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  • iPhone app works hundreds of times, then crashes from memory error on startup, then never works unti

    - by peter
    I have a Cocos2d/openGL iPhone game. It's a universal app and I'm dealing with an occasional but nasty error on the iPad. We are loading a lot of textures up front (3 2048x2048 textures). I'm working on reducing this up front load, but what worries me is I really don't understand the root cause of this crash that permanently breaks the app. This is the deal: 1. App works fine for hundreds of plays on the iPad 2. Eventually (I'm guessing due to other programs using up some memory and not letting go or whatever) the app starts crashing on startup. It just closes again in the middle of loading. 3. The App will now never work again on that iPad, closing immediately every time, until the iPad is restarted. Obviously my app is demanding too much memory up front to work reliably every time, I get that. What I don't get is why when it fails once, it has failed forever until the iPad is restarted. Can anyone explain what is going on here? EDIT: forgot to add organizer crash lags just say low memory, like this every time (I changed my app name to MyAppName below). Again, I know it's low memory, but why does it stay low memory until restart?: Incident Identifier: E7A2507C-3FB1-4E3B-B315-09F094236541 CrashReporter Key: 0fda9d667f2c6073f20a76809aa25438b6854d15 OS Version: iPhone OS 3.2 (7B367) Date: 2010-04-30 16:59:44 -0400 Free pages: 437 Wired pages: 17228 Purgeable pages: 0 Largest process: MyAppName Processes Name UUID Count resident pages MyAppName <6307ce41802850944baa78d29224fa7f> 22385 (jettisoned) (active) mediaserverd <ea8bac28b06fe3980fdd44b5caceb563> 242 DTMobileIS <a0f651e43881e66f50f8a95abea72921> 5826 notification_pro <4c9a7ee0a5bbe160465991228f2d2f2e> 67 syslog_relay <4ceaed776d2df957fa130712f4ef21d0> 66 notification_pro <4c9a7ee0a5bbe160465991228f2d2f2e> 67 notification_pro <4c9a7ee0a5bbe160465991228f2d2f2e> 67 afcd <4f3c9566e33b4463f05603d990584e5d> 72 ptpd <83de0f774bd6553d513ae9e19b0f9b56> 181 syslogd <66247e305d5c0bf6f1ce1cc950653263> 81 lsd <a4d852c1c8da2b3d231bdc90887b52ba> 130 iapd <a8534cbde4b90ad5915dd26ab03ff3e3> 204 notifyd <5e9d5bee7c3eae1c8b494c79eb11406e> 71 BTServer <64e4a6ea6b1240db2331e05a29caa862> 108 CommCenter <97bf297944ac4bde19bcee96dd23bd5f> 181 SpringBoard <c7a5904c12db7b14334a4edaa4cabaa9> 5339 (active) configd <aca9fa3380322669164fd6b1a3864300> 373 fairplayd.K48 <2d997ffca1a568f9c5400ac32d8f0782> 84 locationd <dd1ea88105c62173908ce767db5c4d37> 599 mDNSResponder <820560222d47a1f2a0dce98a7f8a9721> 108 lockdownd <497fd54c79a680bf29f5d9320f514613> 303 MobileStorageMou <c277b79c2157c4dc5cfc5c3ca35bd5f2> 69 launchd <66972eee4d865c4383b33d985d22994b> 98 **End**

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  • JLabel not displaying all the characters even after dynamically changing font size

    - by wniroshan
    Hi all, I am trying to fit a sentence that changes often, in to a few jlabels. Widths of my 3 jlabels stay unchanged all the time. What I am doing is changing the font size so all the characters can fit with out non being out of the display range of the labels. What I do is call below code snippet when ever sentence is changed. Here is my code String sentence = "Some long sentence"; int SentenceLength = sentence.length(); int FontSize = 0; // sum of widths of the three labels int TotalLblLength=lbl_0ValueInWords.getWidth()+lbl_1ValueInWords.getWidth()+lbl_1ValueInWords.getWidth(); /*decide the font size so that all the characters can be displayed with out exceeding the display renge(horizontal) of the 3 labels Inconsolata -> monopace font font size == width of the font*2 (something I observed, not sure if this is true always) */ FontSize=(TotalLblLength/SentenceLength)*2; // max font size is 20 - based on label height FontSize=(FontSize>20)?20:FontSize; lbl_0ValueInWords.setFont(new java.awt.Font("Inconsolata", 0,FontSize)); lbl_1ValueInWords.setFont(new java.awt.Font("Inconsolata", 0,FontSize)); lbl_2ValueInWords.setFont(new java.awt.Font("Inconsolata", 0,FontSize)); int CharCount_lbl0 = width_lbl0 / (FontSize / 2); int CharCount_lbl1 = width_lbl1 / (FontSize / 2); int CharsCount_lbl2 = width_lbl2 / (FontSize / 2); /*Set texts of each label if sentence has more than the number of characters that can fit in the 1st label, excessive characters are moved to the 2nd label. same goes for the 2nd and 3rd labels*/ if (SentenceLength > CharCount_lbl0) { lbl_0ValueInWords.setText(sentence.substring(0, CharCount_lbl0)); if (SentenceLength > CharCount_lbl0 + CharCount_lbl1) { lbl_1ValueInWords.setText(sentence.substring(CharCount_lbl0, CharCount_lbl0 + CharCount_lbl1)); lbl_2ValueInWords.setText(sentence.substring(CharCount_lbl0 + CharCount_lbl1, SentenceLength)); } else { lbl_1ValueInWords.setText(sentence.substring(CharCount_lbl0, SentenceLength)); } } else { lbl_0ValueInWords.setText(sentence); } But even after resetting font size sometimes the last character goes out of the display range. I have removed margines from the jlabels that may cause this. This happens for random length sentences. I can solve the problem for the application by reducing label width used for the calculations(hopefully) Can anyone explain me the reason? Could be because of some defect in the fonts symmetry?

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  • How to properly preload images, js and css files?

    - by Kenny Bones
    Hi, I'm creating a website from scratch and I was really into this in the late 90's but the web has changed alot since then! And I'm more of a designer so when I started putting this site together, I basically did a system of php includes to make the site more "dynamic" When you first visit the site, you'll be presented to a logon screen, if you're not already logged on (cookies). If you're not logged on, a page called access.php is introdused. I thought I'd preload the most heavy images at this point. So that when the user is done logging on, the images are already cached. And this is working as I want. But I still notice that the biggest image still isn't rendered immediatly anyway. So it's seems kinda pointless. All of this has made me rethink how the site is structured and how scripts and css files are loaded. Using FireBug and YSlow with Firefox I see a few pointers like expires headers and reducing the size of each script. But is this really the culprit? For example, would this be really really stupid in the main index.php? The entire site is basically structured like this <?php require("dbconnect.php"); ?> <?php include ("head.php"); ?> And below this is basically just the body and the content of the site. Head.php however consists of the doctype, head portions, linking of two css style sheets, jQuery library, jQuery validation engine, Cufon and Cufon font file, and then the small Cufon.Replace snippet. The rest of the body comes with the index.php file, but at the bottom of this again is an include of a file called "footer.php" which basically consists of loading of a couple of jsLoader scripts and a slidepanel and then a js function. All of this makes the end page source look like a typical complete webpage, but I'm wondering if any of you can see immediatly that "this is really really stupid" and "don't do that, do this instead" etc. :) Are includes a bad way to go? This site is also pretty image intensive and I can probably do a little more optimization. But I don't think that's its the primary culprit. YSlow gives me a report of what takes up the most space: doc(1) - 5.8K js(5) - 198.7K css(2) - 5.6K cssimage(8) - 634.7K image(6) - 110.8K I know it looks like it's cssimage(8) that weighs the most, but I've already preloaded these images from before and it doesn't really affect the rendering.

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  • How do I query delegation properties of an active directory user account?

    - by Mark J Miller
    I am writing a utility to audit the configuration of a WCF service. In order to properly pass credentials from the client, thru the WCF service back to the SQL back end the domain account used to run the service must be configured in Active Directory with the setting "Trust this user for delegation" (Properties - "Delegation" tab). Using C#, how do I access the settings on this tab in Active Directory. I've spent the last 5 hours trying to track this down on the web and can't seem to find it. Here's what I've done so far: using (Domain domain = Domain.GetCurrentDomain()) { Console.WriteLine(domain.Name); // get domain "dev" from MSSQLSERVER service account DirectoryEntry ouDn = new DirectoryEntry("LDAP://CN=Users,dc=dev,dc=mydomain,dc=lcl"); DirectorySearcher search = new DirectorySearcher(ouDn); // get sAMAccountName "dev.services" from MSSQLSERVER service account search.Filter = "(sAMAccountName=dev.services)"; search.PropertiesToLoad.Add("displayName"); search.PropertiesToLoad.Add("userAccountControl"); SearchResult result = search.FindOne(); if (result != null) { Console.WriteLine(result.Properties["displayName"][0]); DirectoryEntry entry = result.GetDirectoryEntry(); int userAccountControlFlags = (int)entry.Properties["userAccountControl"].Value; if ((userAccountControlFlags & (int)UserAccountControl.TRUSTED_FOR_DELEGATION) == (int)UserAccountControl.TRUSTED_FOR_DELEGATION) Console.WriteLine("TRUSTED_FOR_DELEGATION"); else if ((userAccountControlFlags & (int)UserAccountControl.TRUSTED_TO_AUTH_FOR_DELEGATION) == (int)UserAccountControl.TRUSTED_TO_AUTH_FOR_DELEGATION) Console.WriteLine("TRUSTED_TO_AUTH_FOR_DELEGATION"); else if ((userAccountControlFlags & (int)UserAccountControl.NOT_DELEGATED) == (int)UserAccountControl.NOT_DELEGATED) Console.WriteLine("NOT_DELEGATED"); foreach (PropertyValueCollection pvc in entry.Properties) { Console.WriteLine(pvc.PropertyName); for (int i = 0; i < pvc.Count; i++) { Console.WriteLine("\t{0}", pvc[i]); } } } } The "userAccountControl" does not seem to be the correct property. I think it is tied to the "Account Options" section on the "Account" tab, which is not what we're looking for but this is the closest I've gotten so far. The justification for all this is: We do not have permission to setup the service in QA or in Production, so along with our written instructions (which are notoriously only followed in partial) I am creating a tool that will audit the setup (WCF and SQL) to determine if the setup is correct. This will allow the person deploying the service to run this utility and verify everything is setup correctly - saving us hours of headaches and reducing downtime during deployment.

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  • change maxlength depending of the option selected

    - by tuner3000
    I've seen similar questions posted and tried to change them to meet my needs but I don't know enough about javascript to do it. I need that when a user change the dropdown select, the "titre text field" maxlength is dynamically changed a, b c and d max maxlength should be 40 and e maxlength should be 2 my code is below, I don't know why but it is not working correctly: <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> <html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /> <title>title page</title> </head> <body> <script type="text/javascript"> function changeValue(dropdown) { var option = dropdown.options[dropdown.selectedIndex].value, field = document.getElementById('titre'); if (option == 'a' || option == 'b' || option == 'c' || option == 'd') { field.maxLength = 40; } else if (option == 'e') { field.value = field.value.substr(0, 2); // before reducing the maxlength, make sure it contains at most two characters; you could also reset the value altogether field.maxLength = 2; } }? </script> <form action="converter.php" method="post"> <h2>Feel all field below:</h2> <div> Title: <input type="texte" name="titre" id="titre" maxLength="40"/> Format: <select id="format" name="format" onchange="changeValue(this);"> <option value="a">A</option> <option value="b">B</option> <option value="c">C</option> <option value="d">D</option> <option value="e">E</option> </select> </div> <div> <textarea name="texte" style="width: 415px; height: 155px;"></textarea> </div> <div> <input type="submit" value="OK" /> </div> </form> </body> </html>

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  • Python: (sampling with replacement): efficient algorithm to extract the set of UNIQUE N-tuples from a set

    - by Homunculus Reticulli
    I have a set of items, from which I want to select DISSIMILAR tuples (more on the definition of dissimilar touples later). The set could contain potentially several thousand items, although typically, it would contain only a few hundreds. I am trying to write a generic algorithm that will allow me to select N items to form an N-tuple, from the original set. The new set of selected N-tuples should be DISSIMILAR. A N-tuple A is said to be DISSIMILAR to another N-tuple B if and only if: Every pair (2-tuple) that occurs in A DOES NOT appear in B Note: For this algorithm, A 2-tuple (pair) is considered SIMILAR/IDENTICAL if it contains the same elements, i.e. (x,y) is considered the same as (y,x). This is a (possible variation on the) classic Urn Problem. A trivial (pseudocode) implementation of this algorithm would be something along the lines of def fetch_unique_tuples(original_set, tuple_size): while True: # randomly select [tuple_size] items from the set to create first set # create a key or hash from the N elements and store in a set # store selected N-tuple in a container if end_condition_met: break I don't think this is the most efficient way of doing this - and though I am no algorithm theorist, I suspect that the time for this algorithm to run is NOT O(n) - in fact, its probably more likely to be O(n!). I am wondering if there is a more efficient way of implementing such an algo, and preferably, reducing the time to O(n). Actually, as Mark Byers pointed out there is a second variable m, which is the size of the number of elements being selected. This (i.e. m) will typically be between 2 and 5. Regarding examples, here would be a typical (albeit shortened) example: original_list = ['CAGG', 'CTTC', 'ACCT', 'TGCA', 'CCTG', 'CAAA', 'TGCC', 'ACTT', 'TAAT', 'CTTG', 'CGGC', 'GGCC', 'TCCT', 'ATCC', 'ACAG', 'TGAA', 'TTTG', 'ACAA', 'TGTC', 'TGGA', 'CTGC', 'GCTC', 'AGGA', 'TGCT', 'GCGC', 'GCGG', 'AAAG', 'GCTG', 'GCCG', 'ACCA', 'CTCC', 'CACG', 'CATA', 'GGGA', 'CGAG', 'CCCC', 'GGTG', 'AAGT', 'CCAC', 'AACA', 'AATA', 'CGAC', 'GGAA', 'TACC', 'AGTT', 'GTGG', 'CGCA', 'GGGG', 'GAGA', 'AGCC', 'ACCG', 'CCAT', 'AGAC', 'GGGT', 'CAGC', 'GATG', 'TTCG'] Select 3-tuples from the original list should produce a list (or set) similar to: [('CAGG', 'CTTC', 'ACCT') ('CAGG', 'TGCA', 'CCTG') ('CAGG', 'CAAA', 'TGCC') ('CAGG', 'ACTT', 'ACCT') ('CAGG', 'CTTG', 'CGGC') .... ('CTTC', 'TGCA', 'CAAA') ] [[Edit]] Actually, in constructing the example output, I have realized that the earlier definition I gave for UNIQUENESS was incorrect. I have updated my definition and have introduced a new metric of DISSIMILARITY instead, as a result of this finding.

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  • Python: (sampling with replacement): efficient algorithm to extract the set of DISSIMILAR N-tuples from a set

    - by Homunculus Reticulli
    I have a set of items, from which I want to select DISSIMILAR tuples (more on the definition of dissimilar touples later). The set could contain potentially several thousand items, although typically, it would contain only a few hundreds. I am trying to write a generic algorithm that will allow me to select N items to form an N-tuple, from the original set. The new set of selected N-tuples should be DISSIMILAR. A N-tuple A is said to be DISSIMILAR to another N-tuple B if and only if: Every pair (2-tuple) that occurs in A DOES NOT appear in B Note: For this algorithm, A 2-tuple (pair) is considered SIMILAR/IDENTICAL if it contains the same elements, i.e. (x,y) is considered the same as (y,x). This is a (possible variation on the) classic Urn Problem. A trivial (pseudocode) implementation of this algorithm would be something along the lines of def fetch_unique_tuples(original_set, tuple_size): while True: # randomly select [tuple_size] items from the set to create first set # create a key or hash from the N elements and store in a set # store selected N-tuple in a container if end_condition_met: break I don't think this is the most efficient way of doing this - and though I am no algorithm theorist, I suspect that the time for this algorithm to run is NOT O(n) - in fact, its probably more likely to be O(n!). I am wondering if there is a more efficient way of implementing such an algo, and preferably, reducing the time to O(n). Actually, as Mark Byers pointed out there is a second variable m, which is the size of the number of elements being selected. This (i.e. m) will typically be between 2 and 5. Regarding examples, here would be a typical (albeit shortened) example: original_list = ['CAGG', 'CTTC', 'ACCT', 'TGCA', 'CCTG', 'CAAA', 'TGCC', 'ACTT', 'TAAT', 'CTTG', 'CGGC', 'GGCC', 'TCCT', 'ATCC', 'ACAG', 'TGAA', 'TTTG', 'ACAA', 'TGTC', 'TGGA', 'CTGC', 'GCTC', 'AGGA', 'TGCT', 'GCGC', 'GCGG', 'AAAG', 'GCTG', 'GCCG', 'ACCA', 'CTCC', 'CACG', 'CATA', 'GGGA', 'CGAG', 'CCCC', 'GGTG', 'AAGT', 'CCAC', 'AACA', 'AATA', 'CGAC', 'GGAA', 'TACC', 'AGTT', 'GTGG', 'CGCA', 'GGGG', 'GAGA', 'AGCC', 'ACCG', 'CCAT', 'AGAC', 'GGGT', 'CAGC', 'GATG', 'TTCG'] # Select 3-tuples from the original list should produce a list (or set) similar to: [('CAGG', 'CTTC', 'ACCT') ('CAGG', 'TGCA', 'CCTG') ('CAGG', 'CAAA', 'TGCC') ('CAGG', 'ACTT', 'ACCT') ('CAGG', 'CTTG', 'CGGC') .... ('CTTC', 'TGCA', 'CAAA') ] [[Edit]] Actually, in constructing the example output, I have realized that the earlier definition I gave for UNIQUENESS was incorrect. I have updated my definition and have introduced a new metric of DISSIMILARITY instead, as a result of this finding.

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  • Improved way to build nested array of unique values in javascript

    - by dualmon
    The setup: I have a nested html table structure that displays hierarchical data, and the individual rows can be hidden or shown by the user. Each row has a dom id that is comprised of the level number plus the primary key for the record type on that level. I have to have both, because each level is from a different database table, so the primary key alone is not unique in the dom. example: id="level-1-row-216" I am storing the levels and rows of the visible elements in a cookie, so that when the page reloads the same rows the user had open are can be shown automatically. I don't store the full map of dom ids, because I'm concerned about it getting too verbose, and I want to keep my cookie under 4Kb. So I convert the dom ids to a compact json object like this, with one property for each level, and a unique array of primary keys under each level: { 1:[231,432,7656], 2:[234,121], 3:[234,2], 4:[222,423], 5:[222] } With this structure stored in a cookie, I feed it to my show function and restore the user's previous disclosure state when the page loads. The area for improvement: I'm looking for better option for reducing my map of id selectors down to this compact format. Here is my function: function getVisibleIds(){ // example dom id: level-1-row-216-sub var ids = $("tr#[id^=level]:visible").map(function() { return this.id; }); var levels = {}; for(var i in ids ) { var id = ids[i]; if (typeof id == 'string'){ if (id.match(/^level/)){ // here we extract the number for level and row var level = id.replace(/.*(level-)(\d*)(.*)/, '$2'); var row = id.replace(/.*(row-)(\d*)(.*)/, '$2'); // *** Improvement here? *** // This works, but it seems klugy. In PHP it's one line (see below): if(levels.hasOwnProperty(level)){ if($.inArray(parseInt(row, 10) ,levels[level]) == -1){ levels[level].push(parseInt(row, 10)); } } else { levels[level] = [parseInt(row, 10)]; } } } } return levels; } If I were doing it in PHP, I'd build the compact array like this, but I can't figure it out in javascript: foreach($ids as $id) { if (/* the criteria */){ $level = /* extract it from $id */; $row = /* extract it from $id */; $levels[$level][$row]; } }

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  • Computer makes hissing noise, turns off after few seconds

    - by Kaustubh P
    I have a problem similar to the questions posted here and here. This is my config: Asus M3N78-EM, with AMD Phenom X3 720 2800 Black Edition, 4GB Transcend DDR2 RAM, Nvidia 9400GT. HD is a 160 GB IDE, and a LG IDE DVD-ROM. The power button is a bit off, I have removed the cover of the switch, and the only way it turns on is just giving the "stick" under the cover a gentle press. It turns on sometimes, and at other times, I have to cut-off the power from the PSU, and try again. I will describe my problem in as detail as possible, please bear with me: The problem has started in the last week, a few months after I changed the to the powerswitch arrangement as described above. The PC makes a hissing noise, and I wasn't able to pin-point the noise source, because of the various other fans. At first, removing the HD, rebooting w/o the HD, turning it off, reconnecting and booting made the problem go away. But of late, it doesn't happen. As suggested in the other questions, I tried reducing the load by disconnecting both the IDE drives, and the problem (noise + turn-off) still occurs. I also connected another 80G IDE HD,today morning, adn it still made that noise, and turned off. I also opened up the PSU, but I couldn't see any fault in that, I tried rotating the fan by blowing into the blades, and with my fingers, but the hissing noise didn't come from there. Or maybe the speed wasn't enough to evoke that noise. A few weeks ago: I had cleaned the Cabinet and had repasted the processor and its fan using some thermal paste. Could that be at fault? I also used a vacuum to blow the dust out of the PSU, could the power have been too much, to maybe offset the fan or something? A label on the PSU says it uses a ball-bearing fan. That only leaves me with the Processor fan and the processor itself. I didn't try removing the processor fan and processor from the motherboard, and then turning the PC on, fearing damage. Will doing so cause any damage? What can I do to localize and pin-point the problem? Also, after a few tries, the Computer starts up. Sometimes it turns of within 2 seconds, sometimes after the POST. Once it turned off at the grub. Another time it booted completely and then turned off. The only way to ensure that the PC wont turn off, is if the hissing noise stops. EDIT: I suspect it to be the Processor/Processor fan, owing to the source of noise. All the config, except for the Cabinet, is just over a year old. EDIT2: I also just remembered, that I had set the "On-power resume" to turn on, i.e. If I supply he PC with power, it will turn itself on, w/o me needing to press the switch. I had done that to workaround the faulty power-switch, as noted above. EDIT3: I calculated the power my system needs, from the antec site, and I just arrived at 292W

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  • NLog Exception Details Renderer

    - by jtimperley
    Originally posted on: http://geekswithblogs.net/jtimperley/archive/2013/07/28/nlog-exception-details-renderer.aspxI recently switch from Microsoft's Enterprise Library Logging block to NLog.  In my opinion, NLog offers a simpler and much cleaner configuration section with better use of placeholders, complemented by custom variables. Despite this, I found one deficiency in my migration; I had lost the ability to simply render all details of an exception into our logs and notification emails. This is easily remedied by implementing a custom layout renderer. Start by extending 'NLog.LayoutRenderers.LayoutRenderer' and overriding the 'Append' method. using System.Text; using NLog; using NLog.Config; using NLog.LayoutRenderers;   [ThreadAgnostic] [LayoutRenderer(Name)] public class ExceptionDetailsRenderer : LayoutRenderer { public const string Name = "exceptiondetails";   protected override void Append(StringBuilder builder, LogEventInfo logEvent) { // Todo: Append details to StringBuilder } }   Now that we have a base layout renderer, we simply need to add the formatting logic to add exception details as well as inner exception details. This is done using reflection with some simple filtering for the properties that are already being rendered. I have added an additional 'Register' method, allowing the definition to be registered in code, rather than in configuration files. This complements by 'LogWrapper' class which standardizes writing log entries throughout my applications. using System; using System.Collections.Generic; using System.Linq; using System.Reflection; using System.Text; using NLog; using NLog.Config; using NLog.LayoutRenderers;   [ThreadAgnostic] [LayoutRenderer(Name)] public sealed class ExceptionDetailsRenderer : LayoutRenderer { public const string Name = "exceptiondetails"; private const string _Spacer = "======================================"; private List<string> _FilteredProperties;   private List<string> FilteredProperties { get { if (_FilteredProperties == null) { _FilteredProperties = new List<string> { "StackTrace", "HResult", "InnerException", "Data" }; }   return _FilteredProperties; } }   public bool LogNulls { get; set; }   protected override void Append(StringBuilder builder, LogEventInfo logEvent) { Append(builder, logEvent.Exception, false); }   private void Append(StringBuilder builder, Exception exception, bool isInnerException) { if (exception == null) { return; }   builder.AppendLine();   var type = exception.GetType(); if (isInnerException) { builder.Append("Inner "); }   builder.AppendLine("Exception Details:") .AppendLine(_Spacer) .Append("Exception Type: ") .AppendLine(type.ToString());   var bindingFlags = BindingFlags.Instance | BindingFlags.Public; var properties = type.GetProperties(bindingFlags); foreach (var property in properties) { var propertyName = property.Name; var isFiltered = FilteredProperties.Any(filter => String.Equals(propertyName, filter, StringComparison.InvariantCultureIgnoreCase)); if (isFiltered) { continue; }   var propertyValue = property.GetValue(exception, bindingFlags, null, null, null); if (propertyValue == null && !LogNulls) { continue; }   var valueText = propertyValue != null ? propertyValue.ToString() : "NULL"; builder.Append(propertyName) .Append(": ") .AppendLine(valueText); }   AppendStackTrace(builder, exception.StackTrace, isInnerException); Append(builder, exception.InnerException, true); }   private void AppendStackTrace(StringBuilder builder, string stackTrace, bool isInnerException) { if (String.IsNullOrEmpty(stackTrace)) { return; }   builder.AppendLine();   if (isInnerException) { builder.Append("Inner "); }   builder.AppendLine("Exception StackTrace:") .AppendLine(_Spacer) .AppendLine(stackTrace); }   public static void Register() { Type definitionType; var layoutRenderers = ConfigurationItemFactory.Default.LayoutRenderers; if (layoutRenderers.TryGetDefinition(Name, out definitionType)) { return; }   layoutRenderers.RegisterDefinition(Name, typeof(ExceptionDetailsRenderer)); LogManager.ReconfigExistingLoggers(); } } For brevity I have removed the Trace, Debug, Warn, and Fatal methods. They are modelled after the Info methods. As mentioned above, note how the log wrapper automatically registers our custom layout renderer reducing the amount of application configuration required. using System; using NLog;   public static class LogWrapper { static LogWrapper() { ExceptionDetailsRenderer.Register(); }   #region Log Methods   public static void Info(object toLog) { Log(toLog, LogLevel.Info); }   public static void Info(string messageFormat, params object[] parameters) { Log(messageFormat, parameters, LogLevel.Info); }   public static void Error(object toLog) { Log(toLog, LogLevel.Error); }   public static void Error(string message, Exception exception) { Log(message, exception, LogLevel.Error); }   private static void Log(string messageFormat, object[] parameters, LogLevel logLevel) { string message = parameters.Length == 0 ? messageFormat : string.Format(messageFormat, parameters); Log(message, (Exception)null, logLevel); }   private static void Log(object toLog, LogLevel logLevel, LogType logType = LogType.General) { if (toLog == null) { throw new ArgumentNullException("toLog"); }   if (toLog is Exception) { var exception = toLog as Exception; Log(exception.Message, exception, logLevel, logType); } else { var message = toLog.ToString(); Log(message, null, logLevel, logType); } }   private static void Log(string message, Exception exception, LogLevel logLevel, LogType logType = LogType.General) { if (exception == null && String.IsNullOrEmpty(message)) { return; }   var logger = GetLogger(logType); // Note: Using the default constructor doesn't set the current date/time var logInfo = new LogEventInfo(logLevel, logger.Name, message); logInfo.Exception = exception; logger.Log(logInfo); }   private static Logger GetLogger(LogType logType) { var loggerName = logType.ToString(); return LogManager.GetLogger(loggerName); }   #endregion   #region LogType private enum LogType { General } #endregion } The following configuration is similar to what is provided for each of my applications. The 'application' variable is all that differentiates the various applications in all of my environments, the rest has been standardized. Depending on your needs to tweak this configuration while developing and debugging, this section could easily be pushed back into code similar to the registering of our custom layout renderer.   <?xml version="1.0"?>   <configuration> <configSections> <section name="nlog" type="NLog.Config.ConfigSectionHandler, NLog"/> </configSections> <nlog xmlns="http://www.nlog-project.org/schemas/NLog.xsd" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <variable name="application" value="Example"/> <targets> <target type="EventLog" name="EventLog" source="${application}" log="${application}" layout="${message}${onexception: ${newline}${exceptiondetails}}"/> <target type="Mail" name="Email" smtpServer="smtp.example.local" from="[email protected]" to="[email protected]" subject="(${machinename}) ${application}: ${level}" body="Machine: ${machinename}${newline}Timestamp: ${longdate}${newline}Level: ${level}${newline}Message: ${message}${onexception: ${newline}${exceptiondetails}}"/> </targets> <rules> <logger name="*" minlevel="Debug" writeTo="EventLog" /> <logger name="*" minlevel="Error" writeTo="Email" /> </rules> </nlog> </configuration>   Now go forward, create your custom exceptions without concern for including their custom properties in your exception logs and notifications.

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  • Issue 15: The Benefits of Oracle Exastack

    - by rituchhibber
         SOLUTIONS FOCUS The Benefits of Oracle Exastack Paul ThompsonDirector, Alliances and Solutions Partner ProgramsOracle EMEA Alliances & Channels RESOURCES -- Oracle PartnerNetwork (OPN) Oracle Exastack Program Oracle Exastack Ready Oracle Exastack Optimized Oracle Exastack Labs and Enablement Resources Oracle Exastack Labs Video Tour SUBSCRIBE FEEDBACK PREVIOUS ISSUES Exastack is a revolutionary programme supporting Oracle independent software vendor partners across the entire Oracle technology stack. Oracle's core strategy is to engineer software and hardware together, and our ISV strategy is the same. At Oracle we design engineered systems that are pre-integrated to reduce the cost and complexity of IT infrastructures while increasing productivity and performance. Oracle innovates and optimises performance at every layer of the stack to simplify business operations, drive down costs and accelerate business innovation. Our engineered systems are optimised to achieve enterprise performance levels that are unmatched in the industry. Faster time to production is achieved by implementing pre-engineered and pre-assembled hardware and software bundles. Our strategy of delivering a single-vendor stack simplifies and reduces costs associated with purchasing, deploying, and supporting IT environments for our customers and partners. In parallel to this core engineered systems strategy, the Oracle Exastack Program enables our Oracle ISV partners to leverage a scalable, integrated infrastructure that delivers their applications tuned, tested and optimised for high-performance. Specifically, the Oracle Exastack Program helps ISVs run their solutions on the Oracle Exadata Database Machine, Oracle Exalogic Elastic Cloud, and Oracle SPARC SuperCluster T4-4 - integrated systems products in which the software and hardware are engineered to work together. These products provide OPN members with a lower cost and high performance infrastructure for database and application workloads across on-premise and cloud based environments. Ready and Optimized Oracle Partners can now leverage our new Oracle Exastack Program to become Oracle Exastack Ready and Oracle Exastack Optimized. Partners can achieve Oracle Exastack Ready status through their support for Oracle Solaris, Oracle Linux, Oracle VM, Oracle Database, Oracle WebLogic Server, Oracle Exadata Database Machine, Oracle Exalogic Elastic Cloud, and Oracle SPARC SuperCluster T4-4. By doing this, partners can demonstrate to their customers that their applications are available on the latest major releases of these products. The Oracle Exastack Ready programme helps customers readily differentiate Oracle partners from lesser software developers, and identify applications that support Oracle engineered systems. Achieving Oracle Exastack Optimized status demonstrates that an OPN member has proven itself against goals for performance and scalability on Oracle integrated systems. This status enables end customers to readily identify Oracle partners that have tested and tuned their solutions for optimum performance on an Oracle Exadata Database Machine, Oracle Exalogic Elastic Cloud, and Oracle SPARC SuperCluster T4-4. These ISVs can display the Oracle Exadata Optimized, Oracle Exalogic Optimized or Oracle SPARC SuperCluster Optimized logos on websites and on all their collateral to show that they have tested and tuned their application for optimum performance. Deliver higher value to customers Oracle's investment in engineered systems enables ISV partners to deliver higher value to customer business processes. New innovations are enabled through extreme performance unachievable through traditional best-of-breed multi-vendor server/software approaches. Core product requirements can be launched faster, enabling ISVs to focus research and development investment on core competencies in order to bring value to market as quickly as possible. Through Exastack, partners no longer have to worry about the underlying product stack, which allows greater focus on the development of intellectual property above the stack. Partners are not burdened by platform issues and can concentrate simply on furthering their applications. The advantage to end customers is that partners can focus all efforts on business functionality, rather than bullet-proofing underlying technologies, and so will inevitably deliver application updates faster. Exastack provides ISVs with a number of flexible deployment options, such as on-premise or Cloud, while maintaining one single code base for applications regardless of customer deployment preference. Customers buying their solutions from Exastack ISVs can therefore be confident in deploying on their own networks, on private clouds or into a public cloud. The underlying platform will support all conceivable deployments, enabling a focus on the ISV's application itself that wouldn't be possible with other vendor partners. It stands to reason that Exastack accelerates time to value as well as lowering implementation costs all round. There is a big competitive advantage in partners being able to offer customers an optimised, pre-configured solution rather than an assortment of components and a suggested fit. Once a customer has decided to buy an Oracle Exastack Ready or Optimized partner solution, it will be up and running without any need for the customer to conduct testing of its own. Operational costs and complexity are also reduced, thanks to streamlined customer support through standardised configurations and pro-active monitoring. 'Engineered to Work Together' is a significant statement of Oracle strategy. It guarantees smoother deployment of a single vendor solution, clear ownership with no finger-pointing and the peace of mind of the Oracle Support Centre underpinning the entire product stack. Next steps Every OPN member with packaged applications must seriously consider taking steps to become Exastack Ready, or Exastack Optimized at the first opportunity. That first step down the track is to talk to an expert on the OPN Portal, at the Oracle Partner Business Center or to discuss the next steps with the closest Oracle account manager. Oracle Exastack lab environments and other technical enablement resources are available for OPN members wishing to further their knowledge of Oracle Exastack and qualify their applications for Oracle Exastack Optimized. New Boot Camps and Guided Learning Paths (GLPs), tailored specifically for ISVs, are available for Oracle Exadata Database Machine, Oracle Exalogic Elastic Cloud, Oracle Linux, Oracle Solaris, Oracle Database, and Oracle WebLogic Server. More information about these GLPs and Boot Camps (including delivery dates and locations) are posted on the OPN Competency Center and corresponding OPN Knowledge Zones. Learn more about Oracle Exastack labs and ISV specific enablement resources. "Oracle Specialized partners are of course front-and-centre, with potential customers clearly directed to those partners and to Exadata Ready partners as a matter of priority." --More OpenWorld 2011 highlights for Oracle partners and customers Oracle Application Testing Suite 9.3 application testing solution for Web, SOA and Oracle Applications Oracle Application Express Release 4.1 improving the development of database-centric Web 2.0 applications and reports Oracle Unified Directory 11g helping customers manage the critical identity information that drives their business applications Oracle SOA Suite for healthcare integration Oracle Enterprise Pack for Eclipse 11g demonstrating continued commitment to the developer and open source communities Oracle Coherence 3.7.1, the latest release of the industry's leading distributed in-memory data grid Oracle Process Accelerators helping to simplify and accelerate time-to-value for customers' business process management initiatives Oracle's JD Edwards EnterpriseOne on the iPad meeting the increasingly mobile demands of today's workforces Oracle CRM On Demand Release 19 Innovation Pack introducing industry-leading hosted call centre and enterprise-marketing capabilities designed to drive further revenue and productivity while reducing costs and improving the customer experience Oracle's Primavera Portfolio Management 9 for businesses delivering on project portfolio goals with increased versatility, transparency and accuracy Oracle's PeopleSoft Human Capital Management (HCM) 9.1 On Demand Standard Edition helping customers manage their long-term investment in enterprise-wide business applications New versions of Oracle FLEXCUBE Universal Banking and Oracle FLEXCUBE Investor Servicing for Financial Institutions, as well as Oracle Financial Services Enterprise Case Management, Oracle Financial Services Pricing Management, Oracle Financial Management Analytics and Oracle Tax Analytics Oracle Utilities Network Management System 1.11 offering new modelling and analysis features to improve distribution-grid management for electric utilities Oracle Communications Network Charging and Control 4.4 helping communications service providers (CSPs) offer their customers more flexible charging options Plus many, many more technology announcements, enhancements, momentum news and community updates -- Oracle OpenWorld 2012 A date has already been set for Oracle OpenWorld 2012. Held once again in San Francisco, exhibitors, partners, customers and Oracle people will gather from 30 September until 4 November to meet, network and learn together with the rest of the global Oracle community. Register now for Oracle OpenWorld 2012 and save $$$! We'll reward your early planning for Oracle OpenWorld 2012 with reduced rates. Super Saver deals are now available! -- Back to the welcome page

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  • Another Marketing Conference, part two – the afternoon

    - by Roger Hart
    In my previous post, I’ve covered the morning sessions at AMC2012. Here’s the rest of the write-up. I’ve skipped Charles Nixon’s session which was a blend of funky futurism and professional development advice, but you can see his slides here. I’ve also skipped the Google presentation, as it was a little thin on insight. 6 – Brand ambassadors: Getting universal buy in across the organisation, Vanessa Northam Slides are here This was the strongest enforcement of the idea that brand and campaign values need to be delivered throughout the organization if they’re going to work. Vanessa runs internal communications at e-on, and shared her experience of using internal comms to align an organization and thereby get the most out of a campaign. She views the purpose of internal comms as: “…to help leaders, to communicate the purpose and future of an organization, and support change.” This (and culture) primes front line staff, which creates customer experience and spreads brand. You ensure a whole organization knows what’s going on with both internal and external comms. If everybody is aligned and informed, if everybody can clearly articulate your brand and campaign goals, then you can turn everybody into an advocate. Alignment is a powerful tool for delivering a consistent experience and message. The pathological counter example is the one in which a marketing message goes out, which creates inbound customer contacts that front line contact staff haven’t been briefed to handle. The NatWest campaign was again mentioned in this context. The good example was e-on’s cheaper tariff campaign. Building a groundswell of internal excitement, and even running an internal launch meant everyone could contribute to a good customer experience. They found that meter readers were excited – not a group they’d considered as obvious in providing customer experience. But they were a group that has a lot of face-to-face contact with customers, and often were asked questions they may not have been briefed to answer. Being able to communicate a simple new message made it easier for them, and also let them become a sales and marketing asset to the organization. 7 – Goodbye Internet, Hello Outernet: the rise and rise of augmented reality, Matt Mills I wasn’t going to write this up, because it was essentially a sales demo for Aurasma. But the technology does merit some discussion. Basically, it replaces QR codes with visual recognition, and provides a simple-looking back end for attaching content. It’s quite sexy. But here’s my beef with it: QR codes had a clear visual language – when you saw one you knew what it was and what to do with it. They were clunky, but they had the “getting started” problem solved out of the box once you knew what you were looking at. However, they fail because QR code reading isn’t native to the platform. You needed an app, which meant you needed to know to download one. Consequentially, you can’t use QR codes with and ubiquity, or depend on them. This means marketers, content providers, etc, never pushed them, and they remained and awkward oddity, a minority sport. Aurasma half solves problem two, and re-introduces problem one, making it potentially half as useful as a QR code. It’s free, and you can apparently build it into your own apps. Add to that the likelihood of it becoming native to the platform if it takes off, and it may have legs. I guess we’ll see. 8 – We all need to code, Helen Mayor Great title – good point. If there was anybody in the room who didn’t at least know basic HTML, and if Helen’s presentation inspired them to learn, that’s fantastic. However, this was a half hour sales pitch for a basic coding training course. Beyond advocating coding skills it contained no useful content. Marketers may also like to consider some of these resources if they’re looking to learn code: Code Academy – free interactive tutorials Treehouse – learn web design, web dev, or app dev WebPlatform.org – tutorials and documentation for web tech  11 – Understanding our inner creativity, Margaret Boden This session was the most theoretical and probably least actionable of the day. It also held my attention utterly. Margaret spoke fluently, fascinatingly, without slides, on the subject of types of creativity and how they work. It was splendid. Yes, it raised a wry smile whenever she spoke of “the content of advertisements” and gave an example from 1970s TV ads, but even without the attempt to meet the conference’s theme this would have been thoroughly engaging. There are, Margaret suggested, three types of creativity: Combinatorial creativity The most common form, and consisting of synthesising ideas from existing and familiar concepts and tropes. Exploratory creativity Less common, this involves exploring the limits and quirks of a particular constraint or style. Transformational creativity This is uncommon, and arises from finding a way to do something that the existing rules would hold to be impossible. In essence, this involves breaking one of the constraints that exploratory creativity is composed from. Combinatorial creativity, she suggested, is particularly important for attaching favourable ideas to existing things. As such is it probably worth developing for marketing. Exploratory creativity may then come into play in something like developing and optimising an idea or campaign that now has momentum. Transformational creativity exists at the edges of this exploration. She suggested that products may often be transformational, but that marketing seemed unlikely to in her experience. This made me wonder about Listerine. Crucially, transformational creativity is characterised by there being some element of continuity with the strictures of previous thinking. Once it has happened, there may be  move from a revolutionary instance into an explored style. Again, from a marketing perspective, this seems to chime well with the thinking in Youngme Moon’s book: Different Talking about the birth of Modernism is visual art, Margaret pointed out that transformational creativity has historically risked a backlash, demanding what is essentially an education of the market. This is best accomplished by referring back to the continuities with the past in order to make the new familiar. Thoughts The afternoon is harder to sum up than the morning. It felt less concrete, and was troubled by a short run of poor presentations in the middle. Mainly, I found myself wrestling with the internal comms issue. It’s one of those things that seems astonishingly obvious in hindsight, but any campaign – particularly any large one – is doomed if the people involved can’t believe in it. We’ve run things here that haven’t gone so well, of course we have; who hasn’t? I’m not going to air any laundry, but people not being informed (much less aligned) feels like a common factor. It’s tough though. Managing and anticipating information needs across an organization of any size can’t be easy. Even the simple things like ensuring sales and support departments know what’s in a product release, and what messages go with it are easy to botch. The thing I like about framing this as a brand and campaign advocacy problem is that it makes it likely to get addressed. Better is always sexier than less-worse. Any technical communicator who’s ever felt crowded out by a content strategist or marketing copywriter  knows this – increasing revenue gets a seat at the table far more readily than reducing support costs, even if the financial impact is identical. So that’s it from AMC. The big thought-provokers were social buying behaviour and eliciting behaviour change, and the value of internal communications in ensuring successful campaigns and continuity of customer experience. I’ll be chewing over that for a while, and I’d definitely return next year.      

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  • SQL SERVER – Shrinking Database is Bad – Increases Fragmentation – Reduces Performance

    - by pinaldave
    Earlier, I had written two articles related to Shrinking Database. I wrote about why Shrinking Database is not good. SQL SERVER – SHRINKDATABASE For Every Database in the SQL Server SQL SERVER – What the Business Says Is Not What the Business Wants I received many comments on Why Database Shrinking is bad. Today we will go over a very interesting example that I have created for the same. Here are the quick steps of the example. Create a test database Create two tables and populate with data Check the size of both the tables Size of database is very low Check the Fragmentation of one table Fragmentation will be very low Truncate another table Check the size of the table Check the fragmentation of the one table Fragmentation will be very low SHRINK Database Check the size of the table Check the fragmentation of the one table Fragmentation will be very HIGH REBUILD index on one table Check the size of the table Size of database is very HIGH Check the fragmentation of the one table Fragmentation will be very low Here is the script for the same. USE MASTER GO CREATE DATABASE ShrinkIsBed GO USE ShrinkIsBed GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Create FirstTable CREATE TABLE FirstTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_FirstTable_ID] ON FirstTable ( [ID] ASC ) ON [PRIMARY] GO -- Create SecondTable CREATE TABLE SecondTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_SecondTable_ID] ON SecondTable ( [ID] ASC ) ON [PRIMARY] GO -- Insert One Hundred Thousand Records INSERT INTO FirstTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Insert One Hundred Thousand Records INSERT INTO SecondTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO Let us check the table size and fragmentation. Now let us TRUNCATE the table and check the size and Fragmentation. USE MASTER GO CREATE DATABASE ShrinkIsBed GO USE ShrinkIsBed GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Create FirstTable CREATE TABLE FirstTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_FirstTable_ID] ON FirstTable ( [ID] ASC ) ON [PRIMARY] GO -- Create SecondTable CREATE TABLE SecondTable (ID INT, FirstName VARCHAR(100), LastName VARCHAR(100), City VARCHAR(100)) GO -- Create Clustered Index on ID CREATE CLUSTERED INDEX [IX_SecondTable_ID] ON SecondTable ( [ID] ASC ) ON [PRIMARY] GO -- Insert One Hundred Thousand Records INSERT INTO FirstTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Insert One Hundred Thousand Records INSERT INTO SecondTable (ID,FirstName,LastName,City) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY a.name) RowID, 'Bob', CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%2 = 1 THEN 'Smith' ELSE 'Brown' END, CASE WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 1 THEN 'New York' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 5 THEN 'San Marino' WHEN ROW_NUMBER() OVER (ORDER BY a.name)%10 = 3 THEN 'Los Angeles' ELSE 'Houston' END FROM sys.all_objects a CROSS JOIN sys.all_objects b GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can clearly see that after TRUNCATE, the size of the database is not reduced and it is still the same as before TRUNCATE operation. After the Shrinking database operation, we were able to reduce the size of the database. If you notice the fragmentation, it is considerably high. The major problem with the Shrink operation is that it increases fragmentation of the database to very high value. Higher fragmentation reduces the performance of the database as reading from that particular table becomes very expensive. One of the ways to reduce the fragmentation is to rebuild index on the database. Let us rebuild the index and observe fragmentation and database size. -- Rebuild Index on FirstTable ALTER INDEX IX_SecondTable_ID ON SecondTable REBUILD GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can notice that after rebuilding, Fragmentation reduces to a very low value (almost same to original value); however the database size increases way higher than the original. Before rebuilding, the size of the database was 5 MB, and after rebuilding, it is around 20 MB. Regular rebuilding the index is rebuild in the same user database where the index is placed. This usually increases the size of the database. Look at irony of the Shrinking database. One person shrinks the database to gain space (thinking it will help performance), which leads to increase in fragmentation (reducing performance). To reduce the fragmentation, one rebuilds index, which leads to size of the database to increase way more than the original size of the database (before shrinking). Well, by Shrinking, one did not gain what he was looking for usually. Rebuild indexing is not the best suggestion as that will create database grow again. I have always remembered the excellent post from Paul Randal regarding Shrinking the database is bad. I suggest every one to read that for accuracy and interesting conversation. Let us run following script where we Shrink the database and REORGANIZE. -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO -- Shrink the Database DBCC SHRINKDATABASE (ShrinkIsBed); GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO -- Rebuild Index on FirstTable ALTER INDEX IX_SecondTable_ID ON SecondTable REORGANIZE GO -- Name of the Database and Size SELECT name, (size*8) Size_KB FROM sys.database_files GO -- Check Fragmentations in the database SELECT avg_fragmentation_in_percent, fragment_count FROM sys.dm_db_index_physical_stats (DB_ID(), OBJECT_ID('SecondTable'), NULL, NULL, 'LIMITED') GO You can see that REORGANIZE does not increase the size of the database or remove the fragmentation. Again, I no way suggest that REORGANIZE is the solution over here. This is purely observation using demo. Read the blog post of Paul Randal. Following script will clean up the database -- Clean up USE MASTER GO ALTER DATABASE ShrinkIsBed SET SINGLE_USER WITH ROLLBACK IMMEDIATE GO DROP DATABASE ShrinkIsBed GO There are few valid cases of the Shrinking database as well, but that is not covered in this blog post. We will cover that area some other time in future. Additionally, one can rebuild index in the tempdb as well, and we will also talk about the same in future. Brent has written a good summary blog post as well. Are you Shrinking your database? Well, when are you going to stop Shrinking it? Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • Thread placement policies on NUMA systems - update

    - by Dave
    In a prior blog entry I noted that Solaris used a "maximum dispersal" placement policy to assign nascent threads to their initial processors. The general idea is that threads should be placed as far away from each other as possible in the resource topology in order to reduce resource contention between concurrently running threads. This policy assumes that resource contention -- pipelines, memory channel contention, destructive interference in the shared caches, etc -- will likely outweigh (a) any potential communication benefits we might achieve by packing our threads more densely onto a subset of the NUMA nodes, and (b) benefits of NUMA affinity between memory allocated by one thread and accessed by other threads. We want our threads spread widely over the system and not packed together. Conceptually, when placing a new thread, the kernel picks the least loaded node NUMA node (the node with lowest aggregate load average), and then the least loaded core on that node, etc. Furthermore, the kernel places threads onto resources -- sockets, cores, pipelines, etc -- without regard to the thread's process membership. That is, initial placement is process-agnostic. Keep reading, though. This description is incorrect. On Solaris 10 on a SPARC T5440 with 4 x T2+ NUMA nodes, if the system is otherwise unloaded and we launch a process that creates 20 compute-bound concurrent threads, then typically we'll see a perfect balance with 5 threads on each node. We see similar behavior on an 8-node x86 x4800 system, where each node has 8 cores and each core is 2-way hyperthreaded. So far so good; this behavior seems in agreement with the policy I described in the 1st paragraph. I recently tried the same experiment on a 4-node T4-4 running Solaris 11. Both the T5440 and T4-4 are 4-node systems that expose 256 logical thread contexts. To my surprise, all 20 threads were placed onto just one NUMA node while the other 3 nodes remained completely idle. I checked the usual suspects such as processor sets inadvertently left around by colleagues, processors left offline, and power management policies, but the system was configured normally. I then launched multiple concurrent instances of the process, and, interestingly, all the threads from the 1st process landed on one node, all the threads from the 2nd process landed on another node, and so on. This happened even if I interleaved thread creating between the processes, so I was relatively sure the effect didn't related to thread creation time, but rather that placement was a function of process membership. I this point I consulted the Solaris sources and talked with folks in the Solaris group. The new Solaris 11 behavior is intentional. The kernel is no longer using a simple maximum dispersal policy, and thread placement is process membership-aware. Now, even if other nodes are completely unloaded, the kernel will still try to pack new threads onto the home lgroup (socket) of the primordial thread until the load average of that node reaches 50%, after which it will pick the next least loaded node as the process's new favorite node for placement. On the T4-4 we have 64 logical thread contexts (strands) per socket (lgroup), so if we launch 48 concurrent threads we will find 32 placed on one node and 16 on some other node. If we launch 64 threads we'll find 32 and 32. That means we can end up with our threads clustered on a small subset of the nodes in a way that's quite different that what we've seen on Solaris 10. So we have a policy that allows process-aware packing but reverts to spreading threads onto other nodes if a node becomes too saturated. It turns out this policy was enabled in Solaris 10, but certain bugs suppressed the mixed packing/spreading behavior. There are configuration variables in /etc/system that allow us to dial the affinity between nascent threads and their primordial thread up and down: see lgrp_expand_proc_thresh, specifically. In the OpenSolaris source code the key routine is mpo_update_tunables(). This method reads the /etc/system variables and sets up some global variables that will subsequently be used by the dispatcher, which calls lgrp_choose() in lgrp.c to place nascent threads. Lgrp_expand_proc_thresh controls how loaded an lgroup must be before we'll consider homing a process's threads to another lgroup. Tune this value lower to have it spread your process's threads out more. To recap, the 'new' policy is as follows. Threads from the same process are packed onto a subset of the strands of a socket (50% for T-series). Once that socket reaches the 50% threshold the kernel then picks another preferred socket for that process. Threads from unrelated processes are spread across sockets. More precisely, different processes may have different preferred sockets (lgroups). Beware that I've simplified and elided details for the purposes of explication. The truth is in the code. Remarks: It's worth noting that initial thread placement is just that. If there's a gross imbalance between the load on different nodes then the kernel will migrate threads to achieve a better and more even distribution over the set of available nodes. Once a thread runs and gains some affinity for a node, however, it becomes "stickier" under the assumption that the thread has residual cache residency on that node, and that memory allocated by that thread resides on that node given the default "first-touch" page-level NUMA allocation policy. Exactly how the various policies interact and which have precedence under what circumstances could the topic of a future blog entry. The scheduler is work-conserving. The x4800 mentioned above is an interesting system. Each of the 8 sockets houses an Intel 7500-series processor. Each processor has 3 coherent QPI links and the system is arranged as a glueless 8-socket twisted ladder "mobius" topology. Nodes are either 1 or 2 hops distant over the QPI links. As an aside the mapping of logical CPUIDs to physical resources is rather interesting on Solaris/x4800. On SPARC/Solaris the CPUID layout is strictly geographic, with the highest order bits identifying the socket, the next lower bits identifying the core within that socket, following by the pipeline (if present) and finally the logical thread context ("strand") on the core. But on Solaris on the x4800 the CPUID layout is as follows. [6:6] identifies the hyperthread on a core; bits [5:3] identify the socket, or package in Intel terminology; bits [2:0] identify the core within a socket. Such low-level details should be of interest only if you're binding threads -- a bad idea, the kernel typically handles placement best -- or if you're writing NUMA-aware code that's aware of the ambient placement and makes decisions accordingly. Solaris introduced the so-called critical-threads mechanism, which is expressed by putting a thread into the FX scheduling class at priority 60. The critical-threads mechanism applies to placement on cores, not on sockets, however. That is, it's an intra-socket policy, not an inter-socket policy. Solaris 11 introduces the Power Aware Dispatcher (PAD) which packs threads instead of spreading them out in an attempt to be able to keep sockets or cores at lower power levels. Maximum dispersal may be good for performance but is anathema to power management. PAD is off by default, but power management polices constitute yet another confounding factor with respect to scheduling and dispatching. If your threads communicate heavily -- one thread reads cache lines last written by some other thread -- then the new dense packing policy may improve performance by reducing traffic on the coherent interconnect. On the other hand if your threads in your process communicate rarely, then it's possible the new packing policy might result on contention on shared computing resources. Unfortunately there's no simple litmus test that says whether packing or spreading is optimal in a given situation. The answer varies by system load, application, number of threads, and platform hardware characteristics. Currently we don't have the necessary tools and sensoria to decide at runtime, so we're reduced to an empirical approach where we run trials and try to decide on a placement policy. The situation is quite frustrating. Relatedly, it's often hard to determine just the right level of concurrency to optimize throughput. (Understanding constructive vs destructive interference in the shared caches would be a good start. We could augment the lines with a small tag field indicating which strand last installed or accessed a line. Given that, we could augment the CPU with performance counters for misses where a thread evicts a line it installed vs misses where a thread displaces a line installed by some other thread.)

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  • SQL SERVER – Faster SQL Server Databases and Applications – Power and Control with SafePeak Caching Options

    - by Pinal Dave
    Update: This blog post is written based on the SafePeak, which is available for free download. Today, I’d like to examine more closely one of my preferred technologies for accelerating SQL Server databases, SafePeak. Safepeak’s software provides a variety of advanced data caching options, techniques and tools to accelerate the performance and scalability of SQL Server databases and applications. I’d like to look more closely at some of these options, as some of these capabilities could help you address lagging database and performance on your systems. To better understand the available options, it is best to start by understanding the difference between the usual “Basic Caching” vs. SafePeak’s “Dynamic Caching”. Basic Caching Basic Caching (or the stale and static cache) is an ability to put the results from a query into cache for a certain period of time. It is based on TTL, or Time-to-live, and is designed to stay in cache no matter what happens to the data. For example, although the actual data can be modified due to DML commands (update/insert/delete), the cache will still hold the same obsolete query data. Meaning that with the Basic Caching is really static / stale cache.  As you can tell, this approach has its limitations. Dynamic Caching Dynamic Caching (or the non-stale cache) is an ability to put the results from a query into cache while maintaining the cache transaction awareness looking for possible data modifications. The modifications can come as a result of: DML commands (update/insert/delete), indirect modifications due to triggers on other tables, executions of stored procedures with internal DML commands complex cases of stored procedures with multiple levels of internal stored procedures logic. When data modification commands arrive, the caching system identifies the related cache items and evicts them from cache immediately. In the dynamic caching option the TTL setting still exists, although its importance is reduced, since the main factor for cache invalidation (or cache eviction) become the actual data updates commands. Now that we have a basic understanding of the differences between “basic” and “dynamic” caching, let’s dive in deeper. SafePeak: A comprehensive and versatile caching platform SafePeak comes with a wide range of caching options. Some of SafePeak’s caching options are automated, while others require manual configuration. Together they provide a complete solution for IT and Data managers to reach excellent performance acceleration and application scalability for  a wide range of business cases and applications. Automated caching of SQL Queries: Fully/semi-automated caching of all “read” SQL queries, containing any types of data, including Blobs, XMLs, Texts as well as all other standard data types. SafePeak automatically analyzes the incoming queries, categorizes them into SQL Patterns, identifying directly and indirectly accessed tables, views, functions and stored procedures; Automated caching of Stored Procedures: Fully or semi-automated caching of all read” stored procedures, including procedures with complex sub-procedure logic as well as procedures with complex dynamic SQL code. All procedures are analyzed in advance by SafePeak’s  Metadata-Learning process, their SQL schemas are parsed – resulting with a full understanding of the underlying code, objects dependencies (tables, views, functions, sub-procedures) enabling automated or semi-automated (manually review and activate by a mouse-click) cache activation, with full understanding of the transaction logic for cache real-time invalidation; Transaction aware cache: Automated cache awareness for SQL transactions (SQL and in-procs); Dynamic SQL Caching: Procedures with dynamic SQL are pre-parsed, enabling easy cache configuration, eliminating SQL Server load for parsing time and delivering high response time value even in most complicated use-cases; Fully Automated Caching: SQL Patterns (including SQL queries and stored procedures) that are categorized by SafePeak as “read and deterministic” are automatically activated for caching; Semi-Automated Caching: SQL Patterns categorized as “Read and Non deterministic” are patterns of SQL queries and stored procedures that contain reference to non-deterministic functions, like getdate(). Such SQL Patterns are reviewed by the SafePeak administrator and in usually most of them are activated manually for caching (point and click activation); Fully Dynamic Caching: Automated detection of all dependent tables in each SQL Pattern, with automated real-time eviction of the relevant cache items in the event of “write” commands (a DML or a stored procedure) to one of relevant tables. A default setting; Semi Dynamic Caching: A manual cache configuration option enabling reducing the sensitivity of specific SQL Patterns to “write” commands to certain tables/views. An optimization technique relevant for cases when the query data is either known to be static (like archive order details), or when the application sensitivity to fresh data is not critical and can be stale for short period of time (gaining better performance and reduced load); Scheduled Cache Eviction: A manual cache configuration option enabling scheduling SQL Pattern cache eviction based on certain time(s) during a day. A very useful optimization technique when (for example) certain SQL Patterns can be cached but are time sensitive. Example: “select customers that today is their birthday”, an SQL with getdate() function, which can and should be cached, but the data stays relevant only until 00:00 (midnight); Parsing Exceptions Management: Stored procedures that were not fully parsed by SafePeak (due to too complex dynamic SQL or unfamiliar syntax), are signed as “Dynamic Objects” with highest transaction safety settings (such as: Full global cache eviction, DDL Check = lock cache and check for schema changes, and more). The SafePeak solution points the user to the Dynamic Objects that are important for cache effectiveness, provides easy configuration interface, allowing you to improve cache hits and reduce cache global evictions. Usually this is the first configuration in a deployment; Overriding Settings of Stored Procedures: Override the settings of stored procedures (or other object types) for cache optimization. For example, in case a stored procedure SP1 has an “insert” into table T1, it will not be allowed to be cached. However, it is possible that T1 is just a “logging or instrumentation” table left by developers. By overriding the settings a user can allow caching of the problematic stored procedure; Advanced Cache Warm-Up: Creating an XML-based list of queries and stored procedure (with lists of parameters) for periodically automated pre-fetching and caching. An advanced tool allowing you to handle more rare but very performance sensitive queries pre-fetch them into cache allowing high performance for users’ data access; Configuration Driven by Deep SQL Analytics: All SQL queries are continuously logged and analyzed, providing users with deep SQL Analytics and Performance Monitoring. Reduce troubleshooting from days to minutes with database objects and SQL Patterns heat-map. The performance driven configuration helps you to focus on the most important settings that bring you the highest performance gains. Use of SafePeak SQL Analytics allows continuous performance monitoring and analysis, easy identification of bottlenecks of both real-time and historical data; Cloud Ready: Available for instant deployment on Amazon Web Services (AWS). As you can see, there are many options to configure SafePeak’s SQL Server database and application acceleration caching technology to best fit a lot of situations. If you’re not familiar with their technology, they offer free-trial software you can download that comes with a free “help session” to help get you started. You can access the free trial here. Also, SafePeak is available to use on Amazon Cloud. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Security in Software

    The term security has many meanings based on the context and perspective in which it is used. Security from the perspective of software/system development is the continuous process of maintaining confidentiality, integrity, and availability of a system, sub-system, and system data. This definition at a very high level can be restated as the following: Computer security is a continuous process dealing with confidentiality, integrity, and availability on multiple layers of a system. Key Aspects of Software Security Integrity Confidentiality Availability Integrity within a system is the concept of ensuring only authorized users can only manipulate information through authorized methods and procedures. An example of this can be seen in a simple lead management application.  If the business decided to allow each sales member to only update their own leads in the system and sales managers can update all leads in the system then an integrity violation would occur if a sales member attempted to update someone else’s leads. An integrity violation occurs when a team member attempts to update someone else’s lead because it was not entered by the sales member.  This violates the business rule that leads can only be update by the originating sales member. Confidentiality within a system is the concept of preventing unauthorized access to specific information or tools.  In a perfect world the knowledge of the existence of confidential information/tools would be unknown to all those who do not have access. When this this concept is applied within the context of an application only the authorized information/tools will be available. If we look at the sales lead management system again, leads can only be updated by originating sales members. If we look at this rule then we can say that all sales leads are confidential between the system and the sales person who entered the lead in to the system. The other sales team members would not need to know about the leads let alone need to access it. Availability within a system is the concept of authorized users being able to access the system. A real world example can be seen again from the lead management system. If that system was hosted on a web server then IP restriction can be put in place to limit access to the system based on the requesting IP address. If in this example all of the sales members where accessing the system from the 192.168.1.23 IP address then removing access from all other IPs would be need to ensure that improper access to the system is prevented while approved users can access the system from an authorized location. In essence if the requesting user is not coming from an authorized IP address then the system will appear unavailable to them. This is one way of controlling where a system is accessed. Through the years several design principles have been identified as being beneficial when integrating security aspects into a system. These principles in various combinations allow for a system to achieve the previously defined aspects of security based on generic architectural models. Security Design Principles Least Privilege Fail-Safe Defaults Economy of Mechanism Complete Mediation Open Design Separation Privilege Least Common Mechanism Psychological Acceptability Defense in Depth Least Privilege Design PrincipleThe Least Privilege design principle requires a minimalistic approach to granting user access rights to specific information and tools. Additionally, access rights should be time based as to limit resources access bound to the time needed to complete necessary tasks. The implications of granting access beyond this scope will allow for unnecessary access and the potential for data to be updated out of the approved context. The assigning of access rights will limit system damaging attacks from users whether they are intentional or not. This principle attempts to limit data changes and prevents potential damage from occurring by accident or error by reducing the amount of potential interactions with a resource. Fail-Safe Defaults Design PrincipleThe Fail-Safe Defaults design principle pertains to allowing access to resources based on granted access over access exclusion. This principle is a methodology for allowing resources to be accessed only if explicit access is granted to a user. By default users do not have access to any resources until access has been granted. This approach prevents unauthorized users from gaining access to resource until access is given. Economy of Mechanism Design PrincipleThe Economy of mechanism design principle requires that systems should be designed as simple and small as possible. Design and implementation errors result in unauthorized access to resources that would not be noticed during normal use. Complete Mediation Design PrincipleThe Complete Mediation design principle states that every access to every resource must be validated for authorization. Open Design Design PrincipleThe Open Design Design Principle is a concept that the security of a system and its algorithms should not be dependent on secrecy of its design or implementation Separation Privilege Design PrincipleThe separation privilege design principle requires that all resource approved resource access attempts be granted based on more than a single condition. For example a user should be validated for active status and has access to the specific resource. Least Common Mechanism Design PrincipleThe Least Common Mechanism design principle declares that mechanisms used to access resources should not be shared. Psychological Acceptability Design PrincipleThe Psychological Acceptability design principle refers to security mechanisms not make resources more difficult to access than if the security mechanisms were not present Defense in Depth Design PrincipleThe Defense in Depth design principle is a concept of layering resource access authorization verification in a system reduces the chance of a successful attack. This layered approach to resource authorization requires unauthorized users to circumvent each authorization attempt to gain access to a resource. When designing a system that requires meeting a security quality attribute architects need consider the scope of security needs and the minimum required security qualities. Not every system will need to use all of the basic security design principles but will use one or more in combination based on a company’s and architect’s threshold for system security because the existence of security in an application adds an additional layer to the overall system and can affect performance. That is why the definition of minimum security acceptably is need when a system is design because this quality attributes needs to be factored in with the other system quality attributes so that the system in question adheres to all qualities based on the priorities of the qualities. Resources: Barnum, Sean. Gegick, Michael. (2005). Least Privilege. Retrieved on August 28, 2011 from https://buildsecurityin.us-cert.gov/bsi/articles/knowledge/principles/351-BSI.html Saltzer, Jerry. (2011). BASIC PRINCIPLES OF INFORMATION PROTECTION. Retrieved on August 28, 2011 from  http://web.mit.edu/Saltzer/www/publications/protection/Basic.html Barnum, Sean. Gegick, Michael. (2005). Defense in Depth. Retrieved on August 28, 2011 from  https://buildsecurityin.us-cert.gov/bsi/articles/knowledge/principles/347-BSI.html Bertino, Elisa. (2005). Design Principles for Security. Retrieved on August 28, 2011 from  http://homes.cerias.purdue.edu/~bhargav/cs526/security-9.pdf

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  • Improved Performance on PeopleSoft Combined Benchmark using SPARC T4-4

    - by Brian
    Oracle's SPARC T4-4 server running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved a world record 18,000 concurrent users experiencing subsecond response time while executing a PeopleSoft Payroll batch job of 500,000 employees in 32.4 minutes. This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier. The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment. The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 47% (online and batch) leaving significant headroom for additional processing across the three tiers. The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices. Performance Landscape Results are presented for the PeopleSoft HRMS Self-Service and Payroll combined benchmark. The new result with 128 streams shows significant improvement in the payroll batch processing time with little impact on the self-service component response time. PeopleSoft HRMS Self-Service and Payroll Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.988 0.539 32.4 128 SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.944 0.503 43.3 64 The following results are for the PeopleSoft HRMS Self-Service benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the payroll component. PeopleSoft HRMS Self-Service 9.1 Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) 2x SPARC T4-2 (db) 18,000 1.048 0.742 N/A N/A The following results are for the PeopleSoft Payroll benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the self-service component. PeopleSoft Payroll (N.A.) 9.1 - 500K Employees (7 Million SQL PayCalc, Unicode) Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-4 (db) N/A N/A N/A 30.84 96 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 PeopleSoft HCM 9.1 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Java Platform, Standard Edition Development Kit 6 Update 32 Database Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 256 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 PeopleTools 8.52 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Micro Focus Server Express (COBOL v 5.1.00) Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 Oracle WebLogic Server 10.3.4 Java Platform, Standard Edition Development Kit 6 Update 32 Storage Configuration: 1 x Sun Server X2-4 as a COMSTAR head for data 4 x Intel Xeon X7550, 2.0 GHz 128 GB memory 1 x Sun Storage F5100 Flash Array (80 flash modules) 1 x Sun Storage F5100 Flash Array (40 flash modules) 1 x Sun Fire X4275 as a COMSTAR head for redo logs 12 x 2 TB SAS disks with Niwot Raid controller Benchmark Description This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2. The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published. PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions. All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions. The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes. The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state. Key Points and Best Practices Two PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning. Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads. A total of 128 PeopleSoft streams server processes where used on the database node to complete payroll batch job of 500,000 employees in 32.4 minutes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN PeopleSoft Enterprise Human Capital Managementoracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 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 8 November 2012.

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  • Recap: Oracle Fusion Middleware Strategies Driving Business Innovation

    - by Harish Gaur
    Hasan Rizvi, Executive Vice President of Oracle Fusion Middleware & Java took the stage on Tuesday to discuss how Oracle Fusion Middleware helps enable business innovation. Through a series of product demos and customer showcases, Hassan demonstrated how Oracle Fusion Middleware is a complete platform to harness the latest technological innovations (cloud, mobile, social and Fast Data) throughout the application lifecycle. Fig 1: Oracle Fusion Middleware is the foundation of business innovation This Session included 4 demonstrations to illustrate these strategies: 1. Build and deploy native mobile applications using Oracle ADF Mobile 2. Empower business user to model processes, design user interface and have rich mobile experience for process interaction using Oracle BPM Suite PS6. 3. Create collaborative user experience and integrate social sign-on using Oracle WebCenter Portal, Oracle WebCenter Content, Oracle Social Network & Oracle Identity Management 11g R2 4. Deploy and manage business applications on Oracle Exalogic Nike, LA Department of Water & Power and Nintendo joined Hasan on stage to share how their organizations are leveraging Oracle Fusion Middleware to enable business innovation. Managing Performance in the Wrld of Social and Mobile How do you provide predictable scalability and performance for an application that monitors active lifestyle of 8 million users on a daily basis? Nike’s answer is Oracle Coherence, a component of Oracle Fusion Middleware and Oracle Exadata. Fig 2: Oracle Coherence enabled data grid improves performance of Nike+ Digital Sports Platform Nicole Otto, Sr. Director of Consumer Digital Technology discussed the vision of the Nike+ platform, a platform which represents a shift for NIKE from a  "product"  to  a "product +" experience.  There are currently nearly 8 million users in the Nike+ system who are using digitally-enabled Nike+ devices.  Once data from the Nike+ device is transmitted to Nike+ application, users access the Nike+ website or via the Nike mobile applicatoin, seeing metrics around their daily active lifestyle and even engage in socially compelling experiences to compare, compete or collaborate their data with their friends. Nike expects the number of users to grow significantly this year which will drive an explosion of data and potential new experiences. To deal with this challenge, Nike envisioned building a shared platform that would drive a consumer-centric model for the company. Nike built this new platform using Oracle Coherence and Oracle Exadata. Using Coherence, Nike built a data grid tier as a distributed cache, thereby provide low-latency access to most recent and relevant data to consumers. Nicole discussed how Nike+ Digital Sports Platform is unique in the way that it utilizes the Coherence Grid.  Nike takes advantage of Coherence as a traditional cache using both cache-aside and cache-through patterns.  This new tier has enabled Nike to create a horizontally scalable distributed event-driven processing architecture. Current data grid volume is approximately 150,000 request per minute with about 40 million objects at any given time on the grid. Improving Customer Experience Across Multiple Channels Customer experience is on top of every CIO's mind. Customer Experience needs to be consistent and secure across multiple devices consumers may use.  This is the challenge Matt Lampe, CIO of Los Angeles Department of Water & Power (LADWP) was faced with. Despite being the largest utilities company in the country, LADWP had been relying on a 38 year old customer information system for serving its customers. Their prior system  had been unable to keep up with growing customer demands. Last year, LADWP embarked on a journey to improve customer experience for 1.6million LA DWP customers using Oracle WebCenter platform. Figure 3: Multi channel & Multi lingual LADWP.com built using Oracle WebCenter & Oracle Identity Management platform Matt shed light on his efforts to drive customer self-service across 3 dimensions – new website, new IVR platform and new bill payment service. LADWP has built a new portal to increase customer self-service while reducing the transactions via IVR. LADWP's website is powered Oracle WebCenter Portal and is accessible by desktop and mobile devices. By leveraging Oracle WebCenter, LADWP eliminated the need to build, format, and maintain individual mobile applications or websites for different devices. Their entire content is managed using Oracle WebCenter Content and secured using Oracle Identity Management. This new portal automated their paper based processes to web based workflows for customers. This includes automation of Self Service implemented through My Account -  like Bill Pay, Payment History, Bill History and Usage Analysis. LADWP's solution went live in April 2012. Matt indicated that LADWP's Self-Service Portal has greatly improved customer satisfaction.  In a JD Power Associates website satisfaction survey, results indicate rankings have climbed by 25+ points, marking a remarkable increase in user experience. Bolstering Performance and Simplifying Manageability of Business Applications Ingvar Petursson, Senior Vice Preisdent of IT at Nintendo America joined Hasan on-stage to discuss their choice of Exalogic. Nintendo had significant new requirements coming their way for business systems, both internal and external, in the years to come, especially with new products like the WiiU on the horizon this holiday season. Nintendo needed a platform that could give them performance, availability and ease of management as they deploy business systems. Ingvar selected Engineered Systems for two reasons: 1. High performance  2. Ease of management Figure 4: Nintendo relies on Oracle Exalogic to run ATG eCommerce, Oracle e-Business Suite and several business applications Nintendo made a decision to run their business applications (ATG eCommerce, E-Business Suite) and several Fusion Middleware components on the Exalogic platform. What impressed Ingvar was the "stress” testing results during evaluation. Oracle Exalogic could handle their 3-year load estimates for many functions, which was better than Nintendo expected without any hardware expansion. Faster Processing of Big Data Middleware plays an increasingly important role in Big Data. Last year, we announced at OpenWorld the introduction of Oracle Data Integrator for Hadoop and Oracle Loader for Hadoop which helps in the ability to move, transform, load data to and from Big Data Appliance to Exadata.  This year, we’ve added new capabilities to find, filter, and focus data using Oracle Event Processing. This product can natively integrate with Big Data Appliance or runs standalone. Hasan briefly discussed how NTT Docomo, largest mobile operator in Japan, leverages Oracle Event Processing & Oracle Coherence to process mobile data (from 13 million smartphone users) at a speed of 700K events per second before feeding it Hadoop for distributed processing of big data. Figure 5: Mobile traffic data processing at NTT Docomo with Oracle Event Processing & Oracle Coherence    

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  • C# Performance Pitfall – Interop Scenarios Change the Rules

    - by Reed
    C# and .NET, overall, really do have fantastic performance in my opinion.  That being said, the performance characteristics dramatically differ from native programming, and take some relearning if you’re used to doing performance optimization in most other languages, especially C, C++, and similar.  However, there are times when revisiting tricks learned in native code play a critical role in performance optimization in C#. I recently ran across a nasty scenario that illustrated to me how dangerous following any fixed rules for optimization can be… The rules in C# when optimizing code are very different than C or C++.  Often, they’re exactly backwards.  For example, in C and C++, lifting a variable out of loops in order to avoid memory allocations often can have huge advantages.  If some function within a call graph is allocating memory dynamically, and that gets called in a loop, it can dramatically slow down a routine. This can be a tricky bottleneck to track down, even with a profiler.  Looking at the memory allocation graph is usually the key for spotting this routine, as it’s often “hidden” deep in call graph.  For example, while optimizing some of my scientific routines, I ran into a situation where I had a loop similar to: for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i]); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This loop was at a fairly high level in the call graph, and often could take many hours to complete, depending on the input data.  As such, any performance optimization we could achieve would be greatly appreciated by our users. After a fair bit of profiling, I noticed that a couple of function calls down the call graph (inside of ProcessElement), there was some code that effectively was doing: // Allocate some data required DataStructure* data = new DataStructure(num); // Call into a subroutine that passed around and manipulated this data highly CallSubroutine(data); // Read and use some values from here double values = data->Foo; // Cleanup delete data; // ... return bar; Normally, if “DataStructure” was a simple data type, I could just allocate it on the stack.  However, it’s constructor, internally, allocated it’s own memory using new, so this wouldn’t eliminate the problem.  In this case, however, I could change the call signatures to allow the pointer to the data structure to be passed into ProcessElement and through the call graph, allowing the inner routine to reuse the same “data” memory instead of allocating.  At the highest level, my code effectively changed to something like: DataStructure* data = new DataStructure(numberToProcess); for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i], data); } delete data; Granted, this dramatically reduced the maintainability of the code, so it wasn’t something I wanted to do unless there was a significant benefit.  In this case, after profiling the new version, I found that it increased the overall performance dramatically – my main test case went from 35 minutes runtime down to 21 minutes.  This was such a significant improvement, I felt it was worth the reduction in maintainability. In C and C++, it’s generally a good idea (for performance) to: Reduce the number of memory allocations as much as possible, Use fewer, larger memory allocations instead of many smaller ones, and Allocate as high up the call stack as possible, and reuse memory I’ve seen many people try to make similar optimizations in C# code.  For good or bad, this is typically not a good idea.  The garbage collector in .NET completely changes the rules here. In C#, reallocating memory in a loop is not always a bad idea.  In this scenario, for example, I may have been much better off leaving the original code alone.  The reason for this is the garbage collector.  The GC in .NET is incredibly effective, and leaving the allocation deep inside the call stack has some huge advantages.  First and foremost, it tends to make the code more maintainable – passing around object references tends to couple the methods together more than necessary, and overall increase the complexity of the code.  This is something that should be avoided unless there is a significant reason.  Second, (unlike C and C++) memory allocation of a single object in C# is normally cheap and fast.  Finally, and most critically, there is a large advantage to having short lived objects.  If you lift a variable out of the loop and reuse the memory, its much more likely that object will get promoted to Gen1 (or worse, Gen2).  This can cause expensive compaction operations to be required, and also lead to (at least temporary) memory fragmentation as well as more costly collections later. As such, I’ve found that it’s often (though not always) faster to leave memory allocations where you’d naturally place them – deep inside of the call graph, inside of the loops.  This causes the objects to stay very short lived, which in turn increases the efficiency of the garbage collector, and can dramatically improve the overall performance of the routine as a whole. In C#, I tend to: Keep variable declarations in the tightest scope possible Declare and allocate objects at usage While this tends to cause some of the same goals (reducing unnecessary allocations, etc), the goal here is a bit different – it’s about keeping the objects rooted for as little time as possible in order to (attempt) to keep them completely in Gen0, or worst case, Gen1.  It also has the huge advantage of keeping the code very maintainable – objects are used and “released” as soon as possible, which keeps the code very clean.  It does, however, often have the side effect of causing more allocations to occur, but keeping the objects rooted for a much shorter time. Now – nowhere here am I suggesting that these rules are hard, fast rules that are always true.  That being said, my time spent optimizing over the years encourages me to naturally write code that follows the above guidelines, then profile and adjust as necessary.  In my current project, however, I ran across one of those nasty little pitfalls that’s something to keep in mind – interop changes the rules. In this case, I was dealing with an API that, internally, used some COM objects.  In this case, these COM objects were leading to native allocations (most likely C++) occurring in a loop deep in my call graph.  Even though I was writing nice, clean managed code, the normal managed code rules for performance no longer apply.  After profiling to find the bottleneck in my code, I realized that my inner loop, a innocuous looking block of C# code, was effectively causing a set of native memory allocations in every iteration.  This required going back to a “native programming” mindset for optimization.  Lifting these variables and reusing them took a 1:10 routine down to 0:20 – again, a very worthwhile improvement. Overall, the lessons here are: Always profile if you suspect a performance problem – don’t assume any rule is correct, or any code is efficient just because it looks like it should be Remember to check memory allocations when profiling, not just CPU cycles Interop scenarios often cause managed code to act very differently than “normal” managed code. Native code can be hidden very cleverly inside of managed wrappers

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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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  • Oracle Tutor: Top 10 to Implement Sustainable Policies and Procedures

    - by emily.chorba(at)oracle.com
    Overview Your organization (executives, managers, and employees) understands the value of having written business process documents (process maps, procedures, instructions, reference documents, and form abstracts). Policies and procedures should be documented because they help to reduce the range of individual decisions and encourage management by exception: the manager only needs to give special attention to unusual problems, not covered by a specific policy or procedure. As more and more procedures are written to cover recurring situations, managers will begin to make decisions which will be consistent from one functional area to the next.Companies should take a project management approach when implementing an environment for a sustainable documentation program and do the following:1. Identify an Executive Champion2. Put together a winning team3. Assign ownership4. Centralize publishing5. Establish the Document Maintenance Process Up Front6. Document critical activities only7. Document actual practice8. Minimize documentation9. Support continuous improvement10. Keep it simple 1. Identify an Executive ChampionAppoint a top down driver. Select one key individual to be a mentor for the procedure planning team. The individual should be a senior manager, such as your company president, CIO, CFO, the vice-president of quality, manufacturing, or engineering. Written policies and procedures can be important supportive aids when known to express the thinking for the chief executive officer and / or the president and to have his or her full support. 2. Put Together a Winning TeamChoose a strong Project Management Leader and staff the procedure planning team with management members from cross functional groups. Make sure team members have the responsibility - and the authority - to make things happen.The winning team should consist of the Documentation Project Manager, Document Owners (one for each functional area), a Document Controller, and Document Specialists (as needed). The Tutor Implementation Guide has complete job descriptions for these roles. 3. Assign Ownership It is virtually impossible to keep process documentation simple and meaningful if employees who are far removed from the activity itself create it. It is impossible to keep documentation up-to-date when responsibility for the document is not clearly understood.Key to the Tutor methodology, therefore, is the concept of ownership. Each document has a single owner, who is responsible for ensuring that the document is necessary and that it reflects actual practice. The owner must be a person who is knowledgeable about the activity and who has the authority to build consensus among the persons who participate in the activity as well as the authority to define or change the way an activity is performed. The owner must be an advocate of the performers and negotiate, not dictate practices.In the Tutor environment, a document's owner is the only person with the authority to approve an update to that document. 4. Centralize Publishing Although it is tempting (especially in a networked environment and with document management software solutions) to decentralize the control of all documents -- with each owner updating and distributing his own -- Tutor promotes centralized publishing by assigning the Document Administrator (gate keeper) to manage the updates and distribution of the procedures library. 5. Establish a Document Maintenance Process Up Front (and stick to it) Everyone in your organization should know they are invited to suggest changes to procedures and should understand exactly what steps to take to do so. Tutor provides a set of procedures to help your company set up a healthy document control system. There are many document management products available to automate some of the document change and maintenance steps. Depending on the size of your organization, a simple document management system can reduce the effort it takes to track and distribute document changes and updates. Whether your company decides to store the written policies and procedures on a file server or in a database, the essential tasks for maintaining documents are the same, though some tasks are automated. 6. Document Critical Activities Only The best way to keep your documentation simple is to reduce the number of process documents to a bare minimum and to include in those documents only as much detail as is absolutely necessary. The first step to reducing process documentation is to document only those activities that are deemed critical. Not all activities require documentation. In fact, some critical activities cannot and should not be standardized. Others may be sufficiently documented with an instruction or a checklist and may not require a procedure. A document should only be created when it enhances the performance of the employee performing the activity. If it does not help the employee, then there is no reason to maintain the document. Activities that represent little risk (such as project status), activities that cannot be defined in terms of specific tasks (such as product research), and activities that can be performed in a variety of ways (such as advertising) often do not require documentation. Sometimes, an activity will evolve to the point where documentation is necessary. For example, an activity performed by single employee may be straightforward and uncomplicated -- that is, until the activity is performed by multiple employees. Sometimes, it is the interaction between co-workers that necessitates documentation; sometimes, it is the complexity or the diversity of the activity.7. Document Actual Practices The only reason to maintain process documentation is to enhance the performance of the employee performing the activity. And documentation can only enhance performance if it reflects reality -- that is, current best practice. Documentation that reflects an unattainable ideal or outdated practices will end up on the shelf, unused and forgotten.Documenting actual practice means (1) auditing the activity to understand how the work is really performed, (2) identifying best practices with employees who are involved in the activity, (3) building consensus so that everyone agrees on a common method, and (4) recording that consensus.8. Minimize Documentation One way to keep it simple is to document at the highest level possible. That is, include in your documents only as much detail as is absolutely necessary.When writing a document, you should ask yourself, What is the purpose of this document? That is, what problem will it solve?By focusing on this question, you can target the critical information.• What questions are the end users likely to have?• What level of detail is required?• Is any of this information extraneous to the document's purpose? Short, concise documents are user friendly and they are easier to keep up to date. 9. Support Continuous Improvement Employees who perform an activity are often in the best position to identify improvements to the process. In other words, continuous improvement is a natural byproduct of the work itself -- but only if the improvements are communicated to all employees who are involved in the process, and only if there is consensus among those employees.Traditionally, process documentation has been used to dictate performance, to limit employees' actions. In the Tutor environment, process documents are used to communicate improvements identified by employees. How does this work? The Tutor methodology requires a process document to reflect actual practice, so the owner of a document must routinely audit its content -- does the document match what the employees are doing? If it doesn't, the owner has the responsibility to evaluate the process, to build consensus among the employees, to identify "best practices," and to communicate these improvements via a document update. Continuous improvement can also be an outgrowth of corrective action -- but only if the solutions to problems are communicated effectively. The goal should be to solve a problem once and only once, which means not only identifying the solution, but ensuring that the solution becomes part of the process. The Tutor system provides the method through which improvements and solutions are documented and communicated to all affected employees in a cost-effective, timely manner; it ensures that improvements are not lost or confined to a single employee. 10. Keep it Simple Process documents don't have to be complex and unfriendly. In fact, the simpler the format and organization, the more likely the documents will be used. And the simpler the method of maintenance, the more likely the documents will be kept up-to-date. Keep it simply by:• Minimizing skills and training required• Following the established Tutor document format and layout• Avoiding technology just for technology's sake No other rule has as major an impact on the success of your internal documentation as -- keep it simple. Learn More For more information about Tutor, visit Oracle.Com or the Tutor Blog. Post your questions at the Tutor Forum.   Emily Chorba Principle Product Manager Oracle Tutor & BPM 

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  • The challenge of communicating externally with IRM secured content

    - by Simon Thorpe
    I am often asked by customers about how they handle sending IRM secured documents to external parties. Their concern is that using IRM to secure sensitive information they need to share outside their business, is troubled with the inability for third parties to install the software which enables them to gain access to the information. It is a very legitimate question and one i've had to answer many times in the past 10 years whilst helping customers plan successful IRM deployments. The operating system does not provide the required level of content security The problem arises from what IRM delivers, persistent security to your sensitive information where ever it resides and whenever it is in use. Oracle IRM gives customers an array of features that help ensure sensitive information in an IRM document or email is always protected and only accessed by authorized users using legitimate applications. Examples of such functionality are; Control of the clipboard, either by disabling completely in the opened document or by allowing the cut and pasting of information between secured IRM documents but not into insecure applications. Protection against programmatic access to the document. Office documents and PDF documents have the ability to be accessed by other applications and scripts. With Oracle IRM we have to protect against this to ensure content cannot be leaked by someone writing a simple program. Securing of decrypted content in memory. At some point during the process of opening and presenting a sealed document to an end user, we must decrypt it and give it to the application (Adobe Reader, Microsoft Word, Excel etc). This process must be secure so that someone cannot simply get access to the decrypted information. The operating system alone just doesn't have the functionality to deliver these types of features. This is why for every IRM technology there must be some extra software installed and typically this software requires administrative rights to do so. The fact is that if you want to have very strong security and access control over a document you are going to send to someone who is beyond your network infrastructure, there must be some software to provide that functionality. Simple installation with Oracle IRM The software used to control access to Oracle IRM sealed content is called the Oracle IRM Desktop. It is a small, free piece of software roughly about 12mb in size. This software delivers functionality for everything a user needs to work with an Oracle IRM solution. It provides the functionality for all formats we support, the storage and transparent synchronization of user rights and unique to Oracle, the ability to search inside sealed files stored on the local computer. In Oracle we've made every technical effort to ensure that installing this software is a simple as possible. In situations where the user's computer is part of the enterprise, this software is typically deployed using existing technologies such as Systems Management Server from Microsoft or by using Active Directory Group Policies. However when sending sealed content externally, you cannot automatically install software on the end users machine. You need to rely on them to download and install themselves. Again we've made every effort for this manual install process to be as simple as we can. Starting with the small download size of the software itself to the simple installation process, most end users are able to install and access sealed content very quickly. You can see for yourself how easily this is done by walking through our free and easy self service demonstration of using sealed content. How to handle objections and ensure there is value However the fact still remains that end users may object to installing, or may simply be unable to install the software themselves due to lack of permissions. This is often a problem with any technology that requires specialized software to access a new type of document. In Oracle, over the past 10 years, we've learned many ways to get over this barrier of getting software deployed by external users. First and I would say of most importance, is the content MUST have some value to the person you are asking to install software. Without some type of value proposition you are going to find it very difficult to get past objections to installing the IRM Desktop. Imagine if you were going to secure the weekly campus restaurant menu and send this to contractors. Their initial response will be, "why on earth are you asking me to download some software just to access your menu!?". A valid objection... there is no value to the user in doing this. Now consider the scenario where you are sending one of your contractors their employment contract which contains their address, social security number and bank account details. Are they likely to take 5 minutes to install the IRM Desktop? You bet they are, because there is real value in doing so and they understand why you are doing it. They want their personal information to be securely handled and a quick download and install of some software is a small task in comparison to dealing with the loss of this information. Be clear in communicating this value So when sending sealed content to people externally, you must be clear in communicating why you are using an IRM technology and why they need to install some software to access the content. Do not try and avoid the issue, you must be clear and upfront about it. In doing so you will significantly reduce the "I didn't know I needed to do this..." responses and also gain respect for being straight forward. One customer I worked with, 6 months after the initial deployment of Oracle IRM, called me panicking that the partner they had started to share their engineering documents with refused to install any software to access this highly confidential intellectual property. I explained they had to communicate to the partner why they were doing this. I told them to go back with the statement that "the company takes protecting its intellectual property seriously and had decided to use IRM to control access to engineering documents." and if the partner didn't respect this decision, they would find another company that would. The result? A few days later the partner had made the Oracle IRM Desktop part of their approved list of software in the company. Companies are successful when sending sealed content to third parties We have many, many customers who send sensitive content to third parties. Some customers actually sell access to Oracle IRM protected content and therefore 99% of their users are external to their business, one in particular has sold content to hundreds of thousands of external users. Oracle themselves use the technology to secure M&A documents, payroll data and security assessments which go beyond the traditional enterprise security perimeter. Pretty much every company who deploys Oracle IRM will at some point be sending those documents to people outside of the company, these customers must be successful otherwise Oracle IRM wouldn't be successful. Because our software is used by a wide variety of companies, some who use it to sell content, i've often run into people i'm sharing a sealed document with and they already have the IRM Desktop installed due to accessing content from another company. The future In summary I would say that yes, this is a hurdle that many customers are concerned about but we see much evidence that in practice, people leap that hurdle with relative ease as long as they are good at communicating the value of using IRM and also take measures to ensure end users can easily go through the process of installation. We are constantly developing new ideas to reducing this hurdle and maybe one day the operating systems will give us enough rich security functionality to have no software installation. Until then, Oracle IRM is by far the easiest solution to balance security and usability for your business. If you would like to evaluate it for yourselves, please contact us.

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  • Design for complex ATG applications

    - by Glen Borkowski
    Overview Needless to say, some ATG applications are more complex than others.  Some ATG applications support a single site, single language, single catalog, single currency, have a single development staff, single business team, and a relatively simple business model.  The real complex applications have to support multiple sites, multiple languages, multiple catalogs, multiple currencies, a couple different development teams, multiple business teams, and a highly complex business model (and processes to go along with it).  While it's still important to implement a proper design for simple applications, it's absolutely critical to do this for the complex applications.  Why?  It's all about time and money.  If you are unable to manage your complex applications in an efficient manner, the cost of managing it will increase dramatically as will the time to get things done (time to market).  On the positive side, your competition is most likely in the same situation, so you just need to be more efficient than they are. This article is intended to discuss a number of key areas to think about when designing complex applications on ATG.  Some of this can get fairly technical, so it may help to get some background first.  You can get enough of the required background information from this post.  After reading that, come back here and follow along. Application Design Of all the various types of ATG applications out there, the most complex tend to be the ones in the telecommunications industry - especially the ones which operate in multiple countries.  To get started, let's assume that we are talking about an application like that.  One that has these properties: Operates in multiple countries - must support multiple sites, catalogs, languages, and currencies The organization is fairly loosely-coupled - single brand, but different businesses across different countries There is some common functionality across all sites in all countries There is some common functionality across different sites within the same country Sites within a single country may have some unique functionality - relative to other sites in the same country Complex product catalog (mostly in terms of bundles, eligibility, and compatibility) At this point, I'll assume you have read through the required reading and have a decent understanding of how ATG modules work... Code / configuration - assemble into modules When it comes to defining your modules for a complex application, there are a number of goals: Divide functionality between the modules in a way that maps to your business Group common functionality 'further down in the stack of modules' Provide a good balance between shared resources and autonomy for countries / sites Now I'll describe a high level approach to how you could accomplish those goals...  Let's start from the bottom and work our way up.  At the very bottom, you have the modules that ship with ATG - the 'out of the box' stuff.  You want to make sure that you are leveraging all the modules that make sense in order to get the most value from ATG as possible - and less stuff you'll have to write yourself.  On top of the ATG modules, you should create what we'll refer to as the Corporate Foundation Module described as follows: Sits directly on top of ATG modules Used by all applications across all countries and sites - this is the foundation for everyone Contains everything that is common across all countries / all sites Once established and settled, will change less frequently than other 'higher' modules Encapsulates as many enterprise-wide integrations as possible Will provide means of code sharing therefore less development / testing - faster time to market Contains a 'reference' web application (described below) The next layer up could be multiple modules for each country (you could replace this with region if that makes more sense).  We'll define those modules as follows: Sits on top of the corporate foundation module Contains what is unique to all sites in a given country Responsible for managing any resource bundles for this country (to handle multiple languages) Overrides / replaces corporate integration points with any country-specific ones Finally, we will define what should be a fairly 'thin' (in terms of functionality) set of modules for each site as follows: Sits on top of the country it resides in module Contains what is unique for a given site within a given country Will mostly contain configuration, but could also define some unique functionality as well Contains one or more web applications The graphic below should help to indicate how these modules fit together: Web applications As described in the previous section, there are many opportunities for sharing (minimizing costs) as it relates to the code and configuration aspects of ATG modules.  Web applications are also contained within ATG modules, however, sharing web applications can be a bit more difficult because this is what the end customer actually sees, and since each site may have some degree of unique look & feel, sharing becomes more challenging.  One approach that can help is to define a 'reference' web application at the corporate foundation layer to act as a solid starting point for each site.  Here's a description of the 'reference' web application: Contains minimal / sample reference styling as this will mostly be addressed at the site level web app Focus on functionality - ensure that core functionality is revealed via this web application Each individual site can use this as a starting point There may be multiple types of web apps (i.e. B2C, B2B, etc) There are some techniques to share web application assets - i.e. multiple web applications, defined in the web.xml, and it's worth investigating, but is out of scope here. Reference infrastructure In this complex environment, it is assumed that there is not a single infrastructure for all countries and all sites.  It's more likely that different countries (or regions) could have their own solution for infrastructure.  In this case, it will be advantageous to define a reference infrastructure which contains all the hardware and software that make up the core environment.  Specifications and diagrams should be created to outline what this reference infrastructure looks like, as well as it's baseline cost and the incremental cost to scale up with volume.  Having some consistency in terms of infrastructure will save time and money as new countries / sites come online.  Here are some properties of the reference infrastructure: Standardized approach to setup of hardware Type and number of servers Defines application server, operating system, database, etc... - including vendor and specific versions Consistent naming conventions Provides a consistent base of terminology and understanding across environments Defines which ATG services run on which servers Production Staging BCC / Preview Each site can change as required to meet scale requirements Governance / organization It should be no surprise that the complex application we're talking about is backed by an equally complex organization.  One of the more challenging aspects of efficiently managing a series of complex applications is to ensure the proper level of governance and organization.  Here are some ideas and goals to work towards: Establish a committee to make enterprise-wide decisions that affect all sites Representation should be evenly distributed Should have a clear communication procedure Focus on high level business goals Evaluation of feature / function gaps and how that relates to ATG release schedule / roadmap Determine when to upgrade & ensure value will be realized Determine how to manage various levels of modules Who is responsible for maintaining corporate / country / site layers Determine a procedure for controlling what goes in the corporate foundation module Standardize on source code control, database, hardware, OS versions, J2EE app servers, development procedures, etc only use tested / proven versions - this is something that should be centralized so that every country / site does not have to worry about compatibility between versions Create a innovation team Quickly develop new features, perform proof of concepts All teams can benefit from their findings Summary At this point, it should be clear why the topics above (design, governance, organization, etc) are critical to being able to efficiently manage a complex application.  To summarize, it's all about competitive advantage...  You will need to reduce costs and improve time to market with the goal of providing a better experience for your end customers.  You can reduce cost by reducing development time, time allocated to testing (don't have to test the corporate foundation module over and over again - do it once), and optimizing operations.  With an efficient design, you can improve your time to market and your business will be more flexible  and agile.  Over time, you'll find that you're becoming more focused on offering functionality that is new to the market (creativity) and this will be rewarded - you're now a leader. In addition to the above, you'll realize soft benefits as well.  Your staff will be operating in a culture based on sharing.  You'll want to reward efforts to improve and enhance the foundation as this will benefit everyone.  This culture will inspire innovation, which can only lend itself to your competitive advantage.

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  • From J2EE to Java EE: what has changed?

    - by Bruno.Borges
    See original @Java_EE tweet on 29 May 2014 Yeap, it has been 8 years since the term J2EE was replaced, and still some people refer to it (mostly recruiters, luckily!). But then comes the question: what has changed besides the name? Our community friend Abhishek Gupta worked on this question and provided an excellent response titled "What's in a name? Java EE? J2EE?". But let me give you a few highlights here so you don't lose yourself with YATO (yet another tab opened): J2EE used to be an infrastructure and resources provider only, requiring developers to depend on external 3rd-party frameworks to then implement application requirements or improve productivity J2EE used to require hundreds of XML lines of codes to define just a dozen of resources like EJBs, MDBs, Servlets, and so on J2EE used to support only EAR (Enterprise Archives) with a bunch of other archives like JARs and WARs just to run a simple Web application And so on, and so on! It was a great technology but still required a lot of work to get something up and running. Remember xDoclet? Remember Struts? The old days of pure Hibernate code? Or when Ajax became a trending topic and we were all implementing it with DWR Servlet? Still, we J2EE developers survived, and learned, and helped evolve the platform to a whole new level of DX (Developer Experience). A new DX for J2EE suggested a new name. One that referred to the platform as the Enterprise Edition of Java, because "Java is why we're here" quoting Bill Shannon. The release of Java EE 5 included so many features that clearly showed developers the platform was going after all those DX gaps. Radical simplification of the persistence model with the introduction of JPA Support of Annotations following the launch of Java SE 5.0 Updated XML APIs with the introduction of StAX Drastic simplification of the EJB component model (with annotations!) Convention over Configuration and Dependency Injection A few bullets you may say but that represented a whole new DX and a vision for upcoming versions. Clearly, the release of Java EE 5 helped drive the future of the platform by reducing the number of XMLs, Java Interfaces, simplified configurations, provided convention-over-configuration, etc! We then saw the release of Java EE 6 with even more great features like Managed Beans, CDI, Bean Validation, improved JSP and Servlets APIs, JASPIC, the posisbility to deploy plain WARs and so many other improvements it is difficult to list in one sentence. And we've gotta give Spring Framework some credit here: thanks to Rod Johnson and team, concepts like Dependency Injection fit perfectly into the Java EE Platform. Clearly, Spring used to be one of the most inspiring frameworks for the Java EE platform, and it is great to see things like Pivotal and Spring supporting JSR 352 Batch API standard! Cooperation to keep improving DX at maximum in the server-side Java landscape.  The master piece result of these previous releases is seen and called today as Java EE 7, which by providing a newly and improved JavaServer Faces release, with new features for Web Development like WebSockets API, improved JAX-RS, and JSON-P, but also including Batch API and so many other great improvements, has increased developer productivity and brought innovation to server-side Java developers. Java EE is not just a new name (which was introduced back in May 2006!) but a new Developer Experience for server-side Java developers. To show you why we are here and where we are going (see the Java EE 8 update), we wanted to share with you a draft of the new Java EE logos that the evangelist team created, to help you spread the word about Java EE. You can get access to these images at the Java EE Platform Facebook Album, or the Google+ Java EE Platform Album whichever is better for you, but don't forget to like and/or +1 those social network profiles :-) A message to all job recruiters: stop using J2EE and start using Java EE if you want to find great Java EE 5, Java EE 6, or Java EE 7 developers To not only save you recruiter valuable characters when tweeting that job opportunity but to also match the correct term, we invite you to replace long terms like "Java/J2EE" or even worse "#Java #J2EE #JEE" or all these awkward combinations with the only acceptable hashtag: #JavaEE. And to prove that Java EE is catching among developers and even recruiters, and that J2EE is past, let me highlight here how are the jobs trends! The image below is from Indeed.com trends page, for the following keywords: J2EE, Java/J2EE, Java/JEE, JEE. As you can see, J2EE is indeed going away, while JEE saw some increase. Perhaps because some people are just lazy to type "Java" but at the same time they are aware that J2EE (the '2') is past. We shall forgive that for a while :-) Another proof that J2EE is going away is by looking at its trending statistics at Google. People have been showing less and less interest in the term J2EE. See the chart below:  Recruiter, if you still need proof that J2EE is past, that Java EE is trending, and that other job recruiters are seeking for Java EE developers, and that the developer community is aware of the new term, perhaps these other charts can show you what term you should be using. See for example the Job Trends for Java EE at Indeed.com and notice where it started... 2006! 8 years ago :-) Last but not least, the Google Trends for Java EE term (including the still wrong but forgivable JavaEE term) shows us that the new term is catching up very well. J2EE is past. Oh, and don't worry about the curves going down. We developers like to be hipsters sometimes and today only AngularJS, NodeJS, BigData are going up. Java EE and other traditional server-side technologies such as Spring, or even from other platforms such as Ruby on Rails, PHP, Grails, are pretty much consolidated and the curves... well, they are consolidated too. So If you are a Java EE developer, drop that J2EE from your résumé, and let recruiters also know that this term is past. Embrace Java EE, and enjoy a new developer experience for server-side Java developers. Java EE on TwitterJava EE on Google+Java EE on Facebook

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  • Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

    - by aspiringgeek
    Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario   Conventional Structures   Columnstore   Δ SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

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