misc/ShipOrder

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  • Data Loading Issues? Try the new Demantra Data Load Guided Resolution

    - by user702295
    Hello!   Do you have data loading issues?  Perhaps you are trying the new partial schema export tool.   New to Demantra, the Data Load Guided Resolution, document 1461899.1.  This interactive guide will help you locate known solutions to previously discovered issues quickly.  From performance, ORA and ODPM errors to collections related issues that have no known hard number error.   This guide includes the diagnosis of data being imported into Demantra and data being exported from Demantra.  Contact me with any questions or suggestions.   Thank You!

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  • Geronimo 3 beta - Another Apache project now compatible with Java EE 6

    - by alexismp
    You probably recall the addition of TomEE and WebSphere CE at JavaOne 2011 to the list of certified Java EE 6 products. This time, Apache Geronimo 3 beta 1 was released with compatibility with the Java EE 6 full platform and is now listed on the Java EE Compatibility Page in both the Web Profile and Full Platform categories. Not surprisingly, a good number of the components used in this Geronimo release are similar to those used in the TomEE certification. We now have 11 compatible Java EE 6 configurations to chose from and expecting more soon.

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  • Jersey 1.8 - Another GlassFish 3.1.1 component is ready

    - by alexismp
    We now have a new release of the JAX-RS 1.1 reference implementation - Jersey 1.8 is just out! Thisbug-fix release follows the EclipseLink 2.3 release from last week (as part of the Eclipse Indigo train release) and other components such as Woodstox 4.1.1 and Weld 1.1.1 which have already been released and integrated. To get started with Jersey 1.8, begin here and don't forget to visit the Jersey Wiki pages. You can also grab a nightly build of GlassFish 3.1.1 or wait for the next promoted build (#10) due out in a few days. As it currently stands for GlassFish 3.1.1, we have integration of the final bits for Metro 2.1.1 (currently at 2.1.1b7), Mojarra 2.1.3 (currently at 2.1.3b1), and MQ 4.5.1 (currently at 4.5.1b3) still ahead of us.

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  • It could be worse....

    - by Darryl Gove
    As "guest" pointed out, in my file I/O test I didn't open the file with O_SYNC, so in fact the time was spent in OS code rather than in disk I/O. It's a straightforward change to add O_SYNC to the open() call, but it's also useful to reduce the iteration count - since the cost per write is much higher: ... #define SIZE 1024 void test_write() { starttime(); int file = open("./test.dat",O_WRONLY|O_CREAT|O_SYNC,S_IWGRP|S_IWOTH|S_IWUSR); ... Running this gave the following results: Time per iteration 0.000065606310 MB/s Time per iteration 2.709711563906 MB/s Time per iteration 0.178590114758 MB/s Yup, disk I/O is way slower than the original I/O calls. However, it's not a very fair comparison since disks get written in large blocks of data and we're deliberately sending a single byte. A fairer result would be to look at the I/O operations per second; which is about 65 - pretty much what I'd expect for this system. It's also interesting to examine at the profiles for the two cases. When the write() was trapping into the OS the profile indicated that all the time was being spent in system. When the data was being written to disk, the time got attributed to sleep. This gives us an indication how to interpret profiles from apps doing I/O. It's the sleep time that indicates disk activity.

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  • SOA Composite Sensors : Good Practice

    - by angelo.santagata
    I was discussing a interesting design problem with a colleague of mine Niall (his blog) on the topic of how to cancel an inflight SOA Composite process.  Obviously one way to do this is to cancel the process from enterprise Manager ( http://hostort/em ) , however we were thinking this isnt a “user friendly” way of doing this.. If you look at Nialls blog you’ll see he’s highlighted a number of different APIs which enable you the ability to manipulate the SCA instance, e.g. Code Snippet to purge (delete) an instance How to determine the instanceId from a composite_sensor_value using the “composite_sensor_value” table How to determine a BPEL Process status using the cube_instance table   Now all of these require that you know the instanceId of your SOA Composite, how does one find this out? Well the easiest way of doing this is to create a composite sensor on the SCA component. A composite sensor is simply a way of publishing a piece of business data as part of your composite. The magic here is that you can later query composites based on this value. So a good best practice is that for any composites you create consider publishing a composite sensor value using a primary key of some sort , e.g. orderId, that way if you need to manipulate/query composites you can easily look up the instanceId using the sensorid.   For information on how to create a composite Sensor id see this documentation link  

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  • Getting Started with Amazon Web Services in NetBeans IDE

    - by Geertjan
    When you need to connect to Amazon Web Services, NetBeans IDE gives you a nice start. You can drag and drop the "itemSearch" service into a Java source file and then various Amazon files are generated for you. From there, you need to do a little bit of work because the request to Amazon needs to be signed before it can be used. Here are some references and places that got me started: http://associates-amazon.s3.amazonaws.com/signed-requests/helper/index.html http://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSGettingStartedGuide/AWSCredentials.html https://affiliate-program.amazon.com/gp/flex/advertising/api/sign-in.html You definitely need to sign up to the Amazon Associates program and also register/create an Access Key ID, which will also get you a Secret Key, as well. Here's a simple Main class that I created that hooks into the generated RestConnection/RestResponse code created by NetBeans IDE: public static void main(String[] args) {    try {        String searchIndex = "Books";        String keywords = "Romeo and Juliet";        RestResponse result = AmazonAssociatesService.itemSearch(searchIndex, keywords);        String dataAsString = result.getDataAsString();        int start = dataAsString.indexOf("<Author>")+8;        int end = dataAsString.indexOf("</Author>");        System.out.println(dataAsString.substring(start,end));    } catch (Exception ex) {        ex.printStackTrace();    }} Then I deleted the generated properties file and the authenticator and changed the generated AmazonAssociatesService.java file to the following: public class AmazonAssociatesService {    private static void sleep(long millis) {        try {            Thread.sleep(millis);        } catch (Throwable th) {        }    }    public static RestResponse itemSearch(String searchIndex, String keywords) throws IOException {        SignedRequestsHelper helper;        RestConnection conn = null;        Map queryMap = new HashMap();        queryMap.put("Service", "AWSECommerceService");        queryMap.put("AssociateTag", "myAssociateTag");        queryMap.put("AWSAccessKeyId", "myAccessKeyId");        queryMap.put("Operation", "ItemSearch");        queryMap.put("SearchIndex", searchIndex);        queryMap.put("Keywords", keywords);        try {            helper = SignedRequestsHelper.getInstance(                    "ecs.amazonaws.com",                    "myAccessKeyId",                    "mySecretKey");            String sign = helper.sign(queryMap);            conn = new RestConnection(sign);        } catch (IllegalArgumentException | UnsupportedEncodingException | NoSuchAlgorithmException | InvalidKeyException ex) {        }        sleep(1000);        return conn.get(null);    }} Finally, I copied this class into my application, which you can see is referred to above: http://code.google.com/p/amazon-product-advertising-api-sample/source/browse/src/com/amazon/advertising/api/sample/SignedRequestsHelper.java Here's the completed app, mostly generated via the drag/drop shown at the start, but slightly edited as shown above: That's all, now everything works as you'd expect.

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  • Running Built-In Test Simulator with SOA Suite Healthcare 11g in PS4 and PS5

    - by Shub Lahiri, A-Team
    Background SOA Suite for Healthcare Integration pack comes with a pre-installed simulator that can be used as an external endpoint to generate inbound and outbound HL7 traffic on specified MLLP ports. This is a command-line utility that can be very handy when trying to build a complete end-to-end demo within a standalone, closed environment. The ant-based utility accepts the name of a configuration file as the command-line input argument. The format of this configuration file has changed between PS4 and PS5. In PS4, the configuration file was XML based and in PS5, it is name-value property based. The rest of this note highlights these differences and provides samples that can be used to run the first scenario from the product samples set. PS4 - Configuration File The sample configuration file for PS4 is shown below. The configuration file contains information about the following items: Directory for incoming and outgoing files for the host running SOA Suite Healthcare Polling Interval for the directory External Endpoint Logical Names External Endpoint Server Host Name and Ports Message throughput to be simulated for generating outbound messages Documents to be handled by different endpoints A copy of this file can be downloaded from here. PS5 - Configuration File The corresponding sample configuration file for PS5 is shown below. The configuration file contains similar information about the sample scenario but is not in XML format. It has name-value pairs specified in the form of a properties file. This sample file can be downloaded from here. Simulator Configuration Before running the simulator, the environment has to be set by defining the proper ANT_HOME and JAVA_HOME. The following extract is taken from a working sample shell script to set the environment: Also, as a part of setting the environment, template jndi.properties and logging.properties can be generated by using the following ant command: ant -f ant-b2bsimulator-util.xml b2bsimulator-prop Sample jndi.properties and logging.properties are shown below and can be modified, as needed. The jndi.properties contains information about connectivity to the local Weblogic Managed Server instance and the logging.properties file controls the amount of logging that can be generated from the running simulator process. Simulator Usage - Start and Stop The command syntax to launch the simulator via ant is the same in PS4 and PS5. Only the appropriate configuration file has to be supplied as the command-line argument, for example: ant -f ant-b2bsimulator-util.xml b2bsimulatorstart -Dargs="simulator1.hl7-config.xml" This will start the simulator and will keep running to provide an active external endpoint for SOA Healthcare Integration engine. To stop the simulator, a similar ant command can be used, for example: ant -f ant-b2bsimulator-util.xml b2bsimulatorstop

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  • Updates to the Demantra Partial Schema Exporter Tool, Patch 13930627, are Available.

    - by user702295
    Hello!  Updates to the Demantra Partial Schema Exporter Tool, Patch 13930627, are Available. This is an updated re-release of the generic Partial Schema Exporter Tool.  The generic patch is for 7.3.1.x and 12.2.x. TABLE_REORG was introduced in 7.3.1.3 12.2.0.  Therefore for 7.3.1.x the schema must be at 7.3.1.3 or above. This is build 3 of the patch. It contains fixes for the following bugs - BUG 17495971 - DEMANTRA 12.2 - CUMULATIVE HISTORY NOT CORRECT   It now only uses DATA_PUMP COMPRESSION only on Enterprise Edition for 11g and and up. - Bug 17452153 - 1OFF:16086475:TRYING TO FILTER DROP DOWN IN A METHOD CALL USING MORE THAN 1 ATTR   It now builds GL level filters with and without the GL id column where applicable. These bugs are also fixed in 7.3.1.6 and 12.2.3.

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