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  • World Record Performance on PeopleSoft Enterprise Financials Benchmark on SPARC T4-2

    - by Brian
    Oracle's SPARC T4-2 server achieved World Record performance on Oracle's PeopleSoft Enterprise Financials 9.1 executing 20 Million Journals lines in 8.92 minutes on Oracle Database 11g Release 2 running on Oracle Solaris 11. This is the first result published on this version of the benchmark. The SPARC T4-2 server was able to process 20 million general ledger journal edit and post batch jobs in 8.92 minutes on this benchmark that reflects a large customer environment that utilizes a back-end database of nearly 500 GB. This benchmark demonstrates that the SPARC T4-2 server with PeopleSoft Financials 9.1 can easily process 100 million journal lines in less than 1 hour. The SPARC T4-2 server delivered more than 146 MB/sec of IO throughput with Oracle Database 11g running on Oracle Solaris 11. Performance Landscape Results are presented for PeopleSoft Financials Benchmark 9.1. Results obtained with PeopleSoft Financials Benchmark 9.1 are not comparable to the the previous version of the benchmark, PeopleSoft Financials Benchmark 9.0, due to significant change in data model and supports only batch. PeopleSoft Financials Benchmark, Version 9.1 Solution Under Test Batch (min) SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 8.92 Results from PeopleSoft Financials Benchmark 9.0. PeopleSoft Financials Benchmark, Version 9.0 Solution Under Test Batch (min) Batch with Online (min) SPARC Enterprise M4000 (Web/App) SPARC Enterprise M5000 (DB) 33.09 34.72 SPARC T3-1 (Web/App) SPARC Enterprise M5000 (DB) 35.82 37.01 Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 128 GB memory Storage Configuration: 1 x Sun Storage F5100 Flash Array (for database and redo logs) 2 x Sun Storage 2540-M2 arrays and 2 x Sun Storage 2501-M2 arrays (for backup) Software Configuration: Oracle Solaris 11 11/11 SRU 7.5 Oracle Database 11g Release 2 (11.2.0.3) PeopleSoft Financials 9.1 Feature Pack 2 PeopleSoft Supply Chain Management 9.1 Feature Pack 2 PeopleSoft PeopleTools 8.52 latest patch - 8.52.03 Oracle WebLogic Server 10.3.5 Java Platform, Standard Edition Development Kit 6 Update 32 Benchmark Description The PeopleSoft Enterprise Financials 9.1 benchmark emulates a large enterprise that processes and validates a large number of financial journal transactions before posting the journal entry to the ledger. The validation process certifies that the journal entries are accurate, ensuring that ChartFields values are valid, debits and credits equal out, and inter/intra-units are balanced. Once validated, the entries are processed, ensuring that each journal line posts to the correct target ledger, and then changes the journal status to posted. In this benchmark, the Journal Edit & Post is set up to edit and post both Inter-Unit and Regular multi-currency journals. The benchmark processes 20 million journal lines using AppEngine for edits and Cobol for post processes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN PeopleSoft Financial Management oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

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  • Customer Support Spotlight: Clemson University

    - by cwarticki
    I've begun a Customer Support Spotlight series that highlights our wonderful customers and Oracle loyalists.  A week ago I visited Clemson University.  As I travel to visit and educate our customers, I provide many useful tips/tricks and support best practices (as found on my blog and twitter). Most of all, I always discover an Oracle gem who deserves recognition for their hard work and advocacy. Meet George Manley.  George is a Storage Engineer who has worked in Clemson's Data Center all through college, partially in the Hardware Architecture group and partially in the Storage group. George and the rest of the Storage Team work with most all of the storage technologies that they have here at Clemson. This includes a wide array of different vendors' disk arrays, with the most of them being Oracle/Sun 2540's.  He also works with SAM/QFS, ACSLS, and our SL8500 Tape Libraries (all three Oracle/Sun products). (pictured L to R, Matt Schoger (Oracle), Mark Flores (Oracle) and George Manley) George was kind enough to take us for a data center tour.  It was amazing.  I rarely get to see the inside of data centers, and this one was massive. Clemson Computing and Information Technology’s physical resources include the main data center located in the Information Technology Center at the Innovation Campus and Technology Park. The core of Clemson’s computing infrastructure, the data center has 21,000 sq ft of raised floor and is powered by a 14MW substation. The ITC power capacity is 4.5MW.  The data center is the home of both enterprise and HPC systems, and is staffed by CCIT staff on a 24 hour basis from a state of the art network operations center within the ITC. A smaller business continuance data center is located on the main campus.  The data center serves a wide variety of purposes including HPC (supercomputing) resources which are shared with other Universities throughout the state, the state's medicaid processing system, and nearly all other needs for Clemson University. Yes, that's no typo (14,256 cores and 37TB of memory!!! Thanks for the tour George and thank you very much for your time.  The tour was fantastic. I enjoyed getting to know your team and I look forward to many successes from Clemson using Oracle products. -Chris WartickiGlobal Customer Management

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  • Overview of the IBM BladeCenter

    IBM BladeCenter switches provide the small to mid size business with a number of tactical advantages. Companies can increase storage efficiency by permitting a sharing of disc storage across multiple... [Author: Bob Wall Jr. - Computers and Internet - April 10, 2010]

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  • Nouvelle certification sur le système de stockage New Certification Pillar Axiom 600

    - by swalker
    Vous pouvez dès à présent passer l'examen Pillar Axiom 600 Storage System Essentials (1Z0-581) en version bêta. Décrochez cet examen pour devenir Spécialiste de l'implémentation des systèmes de stockage Pillar Axiom 600. Les partenaires Oracle peuvent bénéficier de bons gratuits ! Si vous souhaitez recevoir un bon gratuit pour l’examen bêta, veuillez envoyer votre demande à l’adresse [email protected] sans oublier de préciser votre nom, votre adresse email professionnelle, le nom de votre société ainsi que le nom de l'examen : Examen Pillar Axiom 600 Storage System Essentials Beta.

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  • Best partition Scheme for Ubuntu Server

    - by K.K Patel
    I am going to deploy Ubuntu server having Following servers on it Bind server, dhcp server, LAMP Server, Openssh Server, Ldap server, Monodb database, FTP server,mail server, Samba server, NFS server , in future I want to set Openstack for PAAS. Currently I have Raid 5 with 10TB. How should I make my Partition Scheme So never get problem in future and easily expand Storage size. Suggest me such a partition Scheme with giving specific percentage of Storage to partitions like /, /boot, /var, /etc. Thanks In advance

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  • Cost Comparison Hard Disk Drive to Solid State Drive on Price per Gigabyte - dispelling a myth!

    - by tonyrogerson
    It is often said that Hard Disk Drive storage is significantly cheaper per GiByte than Solid State Devices – this is wholly inaccurate within the database space. People need to look at the cost of the complete solution and not just a single component part in isolation to what is really required to meet the business requirement. Buying a single Hitachi Ultrastar 600GB 3.5” SAS 15Krpm hard disk drive will cost approximately £239.60 (http://scan.co.uk, 22nd March 2012) compared to an OCZ 600GB Z-Drive R4 CM84 PCIe costing £2,316.54 (http://scan.co.uk, 22nd March 2012); I’ve not included FusionIO ioDrive because there is no public pricing available for it – something I never understand and personally when companies do this I immediately think what are they hiding, luckily in FusionIO’s case the product is proven though is expensive compared to OCZ enterprise offerings. On the face of it the single 15Krpm hard disk has a price per GB of £0.39, the SSD £3.86; this is what you will see in the press and this is what sales people will use in comparing the two technologies – do not be fooled by this bullshit people! What is the requirement? The requirement is the database will have a static size of 400GB kept static through archiving so growth and trim will balance the database size, the client requires resilience, there will be several hundred call centre staff querying the database where queries will read a small amount of data but there will be no hot spot in the data so the randomness will come across the entire 400GB of the database, estimates predict that the IOps required will be approximately 4,000IOps at peak times, because it’s a call centre system the IO latency is important and must remain below 5ms per IO. The balance between read and write is 70% read, 30% write. The requirement is now defined and we have three of the most important pieces of the puzzle – space required, estimated IOps and maximum latency per IO. Something to consider with regard SQL Server; write activity requires synchronous IO to the storage media specifically the transaction log; that means the write thread will wait until the IO is completed and hardened off until the thread can continue execution, the requirement has stated that 30% of the system activity will be write so we can expect a high amount of synchronous activity. The hardware solution needs to be defined; two possible solutions: hard disk or solid state based; the real question now is how many hard disks are required to achieve the IO throughput, the latency and resilience, ditto for the solid state. Hard Drive solution On a test on an HP DL380, P410i controller using IOMeter against a single 15Krpm 146GB SAS drive, the throughput given on a transfer size of 8KiB against a 40GiB file on a freshly formatted disk where the partition is the only partition on the disk thus the 40GiB file is on the outer edge of the drive so more sectors can be read before head movement is required: For 100% sequential IO at a queue depth of 16 with 8 worker threads 43,537 IOps at an average latency of 2.93ms (340 MiB/s), for 100% random IO at the same queue depth and worker threads 3,733 IOps at an average latency of 34.06ms (34 MiB/s). The same test was done on the same disk but the test file was 130GiB: For 100% sequential IO at a queue depth of 16 with 8 worker threads 43,537 IOps at an average latency of 2.93ms (340 MiB/s), for 100% random IO at the same queue depth and worker threads 528 IOps at an average latency of 217.49ms (4 MiB/s). From the result it is clear random performance gets worse as the disk fills up – I’m currently writing an article on short stroking which will cover this in detail. Given the work load is random in nature looking at the random performance of the single drive when only 40 GiB of the 146 GB is used gives near the IOps required but the latency is way out. Luckily I have tested 6 x 15Krpm 146GB SAS 15Krpm drives in a RAID 0 using the same test methodology, for the same test above on a 130 GiB for each drive added the performance boost is near linear, for each drive added throughput goes up by 5 MiB/sec, IOps by 700 IOps and latency reducing nearly 50% per drive added (172 ms, 94 ms, 65 ms, 47 ms, 37 ms, 30 ms). This is because the same 130GiB is spread out more as you add drives 130 / 1, 130 / 2, 130 / 3 etc. so implicit short stroking is occurring because there is less file on each drive so less head movement required. The best latency is still 30 ms but we have the IOps required now, but that’s on a 130GiB file and not the 400GiB we need. Some reality check here: a) the drive randomness is more likely to be 50/50 and not a full 100% but the above has highlighted the effect randomness has on the drive and the more a drive fills with data the worse the effect. For argument sake let us assume that for the given workload we need 8 disks to do the job, for resilience reasons we will need 16 because we need to RAID 1+0 them in order to get the throughput and the resilience, RAID 5 would degrade performance. Cost for hard drives: 16 x £239.60 = £3,833.60 For the hard drives we will need disk controllers and a separate external disk array because the likelihood is that the server itself won’t take the drives, a quick spec off DELL for a PowerVault MD1220 which gives the dual pathing with 16 disks 146GB 15Krpm 2.5” disks is priced at £7,438.00, note its probably more once we had two controller cards to sit in the server in, racking etc. Minimum cost taking the DELL quote as an example is therefore: {Cost of Hardware} / {Storage Required} £7,438.60 / 400 = £18.595 per GB £18.59 per GiB is a far cry from the £0.39 we had been told by the salesman and the myth. Yes, the storage array is composed of 16 x 146 disks in RAID 10 (therefore 8 usable) giving an effective usable storage availability of 1168GB but the actual storage requirement is only 400 and the extra disks have had to be purchased to get the  IOps up. Solid State Drive solution A single card significantly exceeds the IOps and latency required, for resilience two will be required. ( £2,316.54 * 2 ) / 400 = £11.58 per GB With the SSD solution only two PCIe sockets are required, no external disk units, no additional controllers, no redundant controllers etc. Conclusion I hope by showing you an example that the myth that hard disk drives are cheaper per GiB than Solid State has now been dispelled - £11.58 per GB for SSD compared to £18.59 for Hard Disk. I’ve not even touched on the running costs, compare the costs of running 18 hard disks, that’s a lot of heat and power compared to two PCIe cards!Just a quick note: I've left a fair amount of information out due to this being a blog! If in doubt, email me :)I'll also deal with the myth that SSD's wear out at a later date as well - that's just way over done still, yes, 5 years ago, but now - no.

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  • Using the jQuery UI Library in a MVC 3 Application to Build a Dialog Form

    - by ChrisD
    Using a simulated dialog window is a nice way to handle inline data editing. The jQuery UI has a UI widget for a dialog window that makes it easy to get up and running with it in your application. With the release of ASP.NET MVC 3, Microsoft included the jQuery UI scripts and files in the MVC 3 project templates for Visual Studio. With the release of the MVC 3 Tools Update, Microsoft implemented the inclusion of those with NuGet as packages. That means we can get up and running using the latest version of the jQuery UI with minimal effort. To the code! Another that might interested you about JQuery Mobile and ASP.NET MVC 3 with C#. If you are starting with a new MVC 3 application and have the Tools Update then you are a NuGet update and a <link> and <script> tag away from adding the jQuery UI to your project. If you are using an existing MVC project you can still get the jQuery UI library added to your project via NuGet and then add the link and script tags. Assuming that you have pulled down the latest version (at the time of this publish it was 1.8.13) you can add the following link and script tags to your <head> tag: < link href = "@Url.Content(" ~ / Content / themes / base / jquery . ui . all . css ")" rel = "Stylesheet" type = "text/css" /> < script src = "@Url.Content(" ~ / Scripts / jquery-ui-1 . 8 . 13 . min . js ")" type = "text/javascript" ></ script > The jQuery UI library relies upon the CSS scripts and some image files to handle rendering of its widgets (you can choose a different theme or role your own if you like). Adding these to the stock _Layout.cshtml file results in the following markup: <!DOCTYPE html> < html > < head >     < meta charset = "utf-8" />     < title > @ViewBag.Title </ title >     < link href = "@Url.Content(" ~ / Content / Site . css ")" rel = "stylesheet" type = "text/css" />     <link href="@Url.Content("~/Content/themes/base/jquery.ui.all.css")" rel="Stylesheet" type="text/css" />     <script src="@Url.Content("~/Scripts/jquery-1.5.1.min.js")" type="text/javascript"></script>     <script src="@Url.Content("~/Scripts/modernizr-1.7.min . js ")" type = "text/javascript" ></ script >     < script src = "@Url.Content(" ~ / Scripts / jquery-ui-1 . 8 . 13 . min . js ")" type = "text/javascript" ></ script > </ head > < body >     @RenderBody() </ body > </ html > Our example will involve building a list of notes with an id, title and description. Each note can be edited and new notes can be added. The user will never have to leave the single page of notes to manage the note data. The add and edit forms will be delivered in a jQuery UI dialog widget and the note list content will get reloaded via an AJAX call after each change to the list. To begin, we need to craft a model and a data management class. We will do this so we can simulate data storage and get a feel for the workflow of the user experience. The first class named Note will have properties to represent our data model. namespace Website . Models {     public class Note     {         public int Id { get ; set ; }         public string Title { get ; set ; }         public string Body { get ; set ; }     } } The second class named NoteManager will be used to set up our simulated data storage and provide methods for querying and updating the data. We will take a look at the class content as a whole and then walk through each method after. using System . Collections . ObjectModel ; using System . Linq ; using System . Web ; namespace Website . Models {     public class NoteManager     {         public Collection < Note > Notes         {             get             {                 if ( HttpRuntime . Cache [ "Notes" ] == null )                     this . loadInitialData ();                 return ( Collection < Note >) HttpRuntime . Cache [ "Notes" ];             }         }         private void loadInitialData ()         {             var notes = new Collection < Note >();             notes . Add ( new Note                           {                               Id = 1 ,                               Title = "Set DVR for Sunday" ,                               Body = "Don't forget to record Game of Thrones!"                           });             notes . Add ( new Note                           {                               Id = 2 ,                               Title = "Read MVC article" ,                               Body = "Check out the new iwantmymvc.com post"                           });             notes . Add ( new Note                           {                               Id = 3 ,                               Title = "Pick up kid" ,                               Body = "Daughter out of school at 1:30pm on Thursday. Don't forget!"                           });             notes . Add ( new Note                           {                               Id = 4 ,                               Title = "Paint" ,                               Body = "Finish the 2nd coat in the bathroom"                           });             HttpRuntime . Cache [ "Notes" ] = notes ;         }         public Collection < Note > GetAll ()         {             return Notes ;         }         public Note GetById ( int id )         {             return Notes . Where ( i => i . Id == id ). FirstOrDefault ();         }         public int Save ( Note item )         {             if ( item . Id <= 0 )                 return saveAsNew ( item );             var existingNote = Notes . Where ( i => i . Id == item . Id ). FirstOrDefault ();             existingNote . Title = item . Title ;             existingNote . Body = item . Body ;             return existingNote . Id ;         }         private int saveAsNew ( Note item )         {             item . Id = Notes . Count + 1 ;             Notes . Add ( item );             return item . Id ;         }     } } The class has a property named Notes that is read only and handles instantiating a collection of Note objects in the runtime cache if it doesn't exist, and then returns the collection from the cache. This property is there to give us a simulated storage so that we didn't have to add a full blown database (beyond the scope of this post). The private method loadInitialData handles pre-filling the collection of Note objects with some initial data and stuffs them into the cache. Both of these chunks of code would be refactored out with a move to a real means of data storage. The GetAll and GetById methods access our simulated data storage to return all of our notes or a specific note by id. The Save method takes in a Note object, checks to see if it has an Id less than or equal to zero (we assume that an Id that is not greater than zero represents a note that is new) and if so, calls the private method saveAsNew . If the Note item sent in has an Id , the code finds that Note in the simulated storage, updates the Title and Description , and returns the Id value. The saveAsNew method sets the Id , adds it to the simulated storage, and returns the Id value. The increment of the Id is simulated here by getting the current count of the note collection and adding 1 to it. The setting of the Id is the only other chunk of code that would be refactored out when moving to a different data storage approach. With our model and data manager code in place we can turn our attention to the controller and views. We can do all of our work in a single controller. If we use a HomeController , we can add an action method named Index that will return our main view. An action method named List will get all of our Note objects from our manager and return a partial view. We will use some jQuery to make an AJAX call to that action method and update our main view with the partial view content returned. Since the jQuery AJAX call will cache the call to the content in Internet Explorer by default (a setting in jQuery), we will decorate the List, Create and Edit action methods with the OutputCache attribute and a duration of 0. This will send the no-cache flag back in the header of the content to the browser and jQuery will pick that up and not cache the AJAX call. The Create action method instantiates a new Note model object and returns a partial view, specifying the NoteForm.cshtml view file and passing in the model. The NoteForm view is used for the add and edit functionality. The Edit action method takes in the Id of the note to be edited, loads the Note model object based on that Id , and does the same return of the partial view as the Create method. The Save method takes in the posted Note object and sends it to the manager to save. It is decorated with the HttpPost attribute to ensure that it will only be available via a POST. It returns a Json object with a property named Success that can be used by the UX to verify everything went well (we won't use that in our example). Both the add and edit actions in the UX will post to the Save action method, allowing us to reduce the amount of unique jQuery we need to write in our view. The contents of the HomeController.cs file: using System . Web . Mvc ; using Website . Models ; namespace Website . Controllers {     public class HomeController : Controller     {         public ActionResult Index ()         {             return View ();         }         [ OutputCache ( Duration = 0 )]         public ActionResult List ()         {             var manager = new NoteManager ();             var model = manager . GetAll ();             return PartialView ( model );         }         [ OutputCache ( Duration = 0 )]         public ActionResult Create ()         {             var model = new Note ();             return PartialView ( "NoteForm" , model );         }         [ OutputCache ( Duration = 0 )]         public ActionResult Edit ( int id )         {             var manager = new NoteManager ();             var model = manager . GetById ( id );             return PartialView ( "NoteForm" , model );         }         [ HttpPost ]         public JsonResult Save ( Note note )         {             var manager = new NoteManager ();             var noteId = manager . Save ( note );             return Json ( new { Success = noteId > 0 });         }     } } The view for the note form, NoteForm.cshtml , looks like so: @model Website . Models . Note @using ( Html . BeginForm ( "Save" , "Home" , FormMethod . Post , new { id = "NoteForm" })) { @Html . Hidden ( "Id" ) < label class = "Title" >     < span > Title < /span><br / >     @Html . TextBox ( "Title" ) < /label> <label class="Body">     <span>Body</ span >< br />     @Html . TextArea ( "Body" ) < /label> } It is a strongly typed view for our Note model class. We give the <form> element an id attribute so that we can reference it via jQuery. The <label> and <span> tags give our UX some structure that we can style with some CSS. The List.cshtml view is used to render out a <ul> element with all of our notes. @model IEnumerable < Website . Models . Note > < ul class = "NotesList" >     @foreach ( var note in Model )     {     < li >         @note . Title < br />         @note . Body < br />         < span class = "EditLink ButtonLink" noteid = "@note.Id" > Edit < /span>     </ li >     } < /ul> This view is strongly typed as well. It includes a <span> tag that we will use as an edit button. We add a custom attribute named noteid to the <span> tag that we can use in our jQuery to identify the Id of the note object we want to edit. The view, Index.cshtml , contains a bit of html block structure and all of our jQuery logic code. @ {     ViewBag . Title = "Index" ; } < h2 > Notes < /h2> <div id="NoteListBlock"></ div > < span class = "AddLink ButtonLink" > Add New Note < /span> <div id="NoteDialog" title="" class="Hidden"></ div > < script type = "text/javascript" >     $ ( function () {         $ ( "#NoteDialog" ). dialog ({             autoOpen : false , width : 400 , height : 330 , modal : true ,             buttons : {                 "Save" : function () {                     $ . post ( "/Home/Save" ,                         $ ( "#NoteForm" ). serialize (),                         function () {                             $ ( "#NoteDialog" ). dialog ( "close" );                             LoadList ();                         });                 },                 Cancel : function () { $ ( this ). dialog ( "close" ); }             }         });         $ ( ".EditLink" ). live ( "click" , function () {             var id = $ ( this ). attr ( "noteid" );             $ ( "#NoteDialog" ). html ( "" )                 . dialog ( "option" , "title" , "Edit Note" )                 . load ( "/Home/Edit/" + id , function () { $ ( "#NoteDialog" ). dialog ( "open" ); });         });         $ ( ".AddLink" ). click ( function () {             $ ( "#NoteDialog" ). html ( "" )                 . dialog ( "option" , "title" , "Add Note" )                 . load ( "/Home/Create" , function () { $ ( "#NoteDialog" ). dialog ( "open" ); });         });         LoadList ();     });     function LoadList () {         $ ( "#NoteListBlock" ). load ( "/Home/List" );     } < /script> The <div> tag with the id attribute of "NoteListBlock" is used as a container target for the load of the partial view content of our List action method. It starts out empty and will get loaded with content via jQuery once the DOM is loaded. The <div> tag with the id attribute of "NoteDialog" is the element for our dialog widget. The jQuery UI library will use the title attribute for the text in the dialog widget top header bar. We start out with it empty here and will dynamically change the text via jQuery based on the request to either add or edit a note. This <div> tag is given a CSS class named "Hidden" that will set the display:none style on the element. Since our call to the jQuery UI method to make the element a dialog widget will occur in the jQuery document ready code block, the end user will see the <div> element rendered in their browser as the page renders and then it will hide after that jQuery call. Adding the display:hidden to the <div> element via CSS will ensure that it is never rendered until the user triggers the request to open the dialog. The jQuery document load block contains the setup for the dialog node, click event bindings for the edit and add links, and a call to a JavaScript function called LoadList that handles the AJAX call to the List action method. The .dialog() method is called on the "NoteDialog" <div> element and the options are set for the dialog widget. The buttons option defines 2 buttons and their click actions. The first is the "Save" button (the text in quotations is used as the text for the button) that will do an AJAX post to our Save action method and send the serialized form data from the note form (targeted with the id attribute "NoteForm"). Upon completion it will close the dialog widget and call the LoadList to update the UX without a redirect. The "Cancel" button simply closes the dialog widget. The .live() method handles binding a function to the "click" event on all elements with the CSS class named EditLink . We use the .live() method because it will catch and bind our function to elements even as the DOM changes. Since we will be constantly changing the note list as we add and edit we want to ensure that the edit links get wired up with click events. The function for the click event on the edit links gets the noteid attribute and stores it in a local variable. Then it clears out the HTML in the dialog element (to ensure a fresh start), calls the .dialog() method and sets the "title" option (this sets the title attribute value), and then calls the .load() AJAX method to hit our Edit action method and inject the returned content into the "NoteDialog" <div> element. Once the .load() method is complete it opens the dialog widget. The click event binding for the add link is similar to the edit, only we don't need to get the id value and we load the Create action method. This binding is done via the .click() method because it will only be bound on the initial load of the page. The add button will always exist. Finally, we toss in some CSS in the Content/Site.css file to style our form and the add/edit links. . ButtonLink { color : Blue ; cursor : pointer ; } . ButtonLink : hover { text - decoration : underline ; } . Hidden { display : none ; } #NoteForm label { display:block; margin-bottom:6px; } #NoteForm label > span { font-weight:bold; } #NoteForm input[type=text] { width:350px; } #NoteForm textarea { width:350px; height:80px; } With all of our code in place we can do an F5 and see our list of notes: If we click on an edit link we will get the dialog widget with the correct note data loaded: And if we click on the add new note link we will get the dialog widget with the empty form: The end result of our solution tree for our sample:

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  • #DAX Query Plan in SQL Server 2012 #Tabular

    - by Marco Russo (SQLBI)
    The SQL Server Profiler provides you many information regarding the internal behavior of DAX queries sent to a BISM Tabular model. Similar to MDX, also in DAX there is a Formula Engine (FE) and a Storage Engine (SE). The SE is usually handled by Vertipaq (unless you are using DirectQuery mode) and Vertipaq SE Query classes of events gives you a SQL-like syntax that represents the query sent to the storage engine. Another interesting class of events is the DAX Query Plan , which contains a couple...(read more)

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  • Apprentice Boot Camp in South Africa (Part 1)

    - by Tim Koekkoek
    By Maximilian Michel (DE), Jorge Garnacho (ES), Daniel Maull (UK), Adam Griffiths (UK), Guillermo De Las Nieves (ES), Catriona McGill (UK), Ed Dunlop (UK) The Boot Camp in South Africa was an amazing experience for all of us. The minute we landed, we were made to feel at home from our host Patrick Fitzgerald. The whole family who run the Guest House were also very friendly and always keen to help us. Since we had people from South Africa to show us all the amazing sights and their traditional ways to live their lives, the two weeks were very enjoyable for all of us and we came much closer together as a group. You can read this in the following parts of this report. Enjoy! The first group of Apprentices in Oracle (from left to right): Maximilian Michel (DE), Jorge Garnacho (ES), Daniel Maull (UK), Adam Griffiths (UK), Guillermo De Las Nieves (ES), Catriona McGill (UK), Ed Dunlop (UK) The Training Well, it’s time to talk about the main purpose of our trip to South Africa: the training. Two weeks, two courses. Servers and Storage. Two weeks to learn as much as possible and get the certificate. First week: Eben Pretorius with Servers Boot Camp. Learning about: • Machines: T1000, T2000, T3, T4, M series; • How to connect to the machines: serial and network connections; • Levels of software: ALOM, ILOM, OBP and of course the operating system, Solaris Combined with the practical part (screwdriver in one hand, and antistatic wristband on the other) makes quite a lot of stuff! But fortunately, Eben was able to tell us about everything without making our brains explode. For the second week: Storage Boot Camp with Deon Van Vuuren. Taking a look at the content: • Storage machines; • Connectors and protocols: SCSi, SAS, SATA Fiber Channel. Again, huge amounts of information, but Deon definitely did a great job and helped us learn it all. At the end, there was just one question left. Were we able to pass the exam and get the certificate? Well, what can we say? Just take a closer look at the picture above and make your conclusions! Our lovely Oracle office in Woodmead (near Johannesburg) We are all very proud to receive certification in “Server and Storage Support Fundamentals” together with our trainer Deon Van Vuuren. In summary, in case that you don't remember any of the above, the allies for a field engineer are: • System Handbook • EIS-DVD • A proper toolkit With these tools by our side, we’ll be unbeatable!  In the next article later this week, you can find part 2 of our experiences!

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  • Neue Zertifizierung von Pillar Axiom 600 Speichersystem

    - by swalker
    Sie haben nun die Möglichkeit, die Beta-Prüfung für Pillar Axiom 600 Storage System Essentials (1Z0-581) vorzunehmen. Wenn Sie die Prüfung bestehen, können Sie Implementierungsspezialist für Pillar Axiom 600 Speichersysteme werden! Für Oracle Partner sind kostenlose Gutscheine erhältlich. Wenn Sie einen kostenlosen Gutschein für die Beta-Prüfung erhalten möchten, senden Sie Ihre Anfrage an [email protected] und geben Sie bitte Ihren Namen, Ihre geschäftliche E-Mail-Adresse, Ihr Unternehmen und den Namen der Prüfung (Pillar Axiom 600 Storage System Essentials Beta) an.

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  • Some Oracle VM 3 updates

    - by wcoekaer
    Today we did another patch set update for Oracle VM 3 (3.0.3-build 227). This can be downloaded from My Oracle Support as patch ID 14736185. There are quite a few updates in here and I highly recommend any Oracle VM 3 customer or user to install this update. This patch can be installed on top of Oracle VM 3.0 versions 3.0.2 and 3.0.3. The patch is cumulative for 3.0.3. So if you already installed patch update 1 (3.0.3-150) then this will just be incremental on top of that and brings you to 3.0.3-build 227. There is a readme file which contains the patchlist in the patch info. The following patches are released on ULN for Oracle VM server 3.0 : initscripts-8.45.30-2.100.18.el5.x86_64 The inittab file and the /etc/init.d scripts. kernel-ovs-2.6.32.21-45.6.x86_64 The Linux kernel kernel-ovs-firmware-2.6.32.21-45.6.x86_64 Firmware files used by the Linux kernel osc-oracle-ocfs2-0.1.0-35.el5.noarch Oracle Storage Connect ocfs2 Plugin osc-plugin-manager-1.2.8-9.el5.3.noarch Oracle Storage Connect Plugin Infrastructure osc-plugin-manager-devel-1.2.8-9.el5.3.noarch Oracle Storage Connect Plugin Development ovs-agent-3.0.3-41.6.x86_64 Agent for Oracle VM xen-4.0.0-81.el5.1.x86_64 Xen is a virtual machine monitor xen-devel-4.0.0-81.el5.1.x86_64 Development libraries for Xen tools xen-tools-4.0.0-81.el5.1.x86_64 Various tooling for the manipulation of Xen instances Errata emails will be sent in the next few days with details on the above updates. Or you will find them here. I also did an update of my Oracle VM utilities to 0.4.0. They are also available from My Oracle Support, patch ID 14736239. These utils can be unzipped and installed on the server running Oracle VM Manager. Typically in /u01/app/oracle/ovm-manager-3/ovm_utils. There is a set of man pages in /u01/app/oracle/ovm-manager-3/ovm_utils/man/man8. There now are 6 commands : ovm_vmcontrol : VM level operations ovm_servercontrol : server level operations ovm_vmdisks : virtual disk/physical location mapping for VM disks ovm_vmmessage : message passing utility between the manager and the VM tools (in the Oracle VM templates) ovm_repocontrol : repository level operations ovm_poolcontrol : pool level operations Some of the new changes : at a pool level, acknowledge events and cascade to servers and virtual machines with outstanding events at a pool level, do a rescan of the storage for fibrechannel/iscsi disks if you add new devices (it does this operation then on every running server) at a repository level, fixup a device if it had a failed create repository at a repository level, refresh the repository and this will update the free space in the UI for ocfs2 repositories at a server level, acknowledge server events and cascade to virtual machines if needed at a VM level, acknowledge VM events at a VM level, bind vcpus to cores with vcpuset/vcpuget Please see the man pages and remember that these tools are just written As Is - no SRs... (per the documentation) Hopefully they are useful.

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  • Class instance clustering in object reference graph for multi-entries serialization

    - by Juh_
    My question is on the best way to cluster a graph of class instances (i.e. objects, the graph nodes) linked by object references (the -directed- edges of the graph) around specifically marked objects. To explain better my question, let me explain my motivation: I currently use a moderately complex system to serialize the data used in my projects: "marked" objects have a specific attributes which stores a "saving entry": the path to an associated file on disc (but it could be done for any storage type providing the suitable interface) Those object can then be serialized automatically (eg: obj.save()) The serialization of a marked object 'a' contains implicitly all objects 'b' for which 'a' has a reference to, directly s.t: a.b = b, or indirectly s.t.: a.c.b = b for some object 'c' This is very simple and basically define specific storage entries to specific objects. I have then "container" type objects that: can be serialized similarly (in fact their are or can-be "marked") they don't serialize in their storage entries the "marked" objects (with direct reference): if a and a.b are both marked, a.save() calls b.save() and stores a.b = storage_entry(b) So, if I serialize 'a', it will serialize automatically all objects that can be reached from 'a' through the object reference graph, possibly in multiples entries. That is what I want, and is usually provides the functionalities I need. However, it is very ad-hoc and there are some structural limitations to this approach: the multi-entry saving can only works through direct connections in "container" objects, and there are situations with undefined behavior such as if two "marked" objects 'a'and 'b' both have a reference to an unmarked object 'c'. In this case my system will stores 'c' in both 'a' and 'b' making an implicit copy which not only double the storage size, but also change the object reference graph after re-loading. I am thinking of generalizing the process. Apart for the practical questions on implementation (I am coding in python, and use Pickle to serialize my objects), there is a general question on the way to attach (cluster) unmarked objects to marked ones. So, my questions are: What are the important issues that should be considered? Basically why not just use any graph parsing algorithm with the "attach to last marked node" behavior. Is there any work done on this problem, practical or theoretical, that I should be aware of? Note: I added the tag graph-database because I think the answer might come from that fields, even if the question is not.

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  • eSTEP Newsletter October 2012 now available

    - by uwes
    Dear Partners,We would like to inform you that the October '12 issue of our Newsletter is now available.The issue contains information to the following topics:News from CorpOracle Announces Oracle Solaris 11.1 at Oracle OpenWorld; Oracle Announces Oracle Exadata X3 Database In-Memory Machine; Oracle Enterprise Manager 12c introduces New Tools and Programs for Partners; Oracle Unveils First Industry-Specific Engineered System - the Oracle Networks Applications Platform,;  Oracle Unveils Expanded Oracle Cloud Offerings; Oracle Outlines Plans to Make the Future Java During JavaOne 2012 Strategy Keynote; Some interesting Java Facts and Figures; Oracle Announces MySQL 5.6 Release Candidate Technical Section What's up with LDoms (4 tech articles); Oracle SPARC T4 Systems cut Complexity, cost of Cryptographic Tasks; PeopleSoft Enterprise Financials 9.1; PeopleSoft HCM 9.1 combined online and batch benchmark,; Product Update Bulletin Oracle Solaris Cluster Oct 2012; Sun ZFS Storage 7420; SPARC Product Line Update; SPARC M-series -  New DAT 160 plus EOL of M3000 series; SPARC SuperCluster and SPARC T4 Servers Included in Enterprise Reference Architecture Sizing Tool; Oracle MagazineLearning & EventsRecently delivered Techcasts: An Update after the Oracle Open World, An Update on OVM Server for SPARC; Update to Oracle Database ApplianceReferencesBridgestone Aircraft Tire Reduces Required Disk Capacity by 50% with Virtualized Storage Solution; Fiat Group Automobiles Aligns Operational Decisions with Strategy by Using End-to-End Enterprise Performance Management System; Birkbeck, University of London Develops World-Class Computer Science Facilities While Reducing Costs with Ultrareliable and Scalable Data Infrastructure How toIntroducing Oracle System Assistant; How to Prepare a ZFS Storage Appliance to Serve as a Storage Device; Migrating Oracle Solaris 8 P2V with Oracle Database 10.2 and ASM; White paper on Best Practices for Building a Virtualized SPARC Computing Environment, How to extend the Oracle Solaris Studio IDE with NetBeans Plug-Ins; How I simplified Oracle Database 11g Installation on Oracle Linux 6You find the Newsletter on our portal under eSTEP News ---> Latest Newsletter. You will need to provide your email address and the pin below to get access. Link to the portal is shown below.URL: http://launch.oracle.com/PIN: eSTEP_2011Previous published Newsletters can be found under the Archived Newsletters section and more useful information under the Events, Download and Links tab. Feel free to explore and any feedback is appreciated to help us improve the service and information we deliver.Thanks and best regards,Partner HW Enablement EMEA

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  • Online ALTER TABLE in MySQL 5.6

    - by Marko Mäkelä
    This is the low-level view of data dictionary language (DDL) operations in the InnoDB storage engine in MySQL 5.6. John Russell gave a more high-level view in his blog post April 2012 Labs Release – Online DDL Improvements. MySQL before the InnoDB Plugin Traditionally, the MySQL storage engine interface has taken a minimalistic approach to data definition language. The only natively supported operations were CREATE TABLE, DROP TABLE and RENAME TABLE. Consider the following example: CREATE TABLE t(a INT); INSERT INTO t VALUES (1),(2),(3); CREATE INDEX a ON t(a); DROP TABLE t; The CREATE INDEX statement would be executed roughly as follows: CREATE TABLE temp(a INT, INDEX(a)); INSERT INTO temp SELECT * FROM t; RENAME TABLE t TO temp2; RENAME TABLE temp TO t; DROP TABLE temp2; You could imagine that the database could crash when copying all rows from the original table to the new one. For example, it could run out of file space. Then, on restart, InnoDB would roll back the huge INSERT transaction. To fix things a little, a hack was added to ha_innobase::write_row for committing the transaction every 10,000 rows. Still, it was frustrating that even a simple DROP INDEX would make the table unavailable for modifications for a long time. Fast Index Creation in the InnoDB Plugin of MySQL 5.1 MySQL 5.1 introduced a new interface for CREATE INDEX and DROP INDEX. The old table-copying approach can still be forced by SET old_alter_table=0. This interface is used in MySQL 5.5 and in the InnoDB Plugin for MySQL 5.1. Apart from the ability to do a quick DROP INDEX, the main advantage is that InnoDB will execute a merge-sort algorithm before inserting the index records into each index that is being created. This should speed up the insert into the secondary index B-trees and potentially result in a better B-tree fill factor. The 5.1 ALTER TABLE interface was not perfect. For example, DROP FOREIGN KEY still invoked the table copy. Renaming columns could conflict with InnoDB foreign key constraints. Combining ADD KEY and DROP KEY in ALTER TABLE was problematic and not atomic inside the storage engine. The ALTER TABLE interface in MySQL 5.6 The ALTER TABLE storage engine interface was completely rewritten in MySQL 5.6. Instead of introducing a method call for every conceivable operation, MySQL 5.6 introduced a handful of methods, and data structures that keep track of the requested changes. In MySQL 5.6, online ALTER TABLE operation can be requested by specifying LOCK=NONE. Also LOCK=SHARED and LOCK=EXCLUSIVE are available. The old-style table copying can be requested by ALGORITHM=COPY. That one will require at least LOCK=SHARED. From the InnoDB point of view, anything that is possible with LOCK=EXCLUSIVE is also possible with LOCK=SHARED. Most ALGORITHM=INPLACE operations inside InnoDB can be executed online (LOCK=NONE). InnoDB will always require an exclusive table lock in two phases of the operation. The execution phases are tied to a number of methods: handler::check_if_supported_inplace_alter Checks if the storage engine can perform all requested operations, and if so, what kind of locking is needed. handler::prepare_inplace_alter_table InnoDB uses this method to set up the data dictionary cache for upcoming CREATE INDEX operation. We need stubs for the new indexes, so that we can keep track of changes to the table during online index creation. Also, crash recovery would drop any indexes that were incomplete at the time of the crash. handler::inplace_alter_table In InnoDB, this method is used for creating secondary indexes or for rebuilding the table. This is the ‘main’ phase that can be executed online (with concurrent writes to the table). handler::commit_inplace_alter_table This is where the operation is committed or rolled back. Here, InnoDB would drop any indexes, rename any columns, drop or add foreign keys, and finalize a table rebuild or index creation. It would also discard any logs that were set up for online index creation or table rebuild. The prepare and commit phases require an exclusive lock, blocking all access to the table. If MySQL times out while upgrading the table meta-data lock for the commit phase, it will roll back the ALTER TABLE operation. In MySQL 5.6, data definition language operations are still not fully atomic, because the data dictionary is split. Part of it is inside InnoDB data dictionary tables. Part of the information is only available in the *.frm file, which is not covered by any crash recovery log. But, there is a single commit phase inside the storage engine. Online Secondary Index Creation It may occur that an index needs to be created on a new column to speed up queries. But, it may be unacceptable to block modifications on the table while creating the index. It turns out that it is conceptually not so hard to support online index creation. All we need is some more execution phases: Set up a stub for the index, for logging changes. Scan the table for index records. Sort the index records. Bulk load the index records. Apply the logged changes. Replace the stub with the actual index. Threads that modify the table will log the operations to the logs of each index that is being created. Errors, such as log overflow or uniqueness violations, will only be flagged by the ALTER TABLE thread. The log is conceptually similar to the InnoDB change buffer. The bulk load of index records will bypass record locking. We still generate redo log for writing the index pages. It would suffice to log page allocations only, and to flush the index pages from the buffer pool to the file system upon completion. Native ALTER TABLE Starting with MySQL 5.6, InnoDB supports most ALTER TABLE operations natively. The notable exceptions are changes to the column type, ADD FOREIGN KEY except when foreign_key_checks=0, and changes to tables that contain FULLTEXT indexes. The keyword ALGORITHM=INPLACE is somewhat misleading, because certain operations cannot be performed in-place. For example, changing the ROW_FORMAT of a table requires a rebuild. Online operation (LOCK=NONE) is not allowed in the following cases: when adding an AUTO_INCREMENT column, when the table contains FULLTEXT indexes or a hidden FTS_DOC_ID column, or when there are FOREIGN KEY constraints referring to the table, with ON…CASCADE or ON…SET NULL option. The FOREIGN KEY limitations are needed, because MySQL does not acquire meta-data locks on the child or parent tables when executing SQL statements. Theoretically, InnoDB could support operations like ADD COLUMN and DROP COLUMN in-place, by lazily converting the table to a newer format. This would require that the data dictionary keep multiple versions of the table definition. For simplicity, we will copy the entire table, even for DROP COLUMN. The bulk copying of the table will bypass record locking and undo logging. For facilitating online operation, a temporary log will be associated with the clustered index of table. Threads that modify the table will also write the changes to the log. When altering the table, we skip all records that have been marked for deletion. In this way, we can simply discard any undo log records that were not yet purged from the original table. Off-page columns, or BLOBs, are an important consideration. We suspend the purge of delete-marked records if it would free any off-page columns from the old table. This is because the BLOBs can be needed when applying changes from the log. We have special logging for handling the ROLLBACK of an INSERT that inserted new off-page columns. This is because the columns will be freed at rollback.

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  • 4.8M wasn't enough so we went for 5.055M tpmc with Unbreakable Enterprise Kernel r2 :-)

    - by wcoekaer
    We released a new set of benchmarks today. One is an updated tpc-c from a few months ago where we had just over 4.8M tpmc at $0.98 and we just updated it to go to 5.05M and $0.89. The other one is related to Java Middleware performance. You can find the press release here. Now, I don't want to talk about the actual relevance of the benchmark numbers, as I am not in the benchmark team. I want to talk about why these numbers and these efforts, unrelated to what they mean to your workload, matter to customers. The actual benchmark effort is a very big, long, expensive undertaking where many groups work together as a big virtual team. Having the virtual team be within a single company of course helps tremendously... We already start with a very big server setup with tons of storage, many disks, lots of ram, lots of cpu's, cores, threads, large database setups. Getting the whole setup going to start tuning, by itself, is no easy task, but then the real fun starts with tuning the system for optimal performance -and- stability. A benchmark is not just revving an engine at high rpm, it's actually hitting the circuit. The tests require long runs, require surviving availability tests, such as surviving crashes -and- recovery under load. In the TPC-C example, the x4800 system had 4TB ram, 160 threads (8 sockets, hyperthreaded, 10 cores/socket), tons of storage attached, tons of luns visible to the OS. flash storage, non flash storage... many things at high scale that all have to be perfectly synchronized. During this process, we find bugs, we fix bugs, we find performance issues, we fix performance issues, we find interesting potential features to investigate for the future, we start new development projects for future releases and all this goes back into the products. As more and more customers, for Oracle Linux, are running larger and larger, faster and faster, more mission critical, higher available databases..., these things are just absolutely critical. Unrelated to what anyone's specific opinion is about tpc-c or tpc-h or specjenterprise etc, there is a ton of effort that the customer benefits from. All this work makes Oracle Linux and/or Oracle Solaris better platforms. Whether it's faster, more stable, more scalable, more resilient. It helps. Another point that I always like to re-iterate around UEK and UEK2 : we have our kernel source git repository online. Complete changelog of the mainline kernel, and our changes, easy to pull, easy to dissect, easy to know what went in when, why and where. No need to go log into a website and manually click through pages to hopefully discover changes or patches. No need to untar 2 tar balls and run a diff.

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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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  • Red Gate Software announces speaker line up for US SQL in the City tour

    SQL in the City is a free, full day training and networking event for database professionals. After the success of last year’s event, Red Gate has expanded the event to cover six cities from sea to shining sea, including: New York, Austin, San Francisco, Chicago, Boston, and Seattle. Compress live data by 73% Red Gate's SQL Storage Compress reduces the size of live SQL Server databases, saving you disk space and storage costs. Learn more.

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  • Disk Is Cheap! ORLY?

    People often conclude that the cheap price of storage is a license to use as much as possible, but there is a cost. Solomon Rutzky talks about the issues you may face if you are not careful with your storage decisions. Join SQL Backup’s 35,000+ customers to compress and strengthen your backups "SQL Backup will be a REAL boost to any DBA lucky enough to use it." Jonathan Allen. Download a free trial now.

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  • CTERA Adds Data Protection to Linux File Systems

    <b>Enterprise Storage Forum: </b>"CTERA Networks is giving the Linux Ext3 file system additional data protection in the form of new snapshot capabilities. The file system is also the basis of the company's Cloud-Attached Storage appliances, the C200 and CloudPlug."

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  • Oracle Magazine - Sep/Oct 2010

    Oracle Magazine Sep/Oct features articles on Oracle Exadata, Database Security, Oracle Enterprise Manager 11g, PL/Scope to analyze your PL/SQL, Using Oracle Essbase Release 11.1.2 Aggregate Storage Option Databases, Oracle Application Express 4.0 Websheets, Oracle Automatic Storage Management disk groups, Tom Kyte revisits a classic, recounts Cardinality Feedback, and remembers SQL*Plus and much more.

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  • Showing ZFS some LOVE

    - by Kristin Rose
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* 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;} L is for the way you look at us, and O because we’re Oracle, but V is very, very, extra ordinary, and E, well that’s obvious… E is because Oracle’s new Sun ZFS Storage Appliance is Excellent, and here at OPN, we like spell out the obvious!  If you haven’t already heard, the Sun ZFS Appliance has “A simple, GUI-driven setup and configuration, solid price-performance and world-class Oracle support behind it. The CRN Test Center recommends the Sun ZFS Storage”. Read more about what CRN said here. Oracle's Sun ZFS Appliance family delivers enterprise-class network attached storage (NAS) capabilities with leading Oracle integration, simplicity, efficiency, performance, and TCO.  The systems offer an easy way to manage and expand your storage environment at a lower cost, with more efficiency, better data integrity, and higher performance when compared with competitive NAS offerings. Did we mention that set up, including configuring, will take you less than an hour since it all comes in one box and is so darn simple to use? So if you L-O-V-E what you’re hearing about Oracle’s Sun Z-F-S, learn more by watching the video below, and visiting any of our available resources . It Had to Be You, The OPN Communications Team

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  • 13.10 upgrade dropping wifi [on hold]

    - by Daryl
    Almost a complete newb here. After my last upgrade from 12.04 to 13.10 my wifi now randomly drops. The only way I can get a signal back is a shutdown and restart otherwise it shows no network is even available to connect to. Had no problems until the upgrade. Any help would be appreciated. H/W path Device Class Description ==================================================== system h8-1534 (H2N64AA#ABA) /0 bus 2AC8 /0/0 memory 64KiB BIOS /0/4 processor AMD FX(tm)-6200 Six-Core Processor /0/4/5 memory 288KiB L1 cache /0/4/6 memory 6MiB L2 cache /0/4/7 memory 8MiB L3 cache /0/d memory 10GiB System Memory /0/d/0 memory DIMM Synchronous [empty] /0/d/1 memory 4GiB DIMM DDR3 Synchronous 1600 MHz (0.6 ns) /0/d/2 memory 2GiB DIMM DDR3 Synchronous 1600 MHz (0.6 ns) /0/d/3 memory 4GiB DIMM DDR3 Synchronous 1600 MHz (0.6 ns) /0/100 bridge RD890 PCI to PCI bridge (external gfx0 port B) /0/100/0.2 generic RD990 I/O Memory Management Unit (IOMMU) /0/100/2 bridge RD890 PCI to PCI bridge (PCI express gpp port B) /0/100/2/0 display Turks PRO [Radeon HD 7570] /0/100/2/0.1 multimedia Turks/Whistler HDMI Audio [Radeon HD 6000 Series] /0/100/5 bridge RD890 PCI to PCI bridge (PCI express gpp port E) /0/100/5/0 bus TUSB73x0 SuperSpeed USB 3.0 xHCI Host Controller /0/100/11 storage SB7x0/SB8x0/SB9x0 SATA Controller [RAID5 mode] /0/100/12 bus SB7x0/SB8x0/SB9x0 USB OHCI0 Controller /0/100/12.2 bus SB7x0/SB8x0/SB9x0 USB EHCI Controller /0/100/13 bus SB7x0/SB8x0/SB9x0 USB OHCI0 Controller /0/100/13.2 bus SB7x0/SB8x0/SB9x0 USB EHCI Controller /0/100/14 bus SBx00 SMBus Controller /0/100/14.2 multimedia SBx00 Azalia (Intel HDA) /0/100/14.3 bridge SB7x0/SB8x0/SB9x0 LPC host controller /0/100/14.4 bridge SBx00 PCI to PCI Bridge /0/100/14.5 bus SB7x0/SB8x0/SB9x0 USB OHCI2 Controller /0/100/15 bridge SB700/SB800/SB900 PCI to PCI bridge (PCIE port 0) /0/100/15.1 bridge SB700/SB800/SB900 PCI to PCI bridge (PCIE port 1) /0/100/15.2 bridge SB900 PCI to PCI bridge (PCIE port 2) /0/100/15.2/0 wlan0 network RT3290 Wireless 802.11n 1T/1R PCIe /0/100/15.2/0.1 generic RT3290 Bluetooth /0/100/15.3 bridge SB900 PCI to PCI bridge (PCIE port 3) /0/100/15.3/0 eth0 network RTL8111/8168/8411 PCI Express Gigabit Ethernet Controller /0/100/16 bus SB7x0/SB8x0/SB9x0 USB OHCI0 Controller /0/100/16.2 bus SB7x0/SB8x0/SB9x0 USB EHCI Controller /0/101 bridge Family 15h Processor Function 0 /0/102 bridge Family 15h Processor Function 1 /0/103 bridge Family 15h Processor Function 2 /0/104 bridge Family 15h Processor Function 3 /0/105 bridge Family 15h Processor Function 4 /0/106 bridge Family 15h Processor Function 5 /0/1 scsi0 storage /0/1/0.0.0 /dev/sda disk 1TB WDC WD1002FAEX-0 /0/1/0.0.0/1 volume 189MiB Windows FAT volume /0/1/0.0.0/2 /dev/sda2 volume 244MiB data partition /0/1/0.0.0/3 /dev/sda3 volume 931GiB LVM Physical Volume /0/2 scsi2 storage /0/2/0.0.0 /dev/cdrom disk DVD A DH16ACSHR /0/3 scsi6 storage /0/3/0.0.0 /dev/sdb disk SCSI Disk /0/3/0.0.1 /dev/sdc disk SCSI Disk /0/3/0.0.2 /dev/sdd disk SCSI Disk /0/3/0.0.3 /dev/sde disk MS/MS-Pro /0/3/0.0.3/0 /dev/sde disk /1 power Standard Efficiency I apologize for my newbness. I hope this is enough info for the hardware. Thanks Bruno for pointing out I needed to add more info. If I am lacking anything else please let me know and I'll post it.

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  • Restructuring a large Chrome Extension/WebApp

    - by A.M.K
    I have a very complex Chrome Extension that has gotten too large to maintain in its current format. I'd like to restructure it, but I'm 15 and this is the first webapp or extension of it's type I've built so I have no idea how to do it. TL;DR: I have a large/complex webapp I'd like to restructure and I don't know how to do it. Should I follow my current restructure plan (below)? Does that sound like a good starting point, or is there a different approach that I'm missing? Should I not do any of the things I listed? While it isn't relevant to the question, the actual code is on Github and the extension is on the webstore. The basic structure is as follows: index.html <html> <head> <link href="css/style.css" rel="stylesheet" /> <!-- This holds the main app styles --> <link href="css/widgets.css" rel="stylesheet" /> <!-- And this one holds widget styles --> </head> <body class="unloaded"> <!-- Low-level base elements are "hardcoded" here, the unloaded class is used for transitions and is removed on load. i.e: --> <div class="tab-container" tabindex="-1"> <!-- Tab nav --> </div> <!-- Templates for all parts of the application and widgets are stored as elements here. I plan on changing these to <script> elements during the restructure since <template>'s need valid HTML. --> <template id="template.toolbar"> <!-- Template content --> </template> <!-- Templates end --> <!-- Plugins --> <script type="text/javascript" src="js/plugins.js"></script> <!-- This contains the code for all widgets, I plan on moving this online and downloading as necessary soon. --> <script type="text/javascript" src="js/widgets.js"></script> <!-- This contains the main application JS. --> <script type="text/javascript" src="js/script.js"></script> </body> </html> widgets.js (initLog || (window.initLog = [])).push([new Date().getTime(), "A log is kept during page load so performance can be analyzed and errors pinpointed"]); // Widgets are stored in an object and extended (with jQuery, but I'll probably switch to underscore if using Backbone) as necessary var Widgets = { 1: { // Widget ID, this is set here so widgets can be retreived by ID id: 1, // Widget ID again, this is used after the widget object is duplicated and detached size: 3, // Default size, medium in this case order: 1, // Order shown in "store" name: "Weather", // Widget name interval: 300000, // Refresh interval nicename: "weather", // HTML and JS safe widget name sizes: ["tiny", "small", "medium"], // Available widget sizes desc: "Short widget description", settings: [ { // Widget setting specifications stored as an array of objects. These are used to dynamically generate widget setting popups. type: "list", nicename: "location", label: "Location(s)", placeholder: "Enter a location and press Enter" } ], config: { // Widget settings as stored in the tabs object (see script.js for storage information) size: "medium", location: ["San Francisco, CA"] }, data: {}, // Cached widget data stored locally, this lets it work offline customFunc: function(cb) {}, // Widgets can optionally define custom functions in any part of their object refresh: function() {}, // This fetches data from the web and caches it locally in data, then calls render. It gets called after the page is loaded for faster loads render: function() {} // This renders the widget only using information from data, it's called on page load. } }; script.js (initLog || (window.initLog = [])).push([new Date().getTime(), "These are also at the end of every file"]); // Plugins, extends and globals go here. i.e. Number.prototype.pad = .... var iChrome = function(refresh) { // The main iChrome init, called with refresh when refreshing to not re-run libs iChrome.Status.log("Starting page generation"); // From now on iChrome.Status.log is defined, it's used in place of the initLog iChrome.CSS(); // Dynamically generate CSS based on settings iChrome.Tabs(); // This takes the tabs stored in the storage (see fetching below) and renders all columns and widgets as necessary iChrome.Status.log("Tabs rendered"); // These will be omitted further along in this excerpt, but they're used everywhere // Checks for justInstalled => show getting started are run here /* The main init runs the bare minimum required to display the page, this sets all non-visible or instantly need things (such as widget dragging) on a timeout */ iChrome.deferredTimeout = setTimeout(function() { iChrome.deferred(refresh); // Pass refresh along, see above }, 200); }; iChrome.deferred = function(refresh) {}; // This calls modules one after the next in the appropriate order to finish rendering the page iChrome.Search = function() {}; // Modules have a base init function and are camel-cased and capitalized iChrome.Search.submit = function(val) {}; // Methods within modules are camel-cased and not capitalized /* Extension storage is async and fetched at the beginning of plugins.js, it's then stored in a variable that iChrome.Storage processes. The fetcher checks to see if processStorage is defined, if it is it gets called, otherwise settings are left in iChromeConfig */ var processStorage = function() { iChrome.Storage(function() { iChrome.Templates(); // Templates are read from their elements and held in a cache iChrome(); // Init is called }); }; if (typeof iChromeConfig == "object") { processStorage(); } Objectives of the restructure Memory usage: Chrome apparently has a memory leak in extensions, they're trying to fix it but memory still keeps on getting increased every time the page is loaded. The app also uses a lot on its own. Code readability: At this point I can't follow what's being called in the code. While rewriting the code I plan on properly commenting everything. Module interdependence: Right now modules call each other a lot, AFAIK that's not good at all since any change you make to one module could affect countless others. Fault tolerance: There's very little fault tolerance or error handling right now. If a widget is causing the rest of the page to stop rendering the user should at least be able to remove it. Speed is currently not an issue and I'd like to keep it that way. How I think I should do it The restructure should be done using Backbone.js and events that call modules (i.e. on storage.loaded = init). Modules should each go in their own file, I'm thinking there should be a set of core files that all modules can rely on and call directly and everything else should be event based. Widget structure should be kept largely the same, but maybe they should also be split into their own files. AFAIK you can't load all templates in a folder, therefore they need to stay inline. Grunt should be used to merge all modules, plugins and widgets into one file. Templates should also all be precompiled. Question: Should I follow my current restructure plan? Does that sound like a good starting point, or is there a different approach that I'm missing? Should I not do any of the things I listed? Do applications written with Backbone tend to be more intensive (memory and speed) than ones written in Vanilla JS? Also, can I expect to improve this with a proper restructure or is my current code about as good as can be expected?

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  • PROUHD: RAID for the end-user

    <b>Linuxconfig:</b> "Therefore, there is currently no storage solution that manages heterogeneous storage devices efficiently. In this article, we propose such a solution and we call it PROUHD (Pool of RAID Over User Heterogeneous Devices)."

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