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  • How-to dynamically filter model-driven LOV

    - by Frank Nimphius
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Often developers need to filter a LOV query with information obtained from an ADF Faces form or other where. The sample below shows how to define a launch popup listener configured on the launchPopupListener property of the af:inputListOfValues component to filter a list of values. <af:inputListOfValues id="departmentIdId"    value="#{bindings.DepartmentId.inputValue}"                                          model="#{bindings.DepartmentId.listOfValuesModel}"    launchPopupListener="#{PopupLauncher.onPopupLaunch}" … >         … </af:inputListOfValues> A list of values is queried using a search binding that gets created in the PageDef file of a view when a lis of value component gets added. The managed bean code below looks this search binding up to then add a view criteria that filters the query. Note: There is no public API yet available for the FacesCtrlLOVBinding class, which is why I use the internal package class it in the example. public void onPopupLaunch(LaunchPopupEvent launchPopupEvent) {   BindingContext bctx = BindingContext.getCurrent();   BindingContainer bindings = bctx.getCurrentBindingsEntry();   FacesCtrlLOVBinding lov =        (FacesCtrlLOVBinding)bindings.get("DepartmentId");   ViewCriteriaManager vcm =   lov.getListIterBinding().getViewObject().getViewCriteriaManager();             //make sure the view criteria is cleared   vcm.removeViewCriteria(vcm.DFLT_VIEW_CRITERIA_NAME);   //create a new view criteria   ViewCriteria vc =          new ViewCriteria(lov.getListIterBinding().getViewObject());   //use the default view criteria name   //"__DefaultViewCriteria__"   vc.setName(vcm.DFLT_VIEW_CRITERIA_NAME);   //create a view criteria row for all queryable attributes   ViewCriteriaRow vcr = new ViewCriteriaRow(vc);   //for this sample I set the query filter to DepartmentId 60.   //You may determine it at runtime by reading it from a managed bean   //or binding layer   vcr.setAttribute("DepartmentId", 60);   //also note that the view criteria row consists of all attributes   //that belong to the LOV list view object, which means that you can   //filter on multiple attributes   vc.addRow(vcr);             lov.getListIterBinding().getViewObject().applyViewCriteria(vc); }  Note: Instead of using the vcm.DFLT_VIEW_CRITERIA_NAME name you can also define a custom name for the view criteria.

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  • MySQL Cluster 7.2: Over 8x Higher Performance than Cluster 7.1

    - by Mat Keep
    0 0 1 893 5092 Homework 42 11 5974 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary The scalability enhancements delivered by extensions to multi-threaded data nodes enables MySQL Cluster 7.2 to deliver over 8x higher performance than the previous MySQL Cluster 7.1 release on a recent benchmark What’s New in MySQL Cluster 7.2 MySQL Cluster 7.2 was released as GA (Generally Available) in February 2012, delivering many enhancements to performance on complex queries, new NoSQL Key / Value API, cross-data center replication and ease-of-use. These enhancements are summarized in the Figure below, and detailed in the MySQL Cluster New Features whitepaper Figure 1: Next Generation Web Services, Cross Data Center Replication and Ease-of-Use Once of the key enhancements delivered in MySQL Cluster 7.2 is extensions made to the multi-threading processes of the data nodes. Multi-Threaded Data Node Extensions The MySQL Cluster 7.2 data node is now functionally divided into seven thread types: 1) Local Data Manager threads (ldm). Note – these are sometimes also called LQH threads. 2) Transaction Coordinator threads (tc) 3) Asynchronous Replication threads (rep) 4) Schema Management threads (main) 5) Network receiver threads (recv) 6) Network send threads (send) 7) IO threads Each of these thread types are discussed in more detail below. MySQL Cluster 7.2 increases the maximum number of LDM threads from 4 to 16. The LDM contains the actual data, which means that when using 16 threads the data is more heavily partitioned (this is automatic in MySQL Cluster). Each LDM thread maintains its own set of data partitions, index partitions and REDO log. The number of LDM partitions per data node is not dynamically configurable, but it is possible, however, to map more than one partition onto each LDM thread, providing flexibility in modifying the number of LDM threads. The TC domain stores the state of in-flight transactions. This means that every new transaction can easily be assigned to a new TC thread. Testing has shown that in most cases 1 TC thread per 2 LDM threads is sufficient, and in many cases even 1 TC thread per 4 LDM threads is also acceptable. Testing also demonstrated that in some instances where the workload needed to sustain very high update loads it is necessary to configure 3 to 4 TC threads per 4 LDM threads. In the previous MySQL Cluster 7.1 release, only one TC thread was available. This limit has been increased to 16 TC threads in MySQL Cluster 7.2. The TC domain also manages the Adaptive Query Localization functionality introduced in MySQL Cluster 7.2 that significantly enhanced complex query performance by pushing JOIN operations down to the data nodes. Asynchronous Replication was separated into its own thread with the release of MySQL Cluster 7.1, and has not been modified in the latest 7.2 release. To scale the number of TC threads, it was necessary to separate the Schema Management domain from the TC domain. The schema management thread has little load, so is implemented with a single thread. The Network receiver domain was bound to 1 thread in MySQL Cluster 7.1. With the increase of threads in MySQL Cluster 7.2 it is also necessary to increase the number of recv threads to 8. This enables each receive thread to service one or more sockets used to communicate with other nodes the Cluster. The Network send thread is a new thread type introduced in MySQL Cluster 7.2. Previously other threads handled the sending operations themselves, which can provide for lower latency. To achieve highest throughput however, it has been necessary to create dedicated send threads, of which 8 can be configured. It is still possible to configure MySQL Cluster 7.2 to a legacy mode that does not use any of the send threads – useful for those workloads that are most sensitive to latency. The IO Thread is the final thread type and there have been no changes to this domain in MySQL Cluster 7.2. Multiple IO threads were already available, which could be configured to either one thread per open file, or to a fixed number of IO threads that handle the IO traffic. Except when using compression on disk, the IO threads typically have a very light load. Benchmarking the Scalability Enhancements The scalability enhancements discussed above have made it possible to scale CPU usage of each data node to more than 5x of that possible in MySQL Cluster 7.1. In addition, a number of bottlenecks have been removed, making it possible to scale data node performance by even more than 5x. Figure 2: MySQL Cluster 7.2 Delivers 8.4x Higher Performance than 7.1 The flexAsynch benchmark was used to compare MySQL Cluster 7.2 performance to 7.1 across an 8-node Intel Xeon x5670-based cluster of dual socket commodity servers (6 cores each). As the results demonstrate, MySQL Cluster 7.2 delivers over 8x higher performance per data nodes than MySQL Cluster 7.1. More details of this and other benchmarks will be published in a new whitepaper – coming soon, so stay tuned! In a following blog post, I’ll provide recommendations on optimum thread configurations for different types of server processor. You can also learn more from the Best Practices Guide to Optimizing Performance of MySQL Cluster Conclusion MySQL Cluster has achieved a range of impressive benchmark results, and set in context with the previous 7.1 release, is able to deliver over 8x higher performance per node. As a result, the multi-threaded data node extensions not only serve to increase performance of MySQL Cluster, they also enable users to achieve significantly improved levels of utilization from current and future generations of massively multi-core, multi-thread processor designs.

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  • PHP oci8 dll not loading on windows 64 bit XP. What am I doing wrong?

    - by user47354
    on win 64, I installed apache, php etc. Everything works fine, except the oracle part. I can connect to oracle from sql developer which means my tnsnames.ora file is correct. When apache starts, there are no errors in the logs. But when I try to connect to oracle from my database, oracle module php_oci8.dll is not loaded. What am I doing wrong? The oci8.dll line in php.ini is there, it is uncommented There are no errors in the apache logs extension_dir in php.ini file points to the correct location

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  • FairScheduling Conventions in Hadoop

    - by dan.mcclary
    While scheduling and resource allocation control has been present in Hadoop since 0.20, a lot of people haven't discovered or utilized it in their initial investigations of the Hadoop ecosystem. We could chalk this up to many things: Organizations are still determining what their dataflow and analysis workloads will comprise Small deployments under tests aren't likely to show the signs of strains that would send someone looking for resource allocation options The default scheduling options -- the FairScheduler and the CapacityScheduler -- are not placed in the most prominent position within the Hadoop documentation. However, for production deployments, it's wise to start with at least the foundations of scheduling in place so that you can tune the cluster as workloads emerge. To do that, we have to ask ourselves something about what the off-the-rack scheduling options are. We have some choices: The FairScheduler, which will work to ensure resource allocations are enforced on a per-job basis. The CapacityScheduler, which will ensure resource allocations are enforced on a per-queue basis. Writing your own implementation of the abstract class org.apache.hadoop.mapred.job.TaskScheduler is an option, but usually overkill. If you're going to have several concurrent users and leverage the more interactive aspects of the Hadoop environment (e.g. Pig and Hive scripting), the FairScheduler is definitely the way to go. In particular, we can do user-specific pools so that default users get their fair share, and specific users are given the resources their workloads require. To enable fair scheduling, we're going to need to do a couple of things. First, we need to tell the JobTracker that we want to use scheduling and where we're going to be defining our allocations. We do this by adding the following to the mapred-site.xml file in HADOOP_HOME/conf: <property> <name>mapred.jobtracker.taskScheduler</name> <value>org.apache.hadoop.mapred.FairScheduler</value> </property> <property> <name>mapred.fairscheduler.allocation.file</name> <value>/path/to/allocations.xml</value> </property> <property> <name>mapred.fairscheduler.poolnameproperty</name> <value>pool.name</value> </property> <property> <name>pool.name</name> <value>${user.name}</name> </property> What we've done here is simply tell the JobTracker that we'd like to task scheduling to use the FairScheduler class rather than a single FIFO queue. Moreover, we're going to be defining our resource pools and allocations in a file called allocations.xml For reference, the allocation file is read every 15s or so, which allows for tuning allocations without having to take down the JobTracker. Our allocation file is now going to look a little like this <?xml version="1.0"?> <allocations> <pool name="dan"> <minMaps>5</minMaps> <minReduces>5</minReduces> <maxMaps>25</maxMaps> <maxReduces>25</maxReduces> <minSharePreemptionTimeout>300</minSharePreemptionTimeout> </pool> <mapreduce.job.user.name="dan"> <maxRunningJobs>6</maxRunningJobs> </user> <userMaxJobsDefault>3</userMaxJobsDefault> <fairSharePreemptionTimeout>600</fairSharePreemptionTimeout> </allocations> In this case, I've explicitly set my username to have upper and lower bounds on the maps and reduces, and allotted myself double the number of running jobs. Now, if I run hive or pig jobs from either the console or via the Hue web interface, I'll be treated "fairly" by the JobTracker. There's a lot more tweaking that can be done to the allocations file, so it's best to dig down into the description and start trying out allocations that might fit your workload.

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  • ArchBeat Link-o-Rama for 2012-03-28

    - by Bob Rhubart
    Beware the 'Facebook Effect' when service-orienting information technology | Joe McKenrick www.zdnet.com Experiences seen with Facebook provide a fair warning to shared-service providers in enterprises. Cookbook: SES and UCM setup | George Maggessy blogs.oracle.com WebCenter A-Team member George Maggessy guides you through setting up the integration between UCM and SES. Using Oracle VM with Amazon EC2 | Marc Fielding www.pythian.com "If you’re planning on running Oracle VM with Amazon EC2, there are some important limitations you should know about," says Pythian's Marc Fielding. Oracle Enterprise Pack for Eclipse 12.1.1 update on OTN blogs.oracle.com Oracle Enterprise Pack for Eclipse (OEPE) 12.1.1.0.1 was released to OTN last week with support for new standards and several new features. Thought for the Day "If the mind really is the finest computer, then there are a lot of people out there who need to be rebooted." — Tim Bryce

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  • obiee memory usage

    - by user554629
    Heap memory is a frequent customer topic. Here's the quick refresher, oriented towards AIX, but the principles apply to other unix implementations. 1. 32-bit processes have a maximum addressability of 4GB; usable application heap size of 2-3 GB.  On AIX it is controlled by an environment variable: export LDR_CNTRL=....=MAXDATA=0x080000000   # 2GB ( The leading zero is deliberate, not required )   1a. It is  possible to get 3.25GB  heap size for a 32-bit process using @DSA (Discontiguous Segment Allocation)     export LDR_CNTRL=MAXDATA=0xd0000000@DSA  # 3.25 GB 32-bit only        One side-effect of using AIX segments "c" and "d" is that shared libraries will be loaded privately, and not shared.        If you need the additional heap space, this is worth the trade-off.  This option is frequently used for 32-bit java.   1b. 64-bit processes have no need for the @DSA option. 2. 64-bit processes can double the 32-bit heap size to 4GB using: export LDR_CNTRL=....=MAXDATA=0x100000000  # 1 with 8-zeros    2a. But this setting would place the same memory limitations on obiee as a 32-bit process    2b. The major benefit of 64-bit is to break the binds of 32-bit addressing.  At a minimum, use 8GB export LDR_CNTRL=....=MAXDATA=0x200000000  # 2 with 8-zeros    2c.  Many large customers are providing extra safety to their servers by using 16GB: export LDR_CNTRL=....=MAXDATA=0x400000000  # 4 with 8-zeros There is no performance penalty for providing virtual memory allocations larger than required by the application.  - If the server only uses 2GB of space in 64-bit ... specifying 16GB just provides an upper bound cushion.    When an unexpected user query causes a sudden memory surge, the extra memory keeps the server running. 3.  The next benefit to 64-bit is that you can provide huge thread stack sizes for      strange queries that might otherwise crash the server.      nqsserver uses fast recursive algorithms to traverse complicated control structures.    This means lots of thread space to hold the stack frames.    3a. Stack frames mostly contain register values;  64-bit registers are twice as large as 32-bit          At a minimum you should  quadruple the size of the server stack threads in NQSConfig.INI          when migrating from 32- to 64-bit, to prevent a rogue query from crashing the server.           Allocate more than is normally necessary for safety.    3b. There is no penalty for allocating more stack size than you need ...           it is just virtual memory;   no real resources  are consumed until the extra space is needed.    3c. Increasing thread stack sizes may require the process heap size (MAXDATA) to be increased.          Heap space is used for dynamic memory requests, and for thread stacks.          No performance penalty to run with large heap and thread stack sizes.           In a 32-bit world, this safety would require careful planning to avoid exceeding 2GM usable storage.     3d. Increasing the number of threads also may require additional heap storage.          Most thread stack frames on obiee are allocated when the server is started,          and the real memory usage increases as threads run work. Does 2.8GB sound like a lot of memory for an AIX application server? - I guess it is what you are accustomed to seeing from "grandpa's applications". - One of the primary design goals of obiee is to trade memory for services ( db, query caches, etc) - 2.8GB is still well under the 4GB heap size allocated with MAXDATA=0x100000000 - 2.8GB process size is also possible even on 32-bit Windows applications - It is not unusual to receive a sudden request for 30MB of contiguous storage on obiee.- This is not a memory leak;  eventually the nqsserver storage will stabilize, but it may take days to do so. vmstat is the tool of choice to observe memory usage.  On AIX vmstat will show  something that may be  startling to some people ... that available free memory ( the 2nd column ) is always  trending toward zero ... no available free memory.  Some customers have concluded that "nearly zero memory free" means it is time to upgrade the server with more real memory.   After the upgrade, the server again shows very little free memory available. Should you be concerned about this?   Many customers are !!  Here is what is happening: - AIX filesystems are built on a paging model.   If you read/write a  filesystem block it is paged into memory ( no read/write system calls ) - This filesystem "page" has its own "backing store" on disk, the original filesystem block.   When the system needs the real memory page holding the file block, there is no need to "page out".    The page can be stolen immediately, because the original is still on disk in the filesystem. - The filesystem  pages tend to collect ... every filesystem block that was ever seen since    system boot is available in memory.  If another application needs the file block, it is retrieved with no physical I/O. What happens if the system does need the memory ... to satisfy a 30MB heap request by nqsserver, for example? - Since the filesystem blocks have their own backing store ( not on a paging device )   the kernel can just steal any filesystem block ... on a least-recently-used basis   to satisfy a new real memory request for "computation pages". No cause for alarm.   vmstat is accurately displaying whether all filesystem blocks have been touched, and now reside in memory.   Back to nqsserver:  when should you be worried about its memory footprint? Answer:  Almost never.   Stop monitoring it ... stop fussing over it ... stop trying to optimize it. This is a production application, and nqsserver uses the memory it requires to accomplish the job, based on demand. C'mon ... never worry?   I'm from New York ... worry is what we do best. Ok, here is the metric you should be watching, using vmstat: - Are you paging ... there are several columns of vmstat outputbash-2.04$ vmstat 3 3 System configuration: lcpu=4 mem=4096MB kthr    memory              page              faults        cpu    ----- ------------ ------------------------ ------------ -----------  r  b    avm   fre  re  pi  po  fr   sr  cy  in   sy  cs us sy id wa  0  0 208492  2600   0   0   0   0    0   0  13   45  73  0  0 99  0  0  0 208492  2600   0   0   0   0    0   0   9   12  77  0  0 99  0  0  0 208492  2600   0   0   0   0    0   0   9   40  86  0  0 99  0 avm is the "available free memory" indicator that trends toward zerore   is "re-page".  The kernel steals a real memory page for one process;  immediately repages back to original processpi  "page in".   A process memory page previously paged out, now paged back in because the process needs itpo "page out" A process memory block was paged out, because it was needed by some other process Light paging activity ( re, pi, po ) is not a concern for worry.   Processes get started, need some memory, go away. Sustained paging activity  is cause for concern.   obiee users are having a terrible day if these counters are always changing. Hang on ... if nqsserver needs that memory and I reduce MAXDATA to keep the process under control, won't the nqsserver process crash when the memory is needed? Yes it will.   It means that nqsserver is configured to require too much memory and there are  lots of options to reduce the real memory requirement.  - number of threads  - size of query cache  - size of sort But I need nqsserver to keep running. Real memory is over-committed.    Many things can cause this:- running all application processes on a single server    ... DB server, web servers, WebLogic/WebSphere, sawserver, nqsserver, etc.   You could move some of those to another host machine and communicate over the network  The need for real memory doesn't go away, it's just distributed to other host machines. - AIX LPAR is configured with too little memory.     The AIX admin needs to provide more real memory to the LPAR running obiee. - More memory to this LPAR affects other partitions. Then it's time to visit your friendly IBM rep and buy more memory.

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  • OWSM Policy Repository in JDeveloper - Tips & Tricks - 11g

    - by Prakash Yamuna
    In this blog post I discussed about the OWSM Policy Repository that is embedded in JDeveloper. However some times people may run into issues with the embedded repository. Here is screen snapshot that shows the error you may run into (click on the image for larger image): If you run into "java.lang.IllegalArgumentException: WSM-04694 : An invalid directory was provided to connect to a file-base MDS repository." this caused due to spaces in the folder name. Here is a quick way to workaround this issue by running "Jdeveloper.exe - su". Hope people find this useful!

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  • File sharing for small, distributed, non-technical, non-profit organization?

    - by mnmldave
    Problem: I've started volunteering for a small non-profit with fewer than five non-technical Windows users who need to share 20-30GB of files (Office documents, images, PDFs, etc.) amongst themselves online. Background: The users are accustomed to a Windows network share on a machine that backed up their data locally. An on-site "disaster" has forced them to work from their homes for awhile and to re-evaluate their file sharing needs (office was located in an old building with obvious electrical issues, etc.). Access to time from volunteers with IT experience seems to be difficult. Demonstrably minimizing energy consumption is a nice-to-have. I'm currently considering Jungle Disk (a Desktop account shared amongst the handful of employees since their TOS and my inquiries to their helpdesk seem to indicate this is permissible). It appears easy-to-use, inexpensive, secure, has backup functionality, and can scale to accomodate more data when needed. I've not used it myself though (have only used Dropbox for personal use) and systems isn't my area of expertise, so am worried I might be jumping on a bandwagon. That said, any suggestions, thoughts or similar experiences would be really appreciated.

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  • Future Tech Duke

    - by Tori Wieldt
    Do you like the new Duke? Have you gotten the new Duke screensaver yet? Follow @java or Like I <3 Java on Facebook and get the latest 3D, animated "Future Tech Duke" screensaver.   If you haven't already, register now to watch the global July 7 Java 7 community celebration and learn more about Java moving forward. We are looking for questions from the community to be asked during the panel Q & A. Enter your questions as a comment here, or tweet it with #java7. There's lots of great content being created for Java 7: technical articles, videos, updated web pages (can you say "layer cake?"), T-shirts, presentations, and there will be lots of Java 7 content in the new Java Magazine. See you at the Java 7 celebration event! Duke will be there!

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  • ODI 11g - Scripting a Reverse Engineer

    - by David Allan
    A common question is related to how to script the reverse engineer using the ODI SDK. This follows on from some of my posts on scripting in general and accelerated model and topology setup. Check out this viewlet here to see how to define a reverse engineering process using ODI's package. Using the ODI SDK, you can script this up using the OdiPackage and StepOdiCommand classes as follows;  OdiPackage pkg = new OdiPackage(folder, "Pkg_Rev"+modName);   StepOdiCommand step1 = new StepOdiCommand(pkg,"step1_cmd_reset");   step1.setCommandExpression(new Expression("OdiReverseResetTable \"-MODEL="+mod.getModelId()+"\"",null, Expression.SqlGroupType.NONE));   StepOdiCommand step2 = new StepOdiCommand(pkg,"step2_cmd_reset");   step2.setCommandExpression(new Expression("OdiReverseGetMetaData \"-MODEL="+mod.getModelId()+"\"",null, Expression.SqlGroupType.NONE));   StepOdiCommand step3 = new StepOdiCommand(pkg,"step3_cmd_reset");   step3.setCommandExpression(new Expression("OdiReverseSetMetaData \"-MODEL="+mod.getModelId()+"\"",null, Expression.SqlGroupType.NONE));   pkg.setFirstStep(step1);   step1.setNextStepAfterSuccess(step2);   step2.setNextStepAfterSuccess(step3); The biggest leap of faith for users is getting to know which SDK classes have to be used to build the objects in the design, using StepOdiCommand isn't necessarily obvious, once you see it in action though it is very simple to use. The above snippet uses an OdiModel variable named mod, its a snippet I added to the accelerated model creation script in the post linked above.

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  • Gilda Garretón, a Java Developer and Parallelism Computing Researcher

    - by Yolande
    In a new interview titled “Gilda Garretón, a Java Developer and Parallelism Computing Research,” Garretón shares her first-hand experience developing with Java and Java 7 for very large-scale integration (VLSI) of computer-aided design (CAD). Garretón gives an insightful overview of how Java is contributing to the parallelism development and to the Electric VLSI Design Systems, an open source VLSI CAD application used as a research platform for new CAD algorithms as well as the research flow for hardware test chips.  Garretón considers that parallelism programming is hard and complex, yet important developments are taking place.  "With the addition of the concurrent package in Java SE 6 and the Fork/Join feature in Java SE 7, developers have a chance to rely more on existing frameworks and dedicate more time to the essence of their parallel algorithms." Read the full article here  

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  • Database Web Service using Toplink DB Provider

    - by Vishal Jain
    With JDeveloper 11gR2 you can now create database based web services using JAX-WS Provider. The key differences between this and the already existing PL/SQL Web Services support is:Based on JAX-WS ProviderSupports SQL Queries for creating Web ServicesSupports Table CRUD OperationsThis is present as a new option in the New Gallery under 'Web Services'When you invoke the New Gallery option, it present you with three options to choose from:In this entry I will explain the options of creating service based on SQL queries and Table CRUD operations.SQL Query based Service When you select this option, on 'Next' page it asks you for the DB Conn details. You can also choose if you want SOAP 1.1 or 1.2 format. For this example, I will proceed with SOAP 1.1, the default option.On the Next page, you can give the SQL query. The wizard support Bind Variables, so you can parametrize your queries. Give "?" as a input parameter you want to give at runtime, and the "Bind Variables" button will get enabled. Here you can specify the name and type of the variable.Finish the wizard. Now you can test your service in Analyzer:See that the bind variable specified comes as a input parameter in the Analyzer Input Form:CRUD OperationsFor this, At Step 2 of Wizard, select the radio button "Generate Table CRUD Service Provider"At the next step, select the DB Connection and the table for which you want to generate the default set of operations:Finish the Wizard. Now, run the service in Analyzer for a quick check.See that all the basic operations are exposed:

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  • “Big Data” Is A Small Concept Unless You Can Apply It To The Customer Experience

    - by Michael Hylton
    There’s been a lot of recent talk in the industry about “big data”.  Much can be said about the importance of big data and the results from it, but you need to always consider the customer experience when analyzing and applying customer data. Personalization and merchandising drive the user experience.  Big data should enable you to gain valuable insight into each of your customers and apply that insight at the moment they are on your Web site, talking to one of your call center agents, or any other touchpoint.  While past customer experience is important, you need to combine that with what your customer is doing on your Web site now as well what they are doing and saying on social networking sites.  It’s key to have a 360 degree view of your customer across all of your touchpoints in order to provide that relevant and consistent experience that they come to expect when interacting with your brand. Big data can enable you to effectively market, merchandize, and recommend the right products to the right customers and the right time.  By taking customer data and applying it to product recommendations, you have an opportunity to gain a greater share of wallet through the cross-selling and up-selling of additional products and services.  You can also build sustaining loyalty programs to continue to engage with your customers throughout their long-term relationship with your brand.

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  • “Big Data” Is A Small Concept Unless You Can Apply It To The Customer Experience

    - by Michael Hylton
    There’s been a lot of recent talk in the industry about “big data”.  Much can be said about the importance of big data and the results from it, but you need to always consider the customer experience when analyzing and applying customer data. Personalization and merchandising drive the user experience.  Big data should enable you to gain valuable insight into each of your customers and apply that insight at the moment they are on your Web site, talking to one of your call center agents, or any other touchpoint.  While past customer experience is important, you need to combine that with what your customer is doing on your Web site now as well what they are doing and saying on social networking sites.  It’s key to have a 360 degree view of your customer across all of your touchpoints in order to provide that relevant and consistent experience that they come to expect when interacting with your brand. Big data can enable you to effectively market, merchandize, and recommend the right products to the right customers and the right time.  By taking customer data and applying it to product recommendations, you have an opportunity to gain a greater share of wallet through the cross-selling and up-selling of additional products and services.  You can also build sustaining loyalty programs to continue to engage with your customers throughout their long-term relationship with your brand.

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  • SaaS Customer Service Matters

    - by charles.knapp
    You probably know that Oracle CRM On Demand goes beyond contact and transaction tracking by providing valuable real-time insights. Do you know that Oracle CRM On Demand also delivers valuable service to our customers? Don't take my word for it. "Prior to Oracle CRM On Demand, we were too busy looking in the rear view mirror on our sales activities and needed a forward-looking tool to maximize sales and coaching opportunities," said Christian Doelle, Vice President Sales & Marketing, MonierLifetile. "After evaluating other organization's solutions, we found Oracle as the most proven with the real-time reporting and detailed reviews of sales opportunities that helped us to address our blind spots. Additionally, we have found throughout our implementation phase that Oracle's commitment to customer attention and service is incomparable." Learn more here about MonierLifetile's experience with Oracle CRM On Demand.

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  • MySQL Connect Conference: My Experience

    - by Hema Sridharan
    It was a great experience to attend the MySQL Connect Conference for the first time ever. Personally I was very much enthralled to present about "How to make MySQL Backups" besides attending different sessions to absorb more knowledge about the technical prospects of MySQL. One of the agenda items in my presentation was "MySQL Enterprise Backup" functionality and features. There were total of 40 attendees in the session, who were very much interested about the MySQL Enterprise Backup product and gave positive feedback as well as areas of improvements on our product. Some of our features brought lot of excitement and smile amongst our customers including,1. Performance improvements in MEB 3.8.02. Incremental Base option from MEB 3.7.1 where there is no need to specify the directory name of the previous backup to fetch the lsn values and instead can directly fetch from backup_history table using --incremental-base=history: last_backup3. only-innodb-with-frm option introduced in MEB 3.7 version. A true online hot backup of InnoDB tables.I also attended a session with similar topic "MEB Best Practices" conducted by Sanjay Manwani, where he double clicked all the features and best strategies of backup & restore. I also got an opportunity to attend other sessions including,* Enabling the new generation of web and cloud services with MySQL 5.6 replication* Getting the most out of MySQL with MySQL Workbench* InnoDB compression for OLTP* Scaling for the Web and Cloud with MySQL replication.Above all, had some special moments in the conference including meeting some of the executives / colleagues for the first time f2f. On a whole, the first MySQL Connect conference was a great success in terms of manifesting the features of our products, direct feedback from customer and team building.  We also had some applauding yahoo moments when Tomas Ulin announced different releases including MySQL 5.6 RC, Connector Python 1.0 and ODBC 5.2 release, MySQL Cluster 7.3, additions to MySQL Enterprise edition etc.

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  • Social Targeting: Who Do You Think You’re Talking To?

    - by Mike Stiles
    Are you the kind of person that tries to sell Clay Aiken CD’s outside Warped Tour concert venues? Then you don’t think a lot about targeting your messages to the right audience. For your communication to pack the biggest punch it can, you need to know where to throw it. And a recent study on social demographics might help you see social targeting in a whole new light. Pingdom’s annual survey of social network demographics shows us first of all that there is no gender difference between Facebook and Twitter. Both are 40% male, 60% female. If you’re looking for locales that lean heavily male, that would be Slashdot, Hacker News and Stack Overflow. The women are dominating Pinterest, Goodreads and Blogger. So what about age? 55% of tweeters are 35 and up, compared with 63% at Pinterest, 65% at Facebook and 70% at LinkedIn. As you can tell, LinkedIn supports the oldest user base, with the average member being 44. The average age at Facebook is 51, and it’s 37 at Twitter. If you want to aim younger, have you met Orkut yet? 83% of its users are under 35. The next sites in order as great candidates for the young market are deviantART, Hacker News, Hi5, Github, and Reddit. I know, other than Reddit, many of you might be saying “who?” But the list could offer an opportunity to look at the vast social world beyond Facebook, Twitter and Google+ (which Pingdom did not include in the survey at all due to a lack of accessible data). As for the average age of social users overall: 26% are 25-34 25% are 35-44 19% are 45-54 16% are 18-24  6% are 55-64  5% are 0-17  and 2% are 65 Now you know where you stand on the “cutting edge” scale for a person your age. You’re welcome. Certainly such demographics are a moving target and need to be watched and reassessed on a regular basis to make sure you’re moving in step with the people you want to talk to. For instance, since Pingdom’s survey last year, the age of the average Facebook user has gone up 2 years, while the age of the average Twitter user has gone down 2 years. With the targeting and analytics tools available on today’s social management platforms, there’s little need to market in the dark. Otherwise, good luck with those Clay CD’s.

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  • Dynamic Bursting ... no really!

    - by Tim Dexter
    If any of you have seen me or my colleagues present BI Publisher to you then we have hopefully mentioned 'bursting.' You may have even seen a demo where we talk about being able to take a batch of data, say invoices. Then split them by some criteria, say customer id; format them with a template; generate the output and then deliver the documents to the recipients with a click. We and especially I, always say this can be completely dynamic! By this I mean, that you could store customer preferences in a database. What layout would each customer like; what output format they would like and how they would like the document delivered. We (I) talk a good talk, but typically don't do the walk in a demo. We hard code everything in the bursting query or bursting control file to get the concept across. But no more peeps! I have finally put together a dynamic bursting demo! Its been minutes in the making but its been tough to find those minutes! Read on ... It's nothing amazing in terms of making the burst dynamic. I created a CUSTOMER_PREFS table with some simple UI in an APEX application so that I can maintain their requirements. In EBS you have descriptive flexfields that could do the same thing or probably even 'contact' fields to store most of the info. Here's my table structure: Name                           Type ------------------------------ -------- CUSTOMER_ID                    NUMBER(6) TEMPLATE_TYPE                  VARCHAR2(20) TEMPLATE_NAME                  VARCHAR2(120) OUTPUT_FORMAT                  VARCHAR2(20) DELIVERY_CHANNEL               VARCHAR2(50) EMAIL                          VARCHAR2(255) FAX                            VARCHAR2(20) ATTACH                         VARCHAR2(20) FILE_LOC                       VARCHAR2(255) Simple enough right? Just need CUSTOMER_ID as the key for the bursting engine to join it to the customer data at burst time. I have not covered the full delivery options, just email, fax and file location. Remember, its a demo people :0) However the principal is exactly the same for each delivery type. They each have a set of attributes that need to be provided and you will need to handle that in your bursting query. On a side note, in EBS, you use a bursting control file, you can apply the same principals that I'm laying out here you just need to get the customer bursting info into the XML data stream so that you can refer to it in the control file using XPATH expressions. Next, we need to look up what attributes or parameters are required for each delivery method. that can be found in the documentation here.  Now we know the combinations of parameters and delivery methods we can construct the query using a series a decode statements: select distinct cp.customer_id "KEY", cp.template_name TEMPLATE, cp.template_type TEMPLATE_FORMAT, 'en-US' LOCALE, cp.output_format OUTPUT_FORMAT, 'false' SAVE_FORMAT, cp.delivery_channel DEL_CHANNEL, decode(cp.delivery_channel,'FILE', cp.file_loc , 'EMAIL', cp.email , 'FAX', cp.fax) PARAMETER1, decode(cp.delivery_channel,'FILE', c.cust_last_name||'_orders.pdf' ,'EMAIL','[email protected]' ,'FAX', 'faxserver.com') PARAMETER2, decode(cp.delivery_channel,'FILE',NULL ,'EMAIL','[email protected]' ,'FAX', null) PARAMETER3, decode(cp.delivery_channel,'FILE',NULL ,'EMAIL','Your current orders' ,'FAX',NULL) PARAMETER4, decode(cp.delivery_channel,'FILE',NULL ,'EMAIL','Please find attached a copy of your current orders with BI Publisher, Inc' ,'FAX',NULL) PARAMETER5, decode(cp.delivery_channel,'FILE',NULL ,'EMAIL','false' ,'FAX',NULL) PARAMETER6, decode(cp.delivery_channel,'FILE',NULL ,'EMAIL','[email protected]' ,'FAX',NULL) PARAMETER7 from cust_prefs cp, customers c, orders_view ov where cp.customer_id = c.customer_id and cp.customer_id = ov.customer_id order by cp.customer_id Pretty straightforward, just need to test, test, test, the query and ensure it's bringing back the correct data based on each customers preferences. Notice the NULL values for parameters that are not relevant for a given delivery channel. You should end up with bursting control data that the bursting engine can use:  Now, your users can run the burst and documents will be formatted, generated and delivered based on the customer prefs. If you're interested in the example, I have used the sample OE schema data for the base report. The report files and CUST_PREFS table are zipped up here. The zip contains the data model (.xdmz), the report and templates (.xdoz) and the sql scripts to create and load data to the CUST_PREFS table.  Once you load the report into the catalog, you'll need to create the OE data connection and point the data model at it. You'll probably need to re-point the report to the data model too. Happy Bursting!

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  • Practical Approaches to increasing Virtualization Density-Part 1

    - by Girish Venkat
    Happy New year everyone!. Let me kick start the year off by talking about Virtualization density.  What is it?The number of virtual servers that a physical server can support and it's increase from the prior physical infrastructure as a percentage. Why is it important?This is important because the density should be indicative of how well the server is getting consumed?So what is wrong ?Virtualization density fails to convey the "Real usage" of a server.  Most of the hypervisor based O/S Virtualization  evangelists take pride in the fact that they are now running a Virtual Server farm of X machines compared to a Physical server farm of Y (with Y less than X obviously). The real question is - has your utilization of the server really increased or not.  In an internal study that was conducted by one of the top financial institution - the utilization of servers only went up by 15% from 30 to 45. So, this really means that just by increasing virtualization density one will not be achieving the goal of using up the servers in their server farm better.  I will write about what the possible approaches are to increase virtualization density in the next entry. 

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  • MySQL Cluster 7.3: On-Demand Webinar and Q&A Available

    - by Mat Keep
    The on-demand webinar for the MySQL Cluster 7.3 Development Release is now available. You can learn more about the design, implementation and getting started with all of the new MySQL Cluster 7.3 features from the comfort and convenience of your own device, including: - Foreign Key constraints in MySQL Cluster - Node.js NoSQL API  - Auto-installation of higher performance distributed, clusters We received some great questions over the course of the webinar, and I wanted to share those for the benefit of a broader audience. Q. What Foreign Key actions are supported: A. The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL Q. Where are Foreign Keys implemented, ie data nodes or SQL nodes? A. They are implemented in the data nodes, therefore can be enforced for both the SQL and NoSQL APIs Q. Are they compatible with the InnoDB Foreign Key implementation? A. Yes, with the following exceptions: - InnoDB doesn’t support “No Action” constraints, MySQL Cluster does - You can choose to suspend FK constraint enforcement with InnoDB using the FOREIGN_KEY_CHECKS parameter; at the moment, MySQL Cluster ignores that parameter. - You cannot set up FKs between 2 tables where one is stored using MySQL Cluster and the other InnoDB. - You cannot change primary keys through the NDB API which means that the MySQL Server actually has to simulate such operations by deleting and re-adding the row. If the PK in the parent table has a FK constraint on it then this causes non-ideal behaviour. With Restrict or No Action constraints, the change will result in an error. With Cascaded constraints, you’d want the rows in the child table to be updated with the new FK value but, the implicit delete of the row from the parent table would remove the associated rows from the child table and the subsequent implicit insert into the parent wouldn’t reinstate the child rows. For this reason, an attempt to add an ON UPDATE CASCADE where the parent column is a primary key will be rejected. Q. Does adding or dropping Foreign Keys cause downtime due to a schema change? A. Nope, this is an online operation. MySQL Cluster supports a number of on-line schema changes, ie adding and dropping indexes, adding columns, etc. Q. Where can I see an example of node.js with MySQL Cluster? A. Check out the tutorial and download the code from GitHub Q. Can I use the auto-installer to support remote deployments? How about setting up MySQL Cluster 7.2? A. Yes to both! Q. Can I get a demo Check out the tutorial. You can download the code from http://labs.mysql.com/ Go to Select Build drop-down box Q. What is be minimum internet speen required for Geo distributed cluster with synchronous replication? A. if you're splitting you cluster between sites then we recommend a network latency of 20ms or less. Alternatively, use MySQL asynchronous replication where the latency of your WAN doesn't impact the latency of your reads/writes. Q. Where you can one learn more about the PayPal project with MySQL Cluster? A. Take a look at the following - you'll find press coverage, a video and slides from their keynote presentation  So, if you want to learn more, listen to the new MySQL Cluster 7.3 on-demand webinar  MySQL Cluster 7.3 is still in the development phase, so it would be great to get your feedback on these new features, and things you want to see!

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  • Tutorial: Getting Started with the NoSQL JavaScript / Node.js API for MySQL Cluster

    - by Mat Keep
    Tutorial authored by Craig Russell and JD Duncan  The MySQL Cluster team are working on a new NoSQL JavaScript connector for MySQL. The objectives are simplicity and high performance for JavaScript users: - allows end-to-end JavaScript development, from the browser to the server and now to the world's most popular open source database - native "NoSQL" access to the storage layer without going first through SQL transformations and parsing. Node.js is a complete web platform built around JavaScript designed to deliver millions of client connections on commodity hardware. With the MySQL NoSQL Connector for JavaScript, Node.js users can easily add data access and persistence to their web, cloud, social and mobile applications. While the initial implementation is designed to plug and play with Node.js, the actual implementation doesn't depend heavily on Node, potentially enabling wider platform support in the future. Implementation The architecture and user interface of this connector are very different from other MySQL connectors in a major way: it is an asynchronous interface that follows the event model built into Node.js. To make it as easy as possible, we decided to use a domain object model to store the data. This allows for users to query data from the database and have a fully-instantiated object to work with, instead of having to deal with rows and columns of the database. The domain object model can have any user behavior that is desired, with the NoSQL connector providing the data from the database. To make it as fast as possible, we use a direct connection from the user's address space to the database. This approach means that no SQL (pun intended) is needed to get to the data, and no SQL server is between the user and the data. The connector is being developed to be extensible to multiple underlying database technologies, including direct, native access to both the MySQL Cluster "ndb" and InnoDB storage engines. The connector integrates the MySQL Cluster native API library directly within the Node.js platform itself, enabling developers to seamlessly couple their high performance, distributed applications with a high performance, distributed, persistence layer delivering 99.999% availability. The following sections take you through how to connect to MySQL, query the data and how to get started. Connecting to the database A Session is the main user access path to the database. You can get a Session object directly from the connector using the openSession function: var nosql = require("mysql-js"); var dbProperties = {     "implementation" : "ndb",     "database" : "test" }; nosql.openSession(dbProperties, null, onSession); The openSession function calls back into the application upon creating a Session. The Session is then used to create, delete, update, and read objects. Reading data The Session can read data from the database in a number of ways. If you simply want the data from the database, you provide a table name and the key of the row that you want. For example, consider this schema: create table employee (   id int not null primary key,   name varchar(32),   salary float ) ENGINE=ndbcluster; Since the primary key is a number, you can provide the key as a number to the find function. function onSession = function(err, session) {   if (err) {     console.log(err);     ... error handling   }   session.find('employee', 0, onData); }; function onData = function(err, data) {   if (err) {     console.log(err);     ... error handling   }   console.log('Found: ', JSON.stringify(data));   ... use data in application }; If you want to have the data stored in your own domain model, you tell the connector which table your domain model uses, by specifying an annotation, and pass your domain model to the find function. var annotations = new nosql.Annotations(); function Employee = function(id, name, salary) {   this.id = id;   this.name = name;   this.salary = salary;   this.giveRaise = function(percent) {     this.salary *= percent;   } }; annotations.mapClass(Employee, {'table' : 'employee'}); function onSession = function(err, session) {   if (err) {     console.log(err);     ... error handling   }   session.find(Employee, 0, onData); }; Updating data You can update the emp instance in memory, but to make the raise persistent, you need to write it back to the database, using the update function. function onData = function(err, emp) {   if (err) {     console.log(err);     ... error handling   }   console.log('Found: ', JSON.stringify(emp));   emp.giveRaise(0.12); // gee, thanks!   session.update(emp); // oops, session is out of scope here }; Using JavaScript can be tricky because it does not have the concept of block scope for variables. You can create a closure to handle these variables, or use a feature of the connector to remember your variables. The connector api takes a fixed number of parameters and returns a fixed number of result parameters to the callback function. But the connector will keep track of variables for you and return them to the callback. So in the above example, change the onSession function to remember the session variable, and you can refer to it in the onData function: function onSession = function(err, session) {   if (err) {     console.log(err);     ... error handling   }   session.find(Employee, 0, onData, session); }; function onData = function(err, emp, session) {   if (err) {     console.log(err);     ... error handling   }   console.log('Found: ', JSON.stringify(emp));   emp.giveRaise(0.12); // gee, thanks!   session.update(emp, onUpdate); // session is now in scope }; function onUpdate = function(err, emp) {   if (err) {     console.log(err);     ... error handling   } Inserting data Inserting data requires a mapped JavaScript user function (constructor) and a session. Create a variable and persist it: function onSession = function(err, session) {   var data = new Employee(999, 'Mat Keep', 20000000);   session.persist(data, onInsert);   } }; Deleting data To remove data from the database, use the session remove function. You use an instance of the domain object to identify the row you want to remove. Only the key field is relevant. function onSession = function(err, session) {   var key = new Employee(999);   session.remove(Employee, onDelete);   } }; More extensive queries We are working on the implementation of more extensive queries along the lines of the criteria query api. Stay tuned. How to evaluate The MySQL Connector for JavaScript is available for download from labs.mysql.com. Select the build: MySQL-Cluster-NoSQL-Connector-for-Node-js You can also clone the project on GitHub Since it is still early in development, feedback is especially valuable (so don't hesitate to leave comments on this blog, or head to the MySQL Cluster forum). Try it out and see how easy (and fast) it is to integrate MySQL Cluster into your Node.js platforms. You can learn more about other previewed functionality of MySQL Cluster 7.3 here

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