Search Results

Search found 3857 results on 155 pages for 'teach my family'.

Page 122/155 | < Previous Page | 118 119 120 121 122 123 124 125 126 127 128 129  | Next Page >

• OpenGL Pixel Format Attributes (NSOpenGLPixelFormatAttibutes) explanation?

  - by nacho4d

  Hi, I am not new to OpenGL, but not an expert. Many tutorials teach how to draw, 3D, 2D, projections, orthogonal, etc, but How about setting a the view? (NSOpenGLView in Cocoa, Macs). For example I have this: - (id) initWithFrame: (NSRect) frame { GLuint attribs[] = { //PF: PixelAttibutes NSOpenGLPFANoRecovery, NSOpenGLPFAWindow, NSOpenGLPFAAccelerated, NSOpenGLPFADoubleBuffer, NSOpenGLPFAColorSize, 24, NSOpenGLPFAAlphaSize, 8, NSOpenGLPFADepthSize, 24, NSOpenGLPFAStencilSize, 8, NSOpenGLPFAAccumSize, 0, 0 }; NSOpenGLPixelFormat* fmt = [[NSOpenGLPixelFormat alloc] initWithAttributes: (NSOpenGLPixelFormatAttribute*) attribs]; return self = [super initWithFrame:frame pixelFormat: [fmt autorelease]]; } And I don't understand very well their usage, specially when combining them. For example: If I want my view to be capable of full screen should I write NSOpenGLPFAFullScreen only ? or both? (by capable I mean not always in full screen) Regarding Double Buffer, what is this exactly? (Below: Apple's definition) If present, this attribute indicates that only double-buffered pixel formats are considered. Otherwise, only single-buffered pixel formats are considered Regarding Color: if NSOpenGLPFAColorSize is 24 and NSOpenGLPFAColorSize is 8 then it means that alpha and RGB components are treated differently? what happen if I set the former to 32 and the later to 0? Etc, etc,In general how do I learn to set my view from scratch? Thanks in advance. Ignacio.

  Read the article

• iPhone: Same Rows Repeated in Each Section of Grouped UITableview

  - by Rank Beginner

  I have an app that is a list of tasks, like a to do list. The user configures the tasks and that goes to the SQLite db. The list is displayed in a tableview. The SQL table in question consists of a taskid int, groupname varchar, taskname varchar, lastcompleted datetime, nextdue datetime, weighting integer. I currently have it working by creating an array from each column in the SQL table. In the tableView:cellForRowAtIndexPath: method, I create the controls for each task by binding their values to the array for each column. I want to add configurable task groups that should display as the section titles. I got the task groups to display as the section headers. My problem is that all the task rows are repeated in each group under each header. How do I get the correct rows to show up only under the correct section? I'm really new to development period and took on a hobby of trying to teach myself how to develop iphone apps. So, pretty please, be a little more detailed than you normally would with a professional developer. :)

  Read the article

• Why do I get "request for member in something not a struct or union" from this code?

  - by pyroxene

  I'm trying to teach myself C by coding up a linked list. I'm new to pointers and memory management and I'm getting a bit confused. I have this code: /* Remove a node from the list and rejiggle the pointers */ void rm_node(struct node **listP, int index) { struct node *prev; struct node *n = *listP; if (index == 0) { *listP = *listP->next; free(n); return; } for (index; index > 0; index--) { n = n->next; if (index == 2) { prev = n; } } prev->next = n->next; free(n); } to remove an element from the list. If I want to remove the first node, I still need some way of referring to the list, which is why the listP arg is a double pointer, so it can point to the first element of the list and allow me to free the node that used to be the head. However, when I try to dereference listP to access the pointer to the next node, the compiler tells me error: request for member ‘next’ in something not a structure or union . What am I doing wrong here? I think I might be hopelessly mixed up..?

  Read the article

• iPad pushing a split view in navigator-based application

  - by FabioWong

  I had read a lot of post from the web, but I still cannot find out how can I make this out. Please help me in detail. I need to make a split-view inside a navigation because I need to make a login system. After login, then we can see the split view. I found that someone say must need to set it to be root view, some say do not need. However I cannot do it in both way. Can anyone teach me how to do that step by step?? Here is what I did. - (void)viewDidLoad { [super viewDidLoad]; GOTSorOE_EN *gotsORoeEN = [[[GOTSorOE_EN alloc]initWithNibName:@"GOTSorOE_EN" bundle:nil]autorelease]; OEFileList_EN *oeFileListEN = [[[OEFileList_EN alloc]initWithNibName:@"OEFileList_EN" bundle:nil]autorelease]; gotsORoeEN.oeFileListEN = oeFileListEN; splitViewController = [[[UISplitViewController alloc]init]autorelease]; splitViewController.viewControllers = [NSArray arrayWithObjects:gotsORoeEN, oeFileListEN, nil]; self.view = splitViewController.view; }

  Read the article

• How can I post an array of string to ASP.NET MVC Controller without a form?

  - by rodbv

  Hi there, I am creating a small app to teach myself ASP.NET MVC and JQuery, and one of the pages is a list of items in which some can be selected. Then I would like to press a button and send a List (or something equivalent) to my controller containing the ids of the items that were selected, using JQuery's Post function. I managed to get an array with the ids of the elements that were selected, and now I want to post that. One way I could do this is to have a dummy form in my page, with a hidden value, and then set the hidden value with the selected items, and post that form; this looks crufty, though. Is there a cleaner way to achieve this, by sending the array directly to the controller? I've tried a few different things but it looks like the controller can't map the data it's receiving. Here's the code so far: function generateList(selectedValues) { var s = { values: selectedValues //selectedValues is an array of string }; $.post("/Home/GenerateList", $.toJSON(s), function() { alert("back") }, "json"); } And then my Controller looks like this public ActionResult GenerateList(List<string> values) { //do something } All I managed to get is a "null" in the controller parameter... Any tips?

  Read the article

• Is there an efficient algorithm to distribute resources in a way that both avoids conflict and allows bias?

  - by Steve V.

  Background (Skip this if you only care about the algorithm) At the university where I work, one of the biggest hassles in our department is classroom scheduling. For illustration purposes and to lay out the scope of the problem, here's how we do scheduling now: Professors give us a list of the classes they're teaching with the time slots they'd prefer to teach, ranked in order of priority (most desired to least desired). Administration gives us a list of the rooms we may assign along with the times those rooms are available for our department's use. We start assigning professors to rooms trying (at first) to take into account the preferences of the various professors. Inevitably, conflicts arise, professors start asking for changes, and the plan falls to pieces somewhere around professor number 30, at which point we start assigning rooms basically wherever we can fit them in, crumpled pieces of paper are everywhere, and nobody's happy. (If you've ever wondered why your class was at 9.30 in the morning on Thursday but 4 pm every other day, now you know) I have been asked to quietly investigate whether software could do this more optimally. The Actual Question Is there an algorithm to efficiently schedule a set of resources such that the following criteria are met: The algorithm must never assign two professors to the same room at the same time. The task is not complete until every professor has been assigned a room / time. The algorithm need not worry about having too many professors for the amount of time slots available. (We're not that well funded.) As much as is possible the algorithm should respect the scheduling preferences of the individual professors. I feel like I can't be the first one to ask this. Is there a efficient algorithm for this, or is this the sort of problem that can only be brute-forced?

  Read the article

• android webview returns blank page when load dynamic html page

  - by user2962555

  I am trying to click one button to load a page into a div block dynamically. To test it, I try to append a list item with text "abc" into the loaded page. However, I always get a blank page. load function works fine because if I try to load a static page, it works. Following is my main html page code. <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1"> <title>LoadPageTest</title> <link rel="stylesheet" href="http://fonts.googleapis.com/css?family=Open+Sans:300,400,700"> <link rel="stylesheet" href="./css/customizedstyle.css"> <link rel="stylesheet" href="./css/themes/default/jquery.mobile-1.4.3.min.css"> <link rel="stylesheet" href="./css/jqm-demos.css"> <script src="./js/jquery.js"></script> <script scr="./js/customizedjs.js"></script> <script src="./js/jquery.mobile-1.4.3.min.js"></script> <script> $( document ).on( "pagecreate", "#demo-page", function() { $( document ).on( "swipeleft swiperight", "#demo-page", function( e ) { if ( $( ".ui-page-active" ).jqmData( "panel" ) !== "open" ) { if ( e.type === "swipeleft" ) { $( "#right-panel" ).panel( "open" ); } } }); }); </script> <style type="text/css"> body { overflow:hidden; } </style> </head> <body style= "overflow:hidden" scrolling="no"> <style type="text/css"> body { overflow:hidden; } </style> <div data-role="page" id="main-page" style= "overflow:hidden" scrolling="no"> <div role="main" class="ui-content" id ="maindiv" style= "overflow: auto"> Will load diff pages here. </div><!-- /content --> <div data-role="panel" id="left-panel" data-theme="b"> <ul data-role="listview" data-icon="false" id="menu"> <li> <a href="#" id = "btnA" data-rel="close">Go Page A <img src="./images/icona.png" class="ui-li-thumb"/> </li> <li> <a href="#" id = "btnB" data-rel="close">Go Page B <img src="./images/iconb.png" class="ui-li-thumb"/> </li> </ul> </div><!-- /panel --> <script type="text/javascript"> $("#btnA").on("click", function(){ $("#maindiv").empty(); $("#maindiv").load("pageA.html"); }); $("#btnB").on("click", function(){ $("#maindiv").empty(); $("#maindiv").load("pageB.html"); }); </script> </div><!-- /page --> </body> </html> Next is code for the page I try to load dynamically. <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1"> <title>Page should be loaded</title> <link rel="stylesheet" href="http://fonts.googleapis.com/css?family=Open+Sans:300,400,700"> <link rel="stylesheet" href="./css/customizedstyle.css"> <link rel="stylesheet" href="./css/themes/default/jquery.mobile-1.4.3.min.css"> <link rel="stylesheet" href="./css/jqm-demos.css"> <script src="./js/jquery.js"></script> <script scr="./js/customizedjs.js"></script> <script src="./js/jquery.mobile-1.4.3.min.js"></script> <script> $(document).on('pagebeforeshow', function () { $('#postlist').append('<li> abc </li>'); $('#postlist').listview('refresh'); }); </script> </head> <body > <div data-role="page" id="posthome"> <div data-role = "content"> <ul data-role='listview' id = "postlist"> </ul> </div> </div> </body> </html> I doubt if it is because my javascript in the page doesn't work, cause the swipe js code in the main page seems not work either. Is that possible? I have enabled javascript in the onCreate() function of the activity file as below. protected void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.activity_message); new LongRunningGetIO().execute(); mWebView = (WebView) findViewById(R.id.webview); mWebView.setWebViewClient(new AppClient()); mWebView.setVerticalScrollBarEnabled(false); mWebView.getSettings().setJavaScriptEnabled(true); mWebView.getSettings().setDomStorageEnabled(true); mWebView.loadUrl("file:///android_asset/index.html"); } I noticed there is a warning for statement to enable javascript "Using setJavaScriptEnabled can introduce XSS vulnerabilities into you application, review carefully". Will that maybe the reason? Then, I added @SuppressLint("SetJavaScriptEnabled") on top of the activity. The warning is gone, but the js code in pages seem still not work.

  Read the article

• [^.] causing headache in RewriteRule

  - by Ollie2893

  I am struggling with a very basic regex problem in my .htaccess file that I hope someone may be able to shed some light on. The basic premise is that I would like to teach Apache to switch any .html extension into a .var extension. I had thought that the rule would be positively trivial: RewriteRule ^([^.]+)\.html$ $1.var But the [^.] part simply doesn't work. Bizarrely, it works like so RewriteRule ^([^A-Z]+)\.html$ $1.var I do not understand why this latter rule works. Assume I am looking for a file called "index.html" then $1 should match to "index." and the ".html" bit should actually fail to match. To widen the scope of the question slightly, I am actually racking my brain on how to implement a multi-lingual site. I don't like Apache's MultiView option because it forces upon me a flat directory structure with file extensions that aren't recognizable to many development tools. I could go the .var type-map route but am finding that the default config for Apache doesn't support this all that well either (hence my excursions into regex land). So while I am using mod_rewrite, I am thinking that I might go the whole hog: whenever a request for a name.html file is received and this file does not exist, check whether there exists a XX/name.html file instead, where "XX" is the language code according to the user's preferences. This would give me a neater directory structure, though it does perhaps not perform as well as the .var approach in a situation where the language preference of the user's browser is not supported in by my site (in which situation .var would substitute EN or similar). Any thoughts? Thanks.

  Read the article

• What is better for a student programming in C++ to learn for writing GUI: C# vs QT?

  - by flashnik

  I'm a teacher(instructor) of CS in the university. The course is based on Cormen and Knuth and students program algorithms in C++. But sometimes it is good to show how an algorithm works or just a result of task through GUI. Also in my opinion it's very imporant to be able to write full programs. They will have courses concerning GUI but a three years, later, in fact, before graduatuion. I think that they should be able to write simple GUI applications earlier. So I want to teach them it. How do you think, what is more useful for them to learn: programming GUI with QT or writing GUI in C# and calling unmanaged C++ library? Update. For developing C++ applications students use MS Visual studio, so C# is already installed. But QT AFAIK also can be integrated into VS. I have following pros of C# (some were suggested there in answers): The need to make an additional layer. It's more work, but it forces you explicitly specify contract between GUI and processing data. The border between GUI and algorithms becomes very clear. It's more popular among employers. At least, in Russia where we live. It's rather common to write performance-critical algorithms in C++ and PInvoke them from well-looking C# application/ASP.Net website. Maybe it is not so widespread in the rest of the world but in Russia Windows is very popular, especially in companies and corporations due to some reasons, so most of b2b applications are Windows applications. Rapid development. It's much quicker to code in .Net then in C++ due to many reasons. And the con is that it's a new language with own specific for students. And the mess with invoking calls to library.

  Read the article

• Trying to add data to sql from link click and return results via jquery or ajax

  - by Jay Schires

  I am not familiar with jquery or ajax, but i do know it is whats needed to perform the action I want. I have created a wordpress plugin that updates a database table based on the users click. Right now it refreshes the page to return the results, but I want to stop the page refresh and return data via ajax I believe. If anyone is interested in helping me figure this out I would be very appreciative or even willing to pay. Thanks! Here is the plugin code: function BoardLikeItGetDelim($postid) { global $wp_rewrite; if($wp_rewrite->using_permalinks()) { if(isset($_GET['mbpost'])) return "?mbpost=".$postid."&"; return "?"; } else { if(isset($_GET['mbpost'])) return "&mbpost=".$postid."&"; return "&"; } } function AddBoardLikeItButton($postid) { global $user_ID; if(isset($_GET['board-like-it-action']) && $_GET['board-like-it-action'] == "like" && $_GET['bpid'] == $postid) BoardLikeItLike($user_ID, $_GET['bpid']); if(isset($_GET['board-like-it-action']) && $_GET['board-like-it-action'] == "unlike" && $_GET['bpid'] == $postid) BoardLikeItUnLike($user_ID, $_GET['bpid']); $num_likes = BoardLikeItGetNumLikes($postid); if(!BoardLikeItIsLiked($user_ID, $postid)) echo "<HREF LINK='".BoardLikeItGetDelim($postid)."board-like-it-action=like&bpid=".$postid."#mngl-board-post-message-".$postid."'>Like</a> ".$num_likes."" . "<br/>"; else echo "<HREF LINK ='".BoardLikeItGetDelim($postid)."board-like-it-action=unlike&bpid=".$postid."#mngl-board-post-message-".$postid."'>Un-Like</a> " . "<br/><span style='display: inline-block; padding: 0px; bottom: -5px; position: relative; border: 0px;'><IMAGE='". get_bloginfo('wpurl')."/wp-content/plugins/board-like-it/top-up.png' /></span><div style='-moz-border-radius: 4px; -khtml-border-radius: 4px; -webkit-border-radius: 4px; font-family: Verdana, Geneva, sans-serif; font-size: 10px; color: #000; background-color: #B8C9DB; width: 90%; margin: 0px; display: block; padding-top: 4px; padding-right: 5px; padding-bottom: 4px; padding-left: 6px;'>" . "<IMAGE='". get_bloginfo('wpurl')."/wp-content/plugins/board-like-it/thumb_up.png'/> " .BoardLikeItShowLikers($postid). "like this." . "</div>"; } function BoardLikeItShowLikers($postid) { global $wpdb; $result = $wpdb->get_var($wpdb->prepare("SELECT `likers` FROM ".BoardLikeItGetDBName()." WHERE `mngl_id` = {$postid}")); $results = explode(',', $result); $names = ""; if($results[0] != "") foreach($results as $r) { $userinfo = get_usermeta($r, 'user_login'); $names .= $userinfo.", "; } return $names; } function BoardLikeItGetNumLikes($postid) { global $wpdb; $result = $wpdb->get_var($wpdb->prepare("SELECT `likers` FROM ".BoardLikeItGetDBName()." WHERE `mngl_id` = {$postid}")); $results = explode(',', $result); if($results[0] != '') return count($results)."<br/><span style='display: inline-block; padding: 0px; bottom: -5px; position: relative; border: 0px;'><IMAGE='". get_bloginfo('wpurl')."/wp-content/plugins/board-like-it/top-up.png' /></span><div style='-moz-border-radius: 4px; -khtml-border-radius: 4px; -webkit-border-radius: 4px; font-family: Verdana, Geneva, sans-serif; font-size: 10px; color: #000; background-color: #B8C9DB; width: 90%; margin: 0px; display: inline-block; border: 0px; padding-top: 0px; padding-right: 5px; padding-bottom: 1px; padding-left: 6px;'>" . "<IMAGE='". get_bloginfo('wpurl')."/wp-content/plugins/board-like-it/thumb_up.png'/> " .BoardLikeItShowLikers($postid). "likes this." . "</div>"; else return ""; } function BoardLikeItLike($user_ID, $postid) { global $wpdb; $likers = array(); $likersnew = array(); $result = $wpdb->get_var($wpdb->prepare("SELECT `likers` FROM ".BoardLikeItGetDBName()." WHERE `mngl_id` = {$postid}")); $results = explode(',',$result); if($results[0] != "") { if(!in_array($user_ID, $results)) $results[] = $user_ID; $likers = implode(',',$results); $wpdb->query($wpdb->prepare("UPDATE ".BoardLikeItGetDBName()." SET `likers` = '{$likers}' WHERE `mngl_id` = {$postid}")); } else { $likersnew[] = $user_ID; $likersnew = implode(',',$likersnew); $wpdb->query($wpdb->prepare("INSERT INTO ".BoardLikeItGetDBName()." (`mngl_id`, `likers`) VALUES ('{$postid}', '{$likersnew}')")); } } function BoardLikeItUnLike($user_ID, $postid) { global $wpdb; $likers = array(); $result = $wpdb->get_var($wpdb->prepare("SELECT `likers` FROM ".BoardLikeItGetDBName()." WHERE `mngl_id` = {$postid}")); $results = explode(',', $result); if(in_array($user_ID, $results)) { $results = BoardLikeItRemoveFromArray($results, $user_ID); if(!empty($results)) { $likers = implode(',', $results); $wpdb->query($wpdb->prepare("UPDATE ".BoardLikeItGetDBName()." SET `likers` = '{$likers}' WHERE `mngl_id` = {$postid}")); } else { $wpdb->query($wpdb->prepare("DELETE FROM ".BoardLikeItGetDBName()." WHERE `mngl_id` = {$postid}")); } } } function BoardLikeItIsLiked($user_ID, $postid) { global $wpdb; $result = $wpdb->get_var($wpdb->prepare("SELECT `likers` FROM ".BoardLikeItGetDBName()." WHERE `mngl_id` = {$postid}")); $results = explode(',', $result); if(in_array($user_ID, $results)) return true; else return false; } function BoardLikeItActivate() { global $wpdb; $charset_collate = ''; if($wpdb->has_cap('collation')) { if(!empty($wpdb->charset)) $charset_collate = "DEFAULT CHARACTER SET $wpdb->charset"; if(!empty($wpdb->collate)) $charset_collate .= " COLLATE $wpdb->collate"; } $table_sql = "CREATE TABLE ".BoardLikeItGetDBName()."( `mngl_id` int(11) NOT NULL, `likers` longtext NOT NULL, PRIMARY KEY (`mngl_id`)) {$charset_collate};"; require_once(ABSPATH.'wp-admin/includes/upgrade.php'); dbDelta($table_sql); } function BoardLikeItGetDBName() { global $wpdb; return $wpdb->prefix."board_like_it"; } function BoardLikeItRemoveFromArray($arr, $key) { $new = array(); foreach($arr as $j => $i) { if($i != $key) $new[] = $i; } return $new; }

  Read the article

• How do I subtract two dates in Django/Python?

  - by Ryan

  Hi! I'm working on a little fitness tracker in order to teach myself Django. I want to graph my weight over time, so I've decided to use the Python Google Charts Wrapper. Google charts require that you convert your date into a x coordinate. To do this I want to take the number of days in my dataset by subtracting the first weigh-in from the last weigh-in and then using that to figure out the x coords (for example, I could 100 by the result and increment the x coord by the resulting number for each y coord.) Anyway, I need to figure out how to subtract Django datetime objects from one another and so far, I am striking out on both google and here at the stack. I know PHP, but have never gotten a handle on OO programming, so please excuse my ignorance. Here is what my models look like: class Goal(models.Model): goal_weight = models.DecimalField("Goal Weight",max_digits=4, decimal_places=1) target_date = models.DateTimeField("Target Date to Reach Goal") set_date = models.DateTimeField("When did you set your goal?") comments = models.TextField(blank=True) def __unicode__(self): return unicode(self.goal_weight) class Weight(models.Model): """Weight at a given date and time """ goal = models.ForeignKey(Goal) weight = models.DecimalField("Current Weight",max_digits=4, decimal_places=1) weigh_date = models.DateTimeField("Date of Weigh-In") comments = models.TextField(blank=True) def __unicode__(self): return unicode(self.weight) def recorded_today(self): return self.date.date() == datetime.date.today() Any ideas on how to proceed in the view? Thanks so much!

  Read the article

• Issues with an image link

  - by user1462362

  Two days ago I spontaneously bought myself a domain. The day before that, I hardly even knew what a domain really was. Since then, I've been trying to teach myself HTML for the very first time. Basically what I'm trying to say is, I'm very new - and will probably be poor in my explanations. I just succeeded in making an 'image-button', sorta. It's where I make a button-like image and then use it as navigation on my website (just like a regular link). My issue is that the link 'border' itself is bigger than the image, so you can press an inch outside the image itself and it will work. How do I make the invisible link 'border' the same size as the button? This is my site: http://www.djeveln.com On the test page (djeveln.com/test) is where I test things. There's the button I'm talking about, in case you can't understand my explanation very well. Here's my HTML: Here is the CSS I use for the image position and size: img.TestButton { /* Dette linker til selve størrelsen av knappen (bildet)*/ position: absolute; width: 100px; height: 75px; top: 400px; right: 250px; } Hope you can help me! :P

  Read the article

• storing user input into string array in C

  - by Jcmoney1010

  I'm writing a program that is supposed to take in a list of names from the user, store them in an array, and then search through the list to check and see if the next name the user enters is part of the original list of names. The issue I'm having is that when I go to enter a list of names, it only saves the last name entered into the list. I've searched the web and this site for similar issues, but I can't seem to find anything that answers this issue specifically. Here is the part of code where I have problem void initialize(char names[][],const int MAX_NAMES,const int MAX_NAMELENGTH) { int i,Number_entrys; printf("How many names would you like to enter to the list?"); scanf("%d",&Number_entrys); if(Number_entrys>MAX_NAMES){ printf("Please choose a smaller entry"); }else{ for (i=0; i<Number_entrys;i++){ scanf("%s",names); } } printf("%s",names); } trying very hard to teach myself, so be gentle lol.

  Read the article

• SCVMM 2012 R2 - Installing Virtual Switch Fails with Error 2916

  - by Brian M.

  So I've been attempting to teach myself SCVMM 2012 and Hyper-V Server 2012 R2, and I seem to have hit a snag. I've connected my Hyper-V Host to SCVMM 2012 successfully, and created a logical network, logical switch, and uplink port profile (which I essentially blew through with the default settings). However when I attempt to create a virtual switch on my Hyper-V host, I run into an issue. The job will use my logical network settings I created to configure the virtual switch, but when it tries to apply it to the host, it stalls and eventually fails with the following error: Error (2916) VMM is unable to complete the request. The connection to the agent vmhost1.test.loc was lost. WinRM: URL: [h**p://vmhost1.test.loc:5985], Verb: [GET], Resource: [h**p://schemas.microsoft.com/wbem/wsman/1/wmi/root/virtualization/v2/Msvm_ConcreteJob?InstanceID=2F401A71-14A2-4636-9B3E-10C0EE942D33] Unknown error (0x80338126) Recommended Action Ensure that the Windows Remote Management (WinRM) service and the VMM agent are installed and running and that a firewall is not blocking HTTP/HTTPS traffic. Ensure that VMM server is able to communicate with econ-hyperv2.econ.loc over WinRM by successfully running the following command: winrm id –r:vmhost1.test.loc This problem can also be caused by a Windows Management Instrumentation (WMI) service crash. If the server is running Windows Server 2008 R2, ensure that KB 982293 (h**p://support.microsoft.com/kb/982293) is installed on it. If the error persists, restart vmhost1.test.loc and then try the operation again. Refer to h**p://support.microsoft.com/kb/2742275 for more details. I restarted the server, and upon booting am greeted with a message stating "No active network adapters found." I load up powershell and run "Get-NetAdapter -IncludeHidden" to see what's going on, and get the following: Name InterfaceDescription ifIndex Status ---- -------------------- ------- ----- Local Area Connection* 5 WAN Miniport (PPPOE) 6 Di... Ethernet Microsoft Hyper-V Network Switch Def... 10 Local Area Connection* 1 WAN Miniport (L2TP) 2 Di... Local Area Connection* 8 WAN Miniport (Network Monitor) 9 Up Local Area Connection* 4 WAN Miniport (PPTP) 5 Di... Ethernet 2 Broadcom NetXtreme Gigabit Ethernet 13 Up Local Area Connection* 7 WAN Miniport (IPv6) 8 Up Local Area Connection* 9 Microsoft Kernel Debug Network Adapter 11 No... Local Area Connection* 3 WAN Miniport (IKEv2) 4 Di... Local Area Connection* 2 WAN Miniport (SSTP) 3 Di... vSwitch (TEST Test Swi... Hyper-V Virtual Switch Extension Ada... 17 Up Local Area Connection* 6 WAN Miniport (IP) 7 Up Now the machine is no longer visible on the network, and I don't have the slightest idea what went wrong, and more importantly how to undo the damage I caused in order to get back to where I was (save for re-installing Hyper-V Server, but I really would rather know what's going on and how to fix it)! Does anybody have any ideas? Much appreciated!

  Read the article

• RDS installation failure on 2012 R2 Server Core VM in Hyper-V Server

  - by Giles

  I'm currently installing a test-bed for my firms Infrastructure replacement. 10 or so Windows/Linux servers will be replaced by 2 physical servers running Hyper-V server. All services (DC, RDS, SQL) will be on Windows 2012 R2 Server Core VMs, Exchange on Server 2012 R2 GUI, and the rest are things like Elastix, MailArchiver etc, which aren't part of the equation thus far. I have installed Hyper-V server on a test box, and sucessfully got two virtual DC's running, SQL 2014 running, and 8.1 which I use for the RSAT tools. When trying to install RDS (The old fashioned kind, not the newer VDI(?) style), I get a failed installation due to the server not being able to reboot. A couple of articles have said not to do it locally, so I've moved on. Sitting at the Powershell prompt on the Domain Controller or SQL server (Both Server Core), I run the following commands: Import-Module RemoteDesktop New-SessionDeployment -ConnectionBroker "AlstersTS.Alsters.local" -SessionHost "AlstersTS.Alsters.local" The installation begins, carries on for 2 or 3 minutes, then I receive the following error message: New-SessionDeployment : Validation failed for the "RD Connection Broker" parameter. AlstersTS.Alsters.local Unable to connect to the server by using WindowsPowerShell remoting. Verify that you can connect to the server. At line:1 char:1 + NewSessionDeployment -ConnectionBroker "AlstersTS.Alsters.local" -SessionHost " ... + + CategoryInfo : NotSpecified: (:) [Write-Error], WriteErrorException + FullyQualifiedErrorID : Microsoft.PowerShell.Commands.WriteErrorException,New-SessionDeployment So far, I have: Triple, triple checked syntax. Tried various other commands, and a script to accomplish the same task. Checked DNS is functioning as it should. Checked to the best of my knowledge that AD is working as it should. Checked that the Network Service has the needed permissions. Created another VM and placed the two roles on different servers. Deleted all VMs, started again with a new domain name (Lather, rinse, repeat) Performed the whole installation on a second physical box running Hyper-V Server Pleaded with it Interestingly, if I perform the installation via a GUI installation, the thing just works! Now I know I could convert this to a Server Core role after installation, but this wouldn't teach me what was wrong in the first instance. I've probably got 10 pages through various Google searches, each page getting a little less relevant. The closest matches seem to have good information, but it doesn't seem to be the fix for my set-up. As a side note, I expected to be able to "tee" or "out-file" the error message into a text file, but couldn't get that to work either, so I've typed in the error message manually. Chaps, any suggestions, from the glaringly obvious, to the long-winded and complex? Thanks!

  Read the article

• Start a software company offshore

  - by Mascarpone

  Hello Everybody, I own a small, very young, EU based (Italy) company, and among other things, we sell IT solutions. I have a degree in applied mathematics, and I mainly deal with user interfaces, embedded systems, automation and web applications. You can say that I'm an enlightened entrepreneur because I work only with open source software (OS, IDE, I release under BSD , ... everything is free as in freedom), I give high importance to post sales services and customer satisfaction, plus I think I'm the best boss someone could desire (LOL), as I have google in mind when I think about IT workers rights. But the most beautiful thing is that, although everybody advised us not to use open source, is that we are quite profitable!!! (for the sixth trimester in a row). Now I offshore most of the work to an Indian company. I divide the work in modules and I outsource the longer or more trivial ones. I spend a lot of time defining the specifications and I leave the hard work to them. Using productivity bonuses, a lot of prototypes and third-party audits I think that my software has reached a very good quality level. I would like to start my own software development company, in order to improve control over process and cut costs. Obviously I can't afford the cost of labor in the EU, so I thought about opening a company in Asia. What I need Is: 1) Cheap labor - I can afford to give productivity bonuses and higher than average wages and stay profitable just because labor is cheap. 2) Many talents - I need a good level of tertiary education, and a good number of graduates, so I can hire junior developers and train and teach them according to my needs and philosophies (e.g.: open source mind) 3) Good infrastructure - buildings, transport, internet, .... everything that a company might need. I thought about 3 possible candidates: 1) India - I already work with indian people, I know that they are realiable and speak a good english. Big cities are too expensive, but maybe a small city like lucknow http://en.wikipedia.org/wiki/Lucknow could suits my needs. 2) China - They say it's cheaper than India, but I everytime I worked with a chineese company the language was a big barrier. They work hard, are somewhat skilled and cheap but maybe it's a risky path. Plus I feel a little uncofortable with their lack of human rights. 3) Philippines - Same as china: cheaper than india, but maybe less educated. Where do you think it's the best place to start a software company? Any reading or book to advise? thank you very much

  Read the article

• Managing hosts and iptables in scalable architecture

  - by hakunin

  Let's say I have a load balancer in front of 3 app servers. Let's say I also have these services available at certain IPs: Postgres server Redis server ElasticSearch server Memcached server 1 Memcached server 2 Memcached server 3 So that's 6 nodes at 6 different IP addresses. Naturally, every one of my 3 app servers needs to talk to these 6 servers above. Then, to make it a bit funkier, I also have 3 worker servers. And each worker also talks to the above 6 servers, but thankfully workers and apps never need to talk to each other. Now's the kicker. Everything is on Digital Ocean VPS. What that means is: you have no private network, no private IPs. You only have separate, random IP address on each machine. You can't mask them or anything. So in order to build a secure environment I would have to configure some iptables. For example: Open app servers be accessed by load balancer server Open redis, ES, PG, and each memcached servers to be accessed by each app's IP and each worker's IP This means that every time I add an app or worker I have to also reconfigure iptables in those above 6 servers to welcome the new app or worker. Is there a way to simplify this type of setup? I was thinking — what if there was a gateway machine between apps/workers and the above 6 machines. This way all the interaction would always happen via the gateway server, and when I add a new app or worker I wouldn't need to teach the 6 servers to let it in. If I went this route, then I'd hope a small 512mb server could handle that perhaps, and there wouldn't be almost any overhead. Or would there? Please help with best way to handle this situation. I would appreciate an answer as concrete as possible. I don't think this is too specific, because this general architecture is very common, and Digital Ocean is becoming increasingly popular. A concrete solution here would be much appreciated by many.

  Read the article

• Scrolling an HTML 5 page using JQuery

  - by nikolaosk

  In this post I will show you how to use JQuery to scroll through an HTML 5 page.I had to help a friend of mine to implement this functionality and I thought it would be a good idea to write a post.I will not use any JQuery scrollbar plugin,I will just use the very popular JQuery Library. Please download the library (minified version) from http://jquery.com/download.Please find here all my posts regarding JQuery.Also have a look at my posts regarding HTML 5.In order to be absolutely clear this is not (and could not be) a detailed tutorial on HTML 5. There are other great resources for that.Navigate to the excellent interactive tutorials of W3School.Another excellent resource is HTML 5 Doctor.Two very nice sites that show you what features and specifications are implemented by various browsers and their versions are http://caniuse.com/ and http://html5test.com/. At this times Chrome seems to support most of HTML 5 specifications.Another excellent way to find out if the browser supports HTML 5 and CSS 3 features is to use the Javascript lightweight library Modernizr.In this hands-on example I will be using Expression Web 4.0.This application is not a free application. You can use any HTML editor you like.You can use Visual Studio 2012 Express edition. You can download it here. Let me move on to the actual example.This is the sample HTML 5 page<!DOCTYPE html><html lang="en">  <head>    <title>Liverpool Legends</title>        <meta http-equiv="Content-Type" content="text/html;charset=utf-8" >        <link rel="stylesheet" type="text/css" href="style.css">        <script type="text/javascript" src="jquery-1.8.2.min.js"> </script>     <script type="text/javascript" src="scroll.js">     </script>       </head>  <body>    <header>        <h1>Liverpool Legends</h1>    </header>        <div id="main">        <table>        <caption>Liverpool Players</caption>        <thead>            <tr>                <th>Name</th>                <th>Photo</th>                <th>Position</th>                <th>Age</th>                <th>Scroll</th>            </tr>        </thead>        <tfoot class="footnote">            <tr>                <td colspan="4">We will add more photos soon</td>            </tr>        </tfoot>    <tbody>        <tr class="maintop">        <td>Alan Hansen</td>            <td>            <figure>            <img src="images\Alan-hansen-large.jpg" alt="Alan Hansen">            <figcaption>The best Liverpool Defender <a href="http://en.wikipedia.org/wiki/Alan_Hansen">Alan Hansen</a></figcaption>            </figure>            </td>            <td>Defender</td>            <td>57</td>            <td class="top">Middle</td>        </tr>        <tr>        <td>Graeme Souness</td>            <td>            <figure>            <img src="images\graeme-souness-large.jpg" alt="Graeme Souness">            <figcaption>Souness was the captain of the successful Liverpool team of the early 1980s <a href="http://en.wikipedia.org/wiki/Graeme_Souness">Graeme Souness</a></figcaption>            </figure>            </td>            <td>MidFielder</td>            <td>59</td>        </tr>        <tr>        <td>Ian Rush</td>            <td>            <figure>            <img src="images\ian-rush-large.jpg" alt="Ian Rush">            <figcaption>The deadliest Liverpool Striker <a href="http://it.wikipedia.org/wiki/Ian_Rush">Ian Rush</a></figcaption>            </figure>            </td>            <td>Striker</td>            <td>51</td>        </tr>        <tr class="mainmiddle">        <td>John Barnes</td>            <td>            <figure>            <img src="images\john-barnes-large.jpg" alt="John Barnes">            <figcaption>The best Liverpool Defender <a href="http://en.wikipedia.org/wiki/John_Barnes_(footballer)">John Barnes</a></figcaption>            </figure>            </td>            <td>MidFielder</td>            <td>49</td>            <td class="middle">Bottom</td>        </tr>                <tr>        <td>Kenny Dalglish</td>            <td>            <figure>            <img src="images\kenny-dalglish-large.jpg" alt="Kenny Dalglish">            <figcaption>King Kenny <a href="http://en.wikipedia.org/wiki/Kenny_Dalglish">Kenny Dalglish</a></figcaption>            </figure>            </td>            <td>Midfielder</td>            <td>61</td>        </tr>        <tr>            <td>Michael Owen</td>            <td>            <figure>            <img src="images\michael-owen-large.jpg" alt="Michael Owen">            <figcaption>Michael was Liverpool's top goal scorer from 1997–2004 <a href="http://www.michaelowen.com/">Michael Owen</a></figcaption>            </figure>            </td>            <td>Striker</td>            <td>33</td>        </tr>        <tr>            <td>Robbie Fowler</td>            <td>            <figure>            <img src="images\robbie-fowler-large.jpg" alt="Robbie Fowler">            <figcaption>Fowler scored 183 goals in total for Liverpool <a href="http://en.wikipedia.org/wiki/Robbie_Fowler">Robbie Fowler</a></figcaption>            </figure>            </td>            <td>Striker</td>            <td>38</td>        </tr>        <tr class="mainbottom">            <td>Steven Gerrard</td>            <td>            <figure>            <img src="images\steven-gerrard-large.jpg" alt="Steven Gerrard">            <figcaption>Liverpool's captain <a href="http://en.wikipedia.org/wiki/Steven_Gerrard">Steven Gerrard</a></figcaption>            </figure>            </td>            <td>Midfielder</td>            <td>32</td>            <td class="bottom">Top</td>        </tr>    </tbody></table>          </div>            <footer>        <p>All Rights Reserved</p>      </footer>     </body>  </html>  The markup is very easy to follow and understand. You do not have to type all the code,simply copy and paste it.For those that you are not familiar with HTML 5, please take a closer look at the new tags/elements introduced with HTML 5.When I view the HTML 5 page with Firefox I see the following result. I have also an external stylesheet (style.css). body{background-color:#efefef;}h1{font-size:2.3em;}table { border-collapse: collapse;font-family: Futura, Arial, sans-serif; }caption { font-size: 1.2em; margin: 1em auto; }th, td {padding: .65em; }th, thead { background: #000; color: #fff; border: 1px solid #000; }tr:nth-child(odd) { background: #ccc; }tr:nth-child(even) { background: #404040; }td { border-right: 1px solid #777; }table { border: 1px solid #777;  }.top, .middle, .bottom {    cursor: pointer;    font-size: 22px;    font-weight: bold;    text-align: center;}.footnote{text-align:center;font-family:Tahoma;color:#EB7515;}a{color:#22577a;text-decoration:none;}     a:hover {color:#125949; text-decoration:none;}  footer{background-color:#505050;width:1150px;}These are just simple CSS Rules that style the various HTML 5 tags,classes. The jQuery code that makes it all possible resides inside the scroll.js file.Make sure you type everything correctly.$(document).ready(function() {                 $('.top').click(function(){                     $('html, body').animate({                         scrollTop: $(".mainmiddle").offset().top                     },4000 );                  });                 $('.middle').click(function(){                     $('html, body').animate({                         scrollTop: $(".mainbottom").offset().top                     },4000);                  });                     $('.bottom').click(function(){                     $('html, body').animate({                         scrollTop: $(".maintop").offset().top                     },4000);                  }); });  Let me explain what I am doing here.When I click on the Middle word (  $('.top').click(function(){ ) this relates to the top class that is clicked.Then we declare the elements that we want to participate in the scrolling. In this case is html,body ( $('html, body').animate).These elements will be part of the vertical scrolling.In the next line of code we simply move (navigate) to the element (class mainmiddle that is attached to a tr element.)      scrollTop: $(".mainmiddle").offset().top  Make sure you type all the code correctly and try it for yourself. I have tested this solution will all 4-5 major browsers.Hope it helps!!!

  Read the article

• Using R to Analyze G1GC Log Files

  - by user12620111

  Using R to Analyze G1GC Log Files body, td { font-family: sans-serif; background-color: white; font-size: 12px; margin: 8px; } tt, code, pre { font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace; } h1 { font-size:2.2em; } h2 { font-size:1.8em; } h3 { font-size:1.4em; } h4 { font-size:1.0em; } h5 { font-size:0.9em; } h6 { font-size:0.8em; } a:visited { color: rgb(50%, 0%, 50%); } pre { margin-top: 0; max-width: 95%; border: 1px solid #ccc; white-space: pre-wrap; } pre code { display: block; padding: 0.5em; } code.r, code.cpp { background-color: #F8F8F8; } table, td, th { border: none; } blockquote { color:#666666; margin:0; padding-left: 1em; border-left: 0.5em #EEE solid; } hr { height: 0px; border-bottom: none; border-top-width: thin; border-top-style: dotted; border-top-color: #999999; } @media print { * { background: transparent !important; color: black !important; filter:none !important; -ms-filter: none !important; } body { font-size:12pt; max-width:100%; } a, a:visited { text-decoration: underline; } hr { visibility: hidden; page-break-before: always; } pre, blockquote { padding-right: 1em; page-break-inside: avoid; } tr, img { page-break-inside: avoid; } img { max-width: 100% !important; } @page :left { margin: 15mm 20mm 15mm 10mm; } @page :right { margin: 15mm 10mm 15mm 20mm; } p, h2, h3 { orphans: 3; widows: 3; } h2, h3 { page-break-after: avoid; } } pre .operator, pre .paren { color: rgb(104, 118, 135) } pre .literal { color: rgb(88, 72, 246) } pre .number { color: rgb(0, 0, 205); } pre .comment { color: rgb(76, 136, 107); } pre .keyword { color: rgb(0, 0, 255); } pre .identifier { color: rgb(0, 0, 0); } pre .string { color: rgb(3, 106, 7); } var hljs=new function(){function m(p){return p.replace(/&/gm,"&").replace(/"}while(y.length||w.length){var v=u().splice(0,1)[0];z+=m(x.substr(q,v.offset-q));q=v.offset;if(v.event=="start"){z+=t(v.node);s.push(v.node)}else{if(v.event=="stop"){var p,r=s.length;do{r--;p=s[r];z+=("")}while(p!=v.node);s.splice(r,1);while(r'+M[0]+""}else{r+=M[0]}O=P.lR.lastIndex;M=P.lR.exec(L)}return r+L.substr(O,L.length-O)}function J(L,M){if(M.sL&&e[M.sL]){var r=d(M.sL,L);x+=r.keyword_count;return r.value}else{return F(L,M)}}function I(M,r){var L=M.cN?'':"";if(M.rB){y+=L;M.buffer=""}else{if(M.eB){y+=m(r)+L;M.buffer=""}else{y+=L;M.buffer=r}}D.push(M);A+=M.r}function G(N,M,Q){var R=D[D.length-1];if(Q){y+=J(R.buffer+N,R);return false}var P=q(M,R);if(P){y+=J(R.buffer+N,R);I(P,M);return P.rB}var L=v(D.length-1,M);if(L){var O=R.cN?"":"";if(R.rE){y+=J(R.buffer+N,R)+O}else{if(R.eE){y+=J(R.buffer+N,R)+O+m(M)}else{y+=J(R.buffer+N+M,R)+O}}while(L1){O=D[D.length-2].cN?"":"";y+=O;L--;D.length--}var r=D[D.length-1];D.length--;D[D.length-1].buffer="";if(r.starts){I(r.starts,"")}return R.rE}if(w(M,R)){throw"Illegal"}}var E=e[B];var D=[E.dM];var A=0;var x=0;var y="";try{var s,u=0;E.dM.buffer="";do{s=p(C,u);var t=G(s[0],s[1],s[2]);u+=s[0].length;if(!t){u+=s[1].length}}while(!s[2]);if(D.length1){throw"Illegal"}return{r:A,keyword_count:x,value:y}}catch(H){if(H=="Illegal"){return{r:0,keyword_count:0,value:m(C)}}else{throw H}}}function g(t){var p={keyword_count:0,r:0,value:m(t)};var r=p;for(var q in e){if(!e.hasOwnProperty(q)){continue}var s=d(q,t);s.language=q;if(s.keyword_count+s.rr.keyword_count+r.r){r=s}if(s.keyword_count+s.rp.keyword_count+p.r){r=p;p=s}}if(r.language){p.second_best=r}return p}function i(r,q,p){if(q){r=r.replace(/^((]+|\t)+)/gm,function(t,w,v,u){return w.replace(/\t/g,q)})}if(p){r=r.replace(/\n/g,"")}return r}function n(t,w,r){var x=h(t,r);var v=a(t);var y,s;if(v){y=d(v,x)}else{return}var q=c(t);if(q.length){s=document.createElement("pre");s.innerHTML=y.value;y.value=k(q,c(s),x)}y.value=i(y.value,w,r);var u=t.className;if(!u.match("(\\s|^)(language-)?"+v+"(\\s|$)")){u=u?(u+" "+v):v}if(/MSIE [678]/.test(navigator.userAgent)&&t.tagName=="CODE"&&t.parentNode.tagName=="PRE"){s=t.parentNode;var p=document.createElement("div");p.innerHTML=""+y.value+"";t=p.firstChild.firstChild;p.firstChild.cN=s.cN;s.parentNode.replaceChild(p.firstChild,s)}else{t.innerHTML=y.value}t.className=u;t.result={language:v,kw:y.keyword_count,re:y.r};if(y.second_best){t.second_best={language:y.second_best.language,kw:y.second_best.keyword_count,re:y.second_best.r}}}function o(){if(o.called){return}o.called=true;var r=document.getElementsByTagName("pre");for(var p=0;p|=||=||=|\\?|\\[|\\{|\\(|\\^|\\^=|\\||\\|=|\\|\\||~";this.ER="(?![\\s\\S])";this.BE={b:"\\\\.",r:0};this.ASM={cN:"string",b:"'",e:"'",i:"\\n",c:[this.BE],r:0};this.QSM={cN:"string",b:'"',e:'"',i:"\\n",c:[this.BE],r:0};this.CLCM={cN:"comment",b:"//",e:"$"};this.CBLCLM={cN:"comment",b:"/\\*",e:"\\*/"};this.HCM={cN:"comment",b:"#",e:"$"};this.NM={cN:"number",b:this.NR,r:0};this.CNM={cN:"number",b:this.CNR,r:0};this.BNM={cN:"number",b:this.BNR,r:0};this.inherit=function(r,s){var p={};for(var q in r){p[q]=r[q]}if(s){for(var q in s){p[q]=s[q]}}return p}}();hljs.LANGUAGES.cpp=function(){var a={keyword:{"false":1,"int":1,"float":1,"while":1,"private":1,"char":1,"catch":1,"export":1,virtual:1,operator:2,sizeof:2,dynamic_cast:2,typedef:2,const_cast:2,"const":1,struct:1,"for":1,static_cast:2,union:1,namespace:1,unsigned:1,"long":1,"throw":1,"volatile":2,"static":1,"protected":1,bool:1,template:1,mutable:1,"if":1,"public":1,friend:2,"do":1,"return":1,"goto":1,auto:1,"void":2,"enum":1,"else":1,"break":1,"new":1,extern:1,using:1,"true":1,"class":1,asm:1,"case":1,typeid:1,"short":1,reinterpret_cast:2,"default":1,"double":1,register:1,explicit:1,signed:1,typename:1,"try":1,"this":1,"switch":1,"continue":1,wchar_t:1,inline:1,"delete":1,alignof:1,char16_t:1,char32_t:1,constexpr:1,decltype:1,noexcept:1,nullptr:1,static_assert:1,thread_local:1,restrict:1,_Bool:1,complex:1},built_in:{std:1,string:1,cin:1,cout:1,cerr:1,clog:1,stringstream:1,istringstream:1,ostringstream:1,auto_ptr:1,deque:1,list:1,queue:1,stack:1,vector:1,map:1,set:1,bitset:1,multiset:1,multimap:1,unordered_set:1,unordered_map:1,unordered_multiset:1,unordered_multimap:1,array:1,shared_ptr:1}};return{dM:{k:a,i:"",k:a,r:10,c:["self"]}]}}}();hljs.LANGUAGES.r={dM:{c:[hljs.HCM,{cN:"number",b:"\\b0[xX][0-9a-fA-F]+[Li]?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+(?:[eE][+\\-]?\\d*)?L\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+\\.(?!\\d)(?:i\\b)?",e:hljs.IMMEDIATE_RE,r:1},{cN:"number",b:"\\b\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"keyword",b:"(?:tryCatch|library|setGeneric|setGroupGeneric)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\.",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\d+(?![\\w.])",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\b(?:function)",e:hljs.IMMEDIATE_RE,r:2},{cN:"keyword",b:"(?:if|in|break|next|repeat|else|for|return|switch|while|try|stop|warning|require|attach|detach|source|setMethod|setClass)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"literal",b:"(?:NA|NA_integer_|NA_real_|NA_character_|NA_complex_)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"literal",b:"(?:NULL|TRUE|FALSE|T|F|Inf|NaN)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"identifier",b:"[a-zA-Z.][a-zA-Z0-9._]*\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"operator",b:"|=||   Using R to Analyze G1GC Log Files   Using R to Analyze G1GC Log Files Introduction Working in Oracle Platform Integration gives an engineer opportunities to work on a wide array of technologies. My team’s goal is to make Oracle applications run best on the Solaris/SPARC platform. When looking for bottlenecks in a modern applications, one needs to be aware of not only how the CPUs and operating system are executing, but also network, storage, and in some cases, the Java Virtual Machine. I was recently presented with about 1.5 GB of Java Garbage First Garbage Collector log file data. If you’re not familiar with the subject, you might want to review Garbage First Garbage Collector Tuning by Monica Beckwith. The customer had been running Java HotSpot 1.6.0_31 to host a web application server. I was told that the Solaris/SPARC server was running a Java process launched using a commmand line that included the following flags: -d64 -Xms9g -Xmx9g -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:InitiatingHeapOccupancyPercent=80 -XX:PermSize=256m -XX:MaxPermSize=256m -XX:+PrintGC -XX:+PrintGCTimeStamps -XX:+PrintHeapAtGC -XX:+PrintGCDateStamps -XX:+PrintFlagsFinal -XX:+DisableExplicitGC -XX:+UnlockExperimentalVMOptions -XX:ParallelGCThreads=8 Several sources on the internet indicate that if I were to print out the 1.5 GB of log files, it would require enough paper to fill the bed of a pick up truck. Of course, it would be fruitless to try to scan the log files by hand. Tools will be required to summarize the contents of the log files. Others have encountered large Java garbage collection log files. There are existing tools to analyze the log files: IBM’s GC toolkit The chewiebug GCViewer gchisto HPjmeter Instead of using one of the other tools listed, I decide to parse the log files with standard Unix tools, and analyze the data with R. Data Cleansing The log files arrived in two different formats. I guess that the difference is that one set of log files was generated using a more verbose option, maybe -XX:+PrintHeapAtGC, and the other set of log files was generated without that option. Format 1 In some of the log files, the log files with the less verbose format, a single trace, i.e. the report of a singe garbage collection event, looks like this: {Heap before GC invocations=12280 (full 61): garbage-first heap total 9437184K, used 7499918K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 1 young (4096K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. 2014-05-14T07:24:00.988-0700: 60586.353: [GC pause (young) 7324M->7320M(9216M), 0.1567265 secs] Heap after GC invocations=12281 (full 61): garbage-first heap total 9437184K, used 7496533K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 0 young (0K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. } A simple grep can be used to extract a summary: $ grep "\[ GC pause (young" g1gc.log 2014-05-13T13:24:35.091-0700: 3.109: [GC pause (young) 20M->5029K(9216M), 0.0146328 secs] 2014-05-13T13:24:35.440-0700: 3.459: [GC pause (young) 9125K->6077K(9216M), 0.0086723 secs] 2014-05-13T13:24:37.581-0700: 5.599: [GC pause (young) 25M->8470K(9216M), 0.0203820 secs] 2014-05-13T13:24:42.686-0700: 10.704: [GC pause (young) 44M->15M(9216M), 0.0288848 secs] 2014-05-13T13:24:48.941-0700: 16.958: [GC pause (young) 51M->20M(9216M), 0.0491244 secs] 2014-05-13T13:24:56.049-0700: 24.066: [GC pause (young) 92M->26M(9216M), 0.0525368 secs] 2014-05-13T13:25:34.368-0700: 62.383: [GC pause (young) 602M->68M(9216M), 0.1721173 secs] But that format wasn't easily read into R, so I needed to be a bit more tricky. I used the following Unix command to create a summary file that was easy for R to read. $ echo "SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime" $ grep "\[GC pause (young" g1gc.log | grep -v mark | sed -e 's/[A-SU-z\(\),]/ /g' -e 's/->/ /' -e 's/: / /g' | more SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime 2014-05-13T13:24:35.091-0700 3.109 20 5029 9216 0.0146328 2014-05-13T13:24:35.440-0700 3.459 9125 6077 9216 0.0086723 2014-05-13T13:24:37.581-0700 5.599 25 8470 9216 0.0203820 2014-05-13T13:24:42.686-0700 10.704 44 15 9216 0.0288848 2014-05-13T13:24:48.941-0700 16.958 51 20 9216 0.0491244 2014-05-13T13:24:56.049-0700 24.066 92 26 9216 0.0525368 2014-05-13T13:25:34.368-0700 62.383 602 68 9216 0.1721173 Format 2 In some of the log files, the log files with the more verbose format, a single trace, i.e. the report of a singe garbage collection event, was more complicated than Format 1. Here is a text file with an example of a single G1GC trace in the second format. As you can see, it is quite complicated. It is nice that there is so much information available, but the level of detail can be overwhelming. I wrote this awk script (download) to summarize each trace on a single line. #!/usr/bin/env awk -f BEGIN { printf("SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize\n") } ###################### # Save count data from lines that are at the start of each G1GC trace. # Each trace starts out like this: # {Heap before GC invocations=14 (full 0): # garbage-first heap total 9437184K, used 325496K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) ###################### /{Heap.*full/{ gsub ( "\\)" , "" ); nf=split($0,a,"="); split(a[2],b," "); getline; if ( match($0, "first") ) { G1GC=1; IncrementalCount=b[1]; FullCount=substr( b[3], 1, length(b[3])-1 ); } else { G1GC=0; } } ###################### # Pull out time stamps that are in lines with this format: # 2014-05-12T14:02:06.025-0700: 94.312: [GC pause (young), 0.08870154 secs] ###################### /GC pause/ { DateTime=$1; SecondsSinceLaunch=substr($2, 1, length($2)-1); } ###################### # Heap sizes are in lines that look like this: # [ 4842M->4838M(9216M)] ###################### /\[ .*]$/ { gsub ( "\\[" , "" ); gsub ( "\ \]" , "" ); gsub ( "->" , " " ); gsub ( "\\( " , " " ); gsub ( "\ \)" , " " ); split($0,a," "); if ( split(a[1],b,"M") > 1 ) {BeforeSize=b[1]*1024;} if ( split(a[1],b,"K") > 1 ) {BeforeSize=b[1];} if ( split(a[2],b,"M") > 1 ) {AfterSize=b[1]*1024;} if ( split(a[2],b,"K") > 1 ) {AfterSize=b[1];} if ( split(a[3],b,"M") > 1 ) {TotalSize=b[1]*1024;} if ( split(a[3],b,"K") > 1 ) {TotalSize=b[1];} } ###################### # Emit an output line when you find input that looks like this: # [Times: user=1.41 sys=0.08, real=0.24 secs] ###################### /\[Times/ { if (G1GC==1) { gsub ( "," , "" ); split($2,a,"="); UserTime=a[2]; split($3,a,"="); SysTime=a[2]; split($4,a,"="); RealTime=a[2]; print DateTime,SecondsSinceLaunch,IncrementalCount,FullCount,UserTime,SysTime,RealTime,BeforeSize,AfterSize,TotalSize; G1GC=0; } } The resulting summary is about 25X smaller that the original file, but still difficult for a human to digest. SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ... 2014-05-12T18:36:34.669-0700: 3985.744 561 0 0.57 0.06 0.16 1724416 1720320 9437184 2014-05-12T18:36:34.839-0700: 3985.914 562 0 0.51 0.06 0.19 1724416 1720320 9437184 2014-05-12T18:36:35.069-0700: 3986.144 563 0 0.60 0.04 0.27 1724416 1721344 9437184 2014-05-12T18:36:35.354-0700: 3986.429 564 0 0.33 0.04 0.09 1725440 1722368 9437184 2014-05-12T18:36:35.545-0700: 3986.620 565 0 0.58 0.04 0.17 1726464 1722368 9437184 2014-05-12T18:36:35.726-0700: 3986.801 566 0 0.43 0.05 0.12 1726464 1722368 9437184 2014-05-12T18:36:35.856-0700: 3986.930 567 0 0.30 0.04 0.07 1726464 1723392 9437184 2014-05-12T18:36:35.947-0700: 3987.023 568 0 0.61 0.04 0.26 1727488 1723392 9437184 2014-05-12T18:36:36.228-0700: 3987.302 569 0 0.46 0.04 0.16 1731584 1724416 9437184 Reading the Data into R Once the GC log data had been cleansed, either by processing the first format with the shell script, or by processing the second format with the awk script, it was easy to read the data into R. g1gc.df = read.csv("summary.txt", row.names = NULL, stringsAsFactors=FALSE,sep="") str(g1gc.df) ## 'data.frame': 8307 obs. of 10 variables: ## $ row.names : chr "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ... ## $ SecondsSinceLaunch: num 1.16 1.47 1.97 3.83 6.1 ... ## $ IncrementalCount : int 0 1 2 3 4 5 6 7 8 9 ... ## $ FullCount : int 0 0 0 0 0 0 0 0 0 0 ... ## $ UserTime : num 0.11 0.05 0.04 0.21 0.08 0.26 0.31 0.33 0.34 0.56 ... ## $ SysTime : num 0.04 0.01 0.01 0.05 0.01 0.06 0.07 0.06 0.07 0.09 ... ## $ RealTime : num 0.02 0.02 0.01 0.04 0.02 0.04 0.05 0.04 0.04 0.06 ... ## $ BeforeSize : int 8192 5496 5768 22528 24576 43008 34816 53248 55296 93184 ... ## $ AfterSize : int 1400 1672 2557 4907 7072 14336 16384 18432 19456 21504 ... ## $ TotalSize : int 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 ... head(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount ## 1 2014-05-12T14:00:32.868-0700: 1.161 0 ## 2 2014-05-12T14:00:33.179-0700: 1.472 1 ## 3 2014-05-12T14:00:33.677-0700: 1.969 2 ## 4 2014-05-12T14:00:35.538-0700: 3.830 3 ## 5 2014-05-12T14:00:37.811-0700: 6.103 4 ## 6 2014-05-12T14:00:41.428-0700: 9.720 5 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 1 0 0.11 0.04 0.02 8192 1400 9437184 ## 2 0 0.05 0.01 0.02 5496 1672 9437184 ## 3 0 0.04 0.01 0.01 5768 2557 9437184 ## 4 0 0.21 0.05 0.04 22528 4907 9437184 ## 5 0 0.08 0.01 0.02 24576 7072 9437184 ## 6 0 0.26 0.06 0.04 43008 14336 9437184 Basic Statistics Once the data has been read into R, simple statistics are very easy to generate. All of the numbers from high school statistics are available via simple commands. For example, generate a summary of every column: summary(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount FullCount ## Length:8307 Min. : 1 Min. : 0 Min. : 0.0 ## Class :character 1st Qu.: 9977 1st Qu.:2048 1st Qu.: 0.0 ## Mode :character Median :12855 Median :4136 Median : 12.0 ## Mean :12527 Mean :4156 Mean : 31.6 ## 3rd Qu.:15758 3rd Qu.:6262 3rd Qu.: 61.0 ## Max. :55484 Max. :8391 Max. :113.0 ## UserTime SysTime RealTime BeforeSize ## Min. :0.040 Min. :0.0000 Min. : 0.0 Min. : 5476 ## 1st Qu.:0.470 1st Qu.:0.0300 1st Qu.: 0.1 1st Qu.:5137920 ## Median :0.620 Median :0.0300 Median : 0.1 Median :6574080 ## Mean :0.751 Mean :0.0355 Mean : 0.3 Mean :5841855 ## 3rd Qu.:0.920 3rd Qu.:0.0400 3rd Qu.: 0.2 3rd Qu.:7084032 ## Max. :3.370 Max. :1.5600 Max. :488.1 Max. :8696832 ## AfterSize TotalSize ## Min. : 1380 Min. :9437184 ## 1st Qu.:5002752 1st Qu.:9437184 ## Median :6559744 Median :9437184 ## Mean :5785454 Mean :9437184 ## 3rd Qu.:7054336 3rd Qu.:9437184 ## Max. :8482816 Max. :9437184 Q: What is the total amount of User CPU time spent in garbage collection? sum(g1gc.df$UserTime) ## [1] 6236 As you can see, less than two hours of CPU time was spent in garbage collection. Is that too much? To find the percentage of time spent in garbage collection, divide the number above by total_elapsed_time*CPU_count. In this case, there are a lot of CPU’s and it turns out the the overall amount of CPU time spent in garbage collection isn’t a problem when viewed in isolation. When calculating rates, i.e. events per unit time, you need to ask yourself if the rate is homogenous across the time period in the log file. Does the log file include spikes of high activity that should be separately analyzed? Averaging in data from nights and weekends with data from business hours may alias problems. If you have a reason to suspect that the garbage collection rates include peaks and valleys that need independent analysis, see the “Time Series” section, below. Q: How much garbage is collected on each pass? The amount of heap space that is recovered per GC pass is surprisingly low: At least one collection didn’t recover any data. (“Min.=0”) 25% of the passes recovered 3MB or less. (“1st Qu.=3072”) Half of the GC passes recovered 4MB or less. (“Median=4096”) The average amount recovered was 56MB. (“Mean=56390”) 75% of the passes recovered 36MB or less. (“3rd Qu.=36860”) At least one pass recovered 2GB. (“Max.=2121000”) g1gc.df$Delta = g1gc.df$BeforeSize - g1gc.df$AfterSize summary(g1gc.df$Delta) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0 3070 4100 56400 36900 2120000 Q: What is the maximum User CPU time for a single collection? The worst garbage collection (“Max.”) is many standard deviations away from the mean. The data appears to be right skewed. summary(g1gc.df$UserTime) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0.040 0.470 0.620 0.751 0.920 3.370 sd(g1gc.df$UserTime) ## [1] 0.3966 Basic Graphics Once the data is in R, it is trivial to plot the data with formats including dot plots, line charts, bar charts (simple, stacked, grouped), pie charts, boxplots, scatter plots histograms, and kernel density plots. Histogram of User CPU Time per Collection I don't think that this graph requires any explanation. hist(g1gc.df$UserTime, main="User CPU Time per Collection", xlab="Seconds", ylab="Frequency") Box plot to identify outliers When the initial data is viewed with a box plot, you can see the one crazy outlier in the real time per GC. Save this data point for future analysis and drop the outlier so that it’s not throwing off our statistics. Now the box plot shows many outliers, which will be examined later, using times series analysis. Notice that the scale of the x-axis changes drastically once the crazy outlier is removed. par(mfrow=c(2,1)) boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(dominated by a crazy outlier)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") crazy.outlier.df=g1gc.df[g1gc.df$RealTime > 400,] g1gc.df=g1gc.df[g1gc.df$RealTime < 400,] boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(crazy outlier excluded)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") box(which = "outer", lty = "solid") Here is the crazy outlier for future analysis: crazy.outlier.df ## row.names SecondsSinceLaunch IncrementalCount ## 8233 2014-05-12T23:15:43.903-0700: 20741 8316 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 8233 112 0.55 0.42 488.1 8381440 8235008 9437184 ## Delta ## 8233 146432 R Time Series Data To analyze the garbage collection as a time series, I’ll use Z’s Ordered Observations (zoo). “zoo is the creator for an S3 class of indexed totally ordered observations which includes irregular time series.” require(zoo) ## Loading required package: zoo ## ## Attaching package: 'zoo' ## ## The following objects are masked from 'package:base': ## ## as.Date, as.Date.numeric head(g1gc.df[,1]) ## [1] "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" ## [3] "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ## [5] "2014-05-12T14:00:37.811-0700:" "2014-05-12T14:00:41.428-0700:" options("digits.secs"=3) times=as.POSIXct( g1gc.df[,1], format="%Y-%m-%dT%H:%M:%OS%z:") g1gc.z = zoo(g1gc.df[,-c(1)], order.by=times) head(g1gc.z) ## SecondsSinceLaunch IncrementalCount FullCount ## 2014-05-12 17:00:32.868 1.161 0 0 ## 2014-05-12 17:00:33.178 1.472 1 0 ## 2014-05-12 17:00:33.677 1.969 2 0 ## 2014-05-12 17:00:35.538 3.830 3 0 ## 2014-05-12 17:00:37.811 6.103 4 0 ## 2014-05-12 17:00:41.427 9.720 5 0 ## UserTime SysTime RealTime BeforeSize AfterSize ## 2014-05-12 17:00:32.868 0.11 0.04 0.02 8192 1400 ## 2014-05-12 17:00:33.178 0.05 0.01 0.02 5496 1672 ## 2014-05-12 17:00:33.677 0.04 0.01 0.01 5768 2557 ## 2014-05-12 17:00:35.538 0.21 0.05 0.04 22528 4907 ## 2014-05-12 17:00:37.811 0.08 0.01 0.02 24576 7072 ## 2014-05-12 17:00:41.427 0.26 0.06 0.04 43008 14336 ## TotalSize Delta ## 2014-05-12 17:00:32.868 9437184 6792 ## 2014-05-12 17:00:33.178 9437184 3824 ## 2014-05-12 17:00:33.677 9437184 3211 ## 2014-05-12 17:00:35.538 9437184 17621 ## 2014-05-12 17:00:37.811 9437184 17504 ## 2014-05-12 17:00:41.427 9437184 28672 Example of Two Benchmark Runs in One Log File The data in the following graph is from a different log file, not the one of primary interest to this article. I’m including this image because it is an example of idle periods followed by busy periods. It would be uninteresting to average the rate of garbage collection over the entire log file period. More interesting would be the rate of garbage collect in the two busy periods. Are they the same or different? Your production data may be similar, for example, bursts when employees return from lunch and idle times on weekend evenings, etc. Once the data is in an R Time Series, you can analyze isolated time windows. Clipping the Time Series data Flashing back to our test case… Viewing the data as a time series is interesting. You can see that the work intensive time period is between 9:00 PM and 3:00 AM. Lets clip the data to the interesting period:     par(mfrow=c(2,1)) plot(g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Complete Log File", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") clipped.g1gc.z=window(g1gc.z, start=as.POSIXct("2014-05-12 21:00:00"), end=as.POSIXct("2014-05-13 03:00:00")) plot(clipped.g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Limited to Benchmark Execution", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") box(which = "outer", lty = "solid") Cumulative Incremental and Full GC count Here is the cumulative incremental and full GC count. When the line is very steep, it indicates that the GCs are repeating very quickly. Notice that the scale on the Y axis is different for full vs. incremental. plot(clipped.g1gc.z[,c(2:3)], main="Cumulative Incremental and Full GC count", xlab="Time of Day", col="#1b9e77") GC Analysis of Benchmark Execution using Time Series data In the following series of 3 graphs: The “After Size” show the amount of heap space in use after each garbage collection. Many Java objects are still referenced, i.e. alive, during each garbage collection. This may indicate that the application has a memory leak, or may indicate that the application has a very large memory footprint. Typically, an application's memory footprint plateau's in the early stage of execution. One would expect this graph to have a flat top. The steep decline in the heap space may indicate that the application crashed after 2:00. The second graph shows that the outliers in real execution time, discussed above, occur near 2:00. when the Java heap seems to be quite full. The third graph shows that Full GCs are infrequent during the first few hours of execution. The rate of Full GC's, (the slope of the cummulative Full GC line), changes near midnight.   plot(clipped.g1gc.z[,c("AfterSize","RealTime","FullCount")], xlab="Time of Day", col=c("#1b9e77","red","#1b9e77")) GC Analysis of heap recovered Each GC trace includes the amount of heap space in use before and after the individual GC event. During garbage coolection, unreferenced objects are identified, the space holding the unreferenced objects is freed, and thus, the difference in before and after usage indicates how much space has been freed. The following box plot and bar chart both demonstrate the same point - the amount of heap space freed per garbage colloection is surprisingly low. par(mfrow=c(2,1)) boxplot(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", horizontal = TRUE, col="red") hist(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", breaks=100, col="red") box(which = "outer", lty = "solid") This graph is the most interesting. The dark blue area shows how much heap is occupied by referenced Java objects. This represents memory that holds live data. The red fringe at the top shows how much data was recovered after each garbage collection. barplot(clipped.g1gc.z[,c("AfterSize","Delta")], col=c("#7570b3","#e7298a"), xlab="Time of Day", border=NA) legend("topleft", c("Live Objects","Heap Recovered on GC"), fill=c("#7570b3","#e7298a")) box(which = "outer", lty = "solid") When I discuss the data in the log files with the customer, I will ask for an explaination for the large amount of referenced data resident in the Java heap. There are two are posibilities: There is a memory leak and the amount of space required to hold referenced objects will continue to grow, limited only by the maximum heap size. After the maximum heap size is reached, the JVM will throw an “Out of Memory” exception every time that the application tries to allocate a new object. If this is the case, the aplication needs to be debugged to identify why old objects are referenced when they are no longer needed. The application has a legitimate requirement to keep a large amount of data in memory. The customer may want to further increase the maximum heap size. Another possible solution would be to partition the application across multiple cluster nodes, where each node has responsibility for managing a unique subset of the data. Conclusion In conclusion, R is a very powerful tool for the analysis of Java garbage collection log files. The primary difficulty is data cleansing so that information can be read into an R data frame. Once the data has been read into R, a rich set of tools may be used for thorough evaluation.

  Read the article

• MySQL is running VERY slow

  - by user1032531

  I have two servers: a VPS and a laptop. I recently re-built both of them, and MySQL is running about 20 times slower on the laptop. Both servers used to run CentOS 5.8 and I think MySQL 5.1, and the laptop used to do great so I do not think it is the hardware. For the VPS, my provider installed CentOS 6.4, and then I installed MySQL 5.1.69 using yum with the CentOS repo. For the laptop, I installed CentOS 6.4 basic server and then installed MySQL 5.1.69 using yum with the CentOS repo. my.cnf for both servers are identical, and I have shown below. For both servers, I've also included below the output from SHOW VARIABLES; as well as output from sysbench, file system information, and cpu information. I have tried adding skip-name-resolve, but it didn't help. The matrix below shows the SHOW VARIABLES output from both servers which is different. Again, MySQL was installed the same way, so I do not know why it is different, but it is and I think this might be why the laptop is executing MySQL so slowly. Why is the laptop running MySQL slowly, and how do I fix it? Differences between SHOW VARIABLES on both servers +---------------------------+-----------------------+-------------------------+ | Variable | Value-VPS | Value-Laptop | +---------------------------+-----------------------+-------------------------+ | hostname | vps.site1.com | laptop.site2.com | | max_binlog_cache_size | 4294963200 | 18446744073709500000 | | max_seeks_for_key | 4294967295 | 18446744073709500000 | | max_write_lock_count | 4294967295 | 18446744073709500000 | | myisam_max_sort_file_size | 2146435072 | 9223372036853720000 | | myisam_mmap_size | 4294967295 | 18446744073709500000 | | plugin_dir | /usr/lib/mysql/plugin | /usr/lib64/mysql/plugin | | pseudo_thread_id | 7568 | 2 | | system_time_zone | EST | PDT | | thread_stack | 196608 | 262144 | | timestamp | 1372252112 | 1372252046 | | version_compile_machine | i386 | x86_64 | +---------------------------+-----------------------+-------------------------+ my.cnf for both servers [root@server1 ~]# cat /etc/my.cnf [mysqld] datadir=/var/lib/mysql socket=/var/lib/mysql/mysql.sock user=mysql # Disabling symbolic-links is recommended to prevent assorted security risks symbolic-links=0 [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid innodb_strict_mode=on sql_mode=TRADITIONAL # sql_mode=STRICT_TRANS_TABLES,NO_ZERO_DATE,NO_ZERO_IN_DATE character-set-server=utf8 collation-server=utf8_general_ci log=/var/log/mysqld_all.log [root@server1 ~]# VPS SHOW VARIABLES Info Same as Laptop shown below but changes per above matrix (removed to allow me to be under the 30000 characters as required by ServerFault) Laptop SHOW VARIABLES Info auto_increment_increment 1 auto_increment_offset 1 autocommit ON automatic_sp_privileges ON back_log 50 basedir /usr/ big_tables OFF binlog_cache_size 32768 binlog_direct_non_transactional_updates OFF binlog_format STATEMENT bulk_insert_buffer_size 8388608 character_set_client utf8 character_set_connection utf8 character_set_database latin1 character_set_filesystem binary character_set_results utf8 character_set_server latin1 character_set_system utf8 character_sets_dir /usr/share/mysql/charsets/ collation_connection utf8_general_ci collation_database latin1_swedish_ci collation_server latin1_swedish_ci completion_type 0 concurrent_insert 1 connect_timeout 10 datadir /var/lib/mysql/ date_format %Y-%m-%d datetime_format %Y-%m-%d %H:%i:%s default_week_format 0 delay_key_write ON delayed_insert_limit 100 delayed_insert_timeout 300 delayed_queue_size 1000 div_precision_increment 4 engine_condition_pushdown ON error_count 0 event_scheduler OFF expire_logs_days 0 flush OFF flush_time 0 foreign_key_checks ON ft_boolean_syntax + -><()~*:""&| ft_max_word_len 84 ft_min_word_len 4 ft_query_expansion_limit 20 ft_stopword_file (built-in) general_log OFF general_log_file /var/run/mysqld/mysqld.log group_concat_max_len 1024 have_community_features YES have_compress YES have_crypt YES have_csv YES have_dynamic_loading YES have_geometry YES have_innodb YES have_ndbcluster NO have_openssl DISABLED have_partitioning YES have_query_cache YES have_rtree_keys YES have_ssl DISABLED have_symlink DISABLED hostname server1.site2.com identity 0 ignore_builtin_innodb OFF init_connect init_file init_slave innodb_adaptive_hash_index ON innodb_additional_mem_pool_size 1048576 innodb_autoextend_increment 8 innodb_autoinc_lock_mode 1 innodb_buffer_pool_size 8388608 innodb_checksums ON innodb_commit_concurrency 0 innodb_concurrency_tickets 500 innodb_data_file_path ibdata1:10M:autoextend innodb_data_home_dir innodb_doublewrite ON innodb_fast_shutdown 1 innodb_file_io_threads 4 innodb_file_per_table OFF innodb_flush_log_at_trx_commit 1 innodb_flush_method innodb_force_recovery 0 innodb_lock_wait_timeout 50 innodb_locks_unsafe_for_binlog OFF innodb_log_buffer_size 1048576 innodb_log_file_size 5242880 innodb_log_files_in_group 2 innodb_log_group_home_dir ./ innodb_max_dirty_pages_pct 90 innodb_max_purge_lag 0 innodb_mirrored_log_groups 1 innodb_open_files 300 innodb_rollback_on_timeout OFF innodb_stats_method nulls_equal innodb_stats_on_metadata ON innodb_support_xa ON innodb_sync_spin_loops 20 innodb_table_locks ON innodb_thread_concurrency 8 innodb_thread_sleep_delay 10000 innodb_use_legacy_cardinality_algorithm ON insert_id 0 interactive_timeout 28800 join_buffer_size 131072 keep_files_on_create OFF key_buffer_size 8384512 key_cache_age_threshold 300 key_cache_block_size 1024 key_cache_division_limit 100 language /usr/share/mysql/english/ large_files_support ON large_page_size 0 large_pages OFF last_insert_id 0 lc_time_names en_US license GPL local_infile ON locked_in_memory OFF log OFF log_bin OFF log_bin_trust_function_creators OFF log_bin_trust_routine_creators OFF log_error /var/log/mysqld.log log_output FILE log_queries_not_using_indexes OFF log_slave_updates OFF log_slow_queries OFF log_warnings 1 long_query_time 10.000000 low_priority_updates OFF lower_case_file_system OFF lower_case_table_names 0 max_allowed_packet 1048576 max_binlog_cache_size 18446744073709547520 max_binlog_size 1073741824 max_connect_errors 10 max_connections 151 max_delayed_threads 20 max_error_count 64 max_heap_table_size 16777216 max_insert_delayed_threads 20 max_join_size 18446744073709551615 max_length_for_sort_data 1024 max_long_data_size 1048576 max_prepared_stmt_count 16382 max_relay_log_size 0 max_seeks_for_key 18446744073709551615 max_sort_length 1024 max_sp_recursion_depth 0 max_tmp_tables 32 max_user_connections 0 max_write_lock_count 18446744073709551615 min_examined_row_limit 0 multi_range_count 256 myisam_data_pointer_size 6 myisam_max_sort_file_size 9223372036853727232 myisam_mmap_size 18446744073709551615 myisam_recover_options OFF myisam_repair_threads 1 myisam_sort_buffer_size 8388608 myisam_stats_method nulls_unequal myisam_use_mmap OFF net_buffer_length 16384 net_read_timeout 30 net_retry_count 10 net_write_timeout 60 new OFF old OFF old_alter_table OFF old_passwords OFF open_files_limit 1024 optimizer_prune_level 1 optimizer_search_depth 62 optimizer_switch index_merge=on,index_merge_union=on,index_merge_sort_union=on,index_merge_intersection=on pid_file /var/run/mysqld/mysqld.pid plugin_dir /usr/lib64/mysql/plugin port 3306 preload_buffer_size 32768 profiling OFF profiling_history_size 15 protocol_version 10 pseudo_thread_id 3 query_alloc_block_size 8192 query_cache_limit 1048576 query_cache_min_res_unit 4096 query_cache_size 0 query_cache_type ON query_cache_wlock_invalidate OFF query_prealloc_size 8192 rand_seed1 rand_seed2 range_alloc_block_size 4096 read_buffer_size 131072 read_only OFF read_rnd_buffer_size 262144 relay_log relay_log_index relay_log_info_file relay-log.info relay_log_purge ON relay_log_space_limit 0 report_host report_password report_port 3306 report_user rpl_recovery_rank 0 secure_auth OFF secure_file_priv server_id 0 skip_external_locking ON skip_name_resolve OFF skip_networking OFF skip_show_database OFF slave_compressed_protocol OFF slave_exec_mode STRICT slave_load_tmpdir /tmp slave_max_allowed_packet 1073741824 slave_net_timeout 3600 slave_skip_errors OFF slave_transaction_retries 10 slow_launch_time 2 slow_query_log OFF slow_query_log_file /var/run/mysqld/mysqld-slow.log socket /var/lib/mysql/mysql.sock sort_buffer_size 2097144 sql_auto_is_null ON sql_big_selects ON sql_big_tables OFF sql_buffer_result OFF sql_log_bin ON sql_log_off OFF sql_log_update ON sql_low_priority_updates OFF sql_max_join_size 18446744073709551615 sql_mode sql_notes ON sql_quote_show_create ON sql_safe_updates OFF sql_select_limit 18446744073709551615 sql_slave_skip_counter sql_warnings OFF ssl_ca ssl_capath ssl_cert ssl_cipher ssl_key storage_engine MyISAM sync_binlog 0 sync_frm ON system_time_zone PDT table_definition_cache 256 table_lock_wait_timeout 50 table_open_cache 64 table_type MyISAM thread_cache_size 0 thread_handling one-thread-per-connection thread_stack 262144 time_format %H:%i:%s time_zone SYSTEM timed_mutexes OFF timestamp 1372254399 tmp_table_size 16777216 tmpdir /tmp transaction_alloc_block_size 8192 transaction_prealloc_size 4096 tx_isolation REPEATABLE-READ unique_checks ON updatable_views_with_limit YES version 5.1.69 version_comment Source distribution version_compile_machine x86_64 version_compile_os redhat-linux-gnu wait_timeout 28800 warning_count 0 VPS Sysbench Info [root@vps ~]# cat sysbench.txt sysbench 0.4.12: multi-threaded system evaluation benchmark Running the test with following options: Number of threads: 8 Doing OLTP test. Running mixed OLTP test Doing read-only test Using Special distribution (12 iterations, 1 pct of values are returned in 75 pct cases) Using "BEGIN" for starting transactions Using auto_inc on the id column Threads started! Time limit exceeded, exiting... (last message repeated 7 times) Done. OLTP test statistics: queries performed: read: 1449966 write: 0 other: 207138 total: 1657104 transactions: 103569 (1726.01 per sec.) deadlocks: 0 (0.00 per sec.) read/write requests: 1449966 (24164.08 per sec.) other operations: 207138 (3452.01 per sec.) Test execution summary: total time: 60.0050s total number of events: 103569 total time taken by event execution: 479.1544 per-request statistics: min: 1.98ms avg: 4.63ms max: 330.73ms approx. 95 percentile: 8.26ms Threads fairness: events (avg/stddev): 12946.1250/381.09 execution time (avg/stddev): 59.8943/0.00 [root@vps ~]# Laptop Sysbench Info [root@server1 ~]# cat sysbench.txt sysbench 0.4.12: multi-threaded system evaluation benchmark Running the test with following options: Number of threads: 8 Doing OLTP test. Running mixed OLTP test Doing read-only test Using Special distribution (12 iterations, 1 pct of values are returned in 75 pct cases) Using "BEGIN" for starting transactions Using auto_inc on the id column Threads started! Time limit exceeded, exiting... (last message repeated 7 times) Done. OLTP test statistics: queries performed: read: 634718 write: 0 other: 90674 total: 725392 transactions: 45337 (755.56 per sec.) deadlocks: 0 (0.00 per sec.) read/write requests: 634718 (10577.78 per sec.) other operations: 90674 (1511.11 per sec.) Test execution summary: total time: 60.0048s total number of events: 45337 total time taken by event execution: 479.4912 per-request statistics: min: 2.04ms avg: 10.58ms max: 85.56ms approx. 95 percentile: 19.70ms Threads fairness: events (avg/stddev): 5667.1250/42.18 execution time (avg/stddev): 59.9364/0.00 [root@server1 ~]# VPS File Info [root@vps ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/simfs simfs 20971520 16187440 4784080 78% / none tmpfs 6224432 4 6224428 1% /dev none tmpfs 6224432 0 6224432 0% /dev/shm [root@vps ~]# Laptop File Info [root@server1 ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/mapper/vg_server1-lv_root ext4 72383800 4243964 64462860 7% / tmpfs tmpfs 956352 0 956352 0% /dev/shm /dev/sdb1 ext4 495844 60948 409296 13% /boot [root@server1 ~]# VPS CPU Info Removed to stay under the 30000 character limit required by ServerFault Laptop CPU Info [root@server1 ~]# cat /proc/cpuinfo processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 0 cpu cores : 2 apicid : 0 initial apicid : 0 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: processor : 1 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 1 cpu cores : 2 apicid : 1 initial apicid : 1 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: [root@server1 ~]# EDIT New Info requested by shakalandy [root@localhost ~]# cat /proc/meminfo MemTotal: 2044804 kB MemFree: 761464 kB Buffers: 68868 kB Cached: 369708 kB SwapCached: 0 kB Active: 881080 kB Inactive: 246016 kB Active(anon): 688312 kB Inactive(anon): 4416 kB Active(file): 192768 kB Inactive(file): 241600 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 4095992 kB SwapFree: 4095992 kB Dirty: 0 kB Writeback: 0 kB AnonPages: 688428 kB Mapped: 65156 kB Shmem: 4216 kB Slab: 92428 kB SReclaimable: 31260 kB SUnreclaim: 61168 kB KernelStack: 2392 kB PageTables: 28356 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 5118392 kB Committed_AS: 1530212 kB VmallocTotal: 34359738367 kB VmallocUsed: 343604 kB VmallocChunk: 34359372920 kB HardwareCorrupted: 0 kB AnonHugePages: 520192 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 8556 kB DirectMap2M: 2078720 kB [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501360 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3036 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14449 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501356 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3048 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14470 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# vmstat 1 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 0 0 742172 76376 371064 0 0 6 6 78 202 2 1 97 1 0 0 0 0 742164 76380 371060 0 0 0 16 191 467 2 1 93 5 0 0 0 0 742164 76380 371064 0 0 0 0 148 388 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 418 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 145 380 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 166 429 2 1 97 0 0 1 0 0 742164 76380 371064 0 0 0 0 148 373 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 149 382 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 168 408 2 0 97 0 0 0 0 0 742164 76380 371064 0 0 0 0 165 394 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 354 2 1 98 0 0 0 0 0 742164 76388 371060 0 0 0 16 180 447 2 0 91 6 0 0 0 0 742164 76388 371064 0 0 0 0 143 344 2 1 98 0 0 0 1 0 742784 76416 370044 0 0 28 580 360 678 3 1 74 23 0 1 0 0 744768 76496 367772 0 0 40 1036 437 865 3 1 53 43 0 0 1 0 747248 76596 365412 0 0 48 1224 561 923 3 2 53 43 0 0 1 0 749232 76696 363092 0 0 32 1132 512 883 3 2 52 44 0 0 1 0 751340 76772 361020 0 0 32 1008 472 872 2 1 52 45 0 0 1 0 753448 76840 358540 0 0 36 1088 512 860 2 1 51 46 0 0 1 0 755060 76936 357636 0 0 28 1012 481 922 2 2 52 45 0 0 1 0 755060 77064 357988 0 0 12 896 444 902 2 1 53 45 0 0 1 0 754688 77148 358448 0 0 16 1096 506 1007 1 1 56 42 0 0 2 0 754192 77268 358932 0 0 12 1060 481 957 1 2 53 44 0 0 1 0 753696 77380 359392 0 0 12 1052 512 1025 2 1 55 42 0 0 1 0 751028 77480 359828 0 0 8 984 423 909 2 2 52 45 0 0 1 0 750524 77620 360200 0 0 8 788 367 869 1 2 54 44 0 0 1 0 749904 77700 360664 0 0 8 928 439 924 2 2 55 43 0 0 1 0 749408 77796 361084 0 0 12 976 468 967 1 1 56 43 0 0 1 0 748788 77896 361464 0 0 12 992 453 944 1 2 54 43 0 1 1 0 748416 77992 361996 0 0 12 784 392 868 2 1 52 46 0 0 1 0 747920 78092 362336 0 0 4 896 382 874 1 1 52 46 0 0 1 0 745252 78172 362780 0 0 12 1040 444 923 1 1 56 42 0 0 1 0 744764 78288 363220 0 0 8 1024 448 934 2 1 55 43 0 0 1 0 744144 78408 363668 0 0 8 1000 461 982 2 1 53 44 0 0 1 0 743648 78488 364148 0 0 8 872 443 888 2 1 54 43 0 0 1 0 743152 78548 364468 0 0 16 1020 511 995 2 1 55 43 0 0 1 0 742656 78632 365024 0 0 12 928 431 913 1 2 53 44 0 0 1 0 742160 78728 365468 0 0 12 996 470 955 2 2 54 44 0 1 1 0 739492 78840 365896 0 0 8 988 447 939 1 2 52 46 0 0 1 0 738872 78996 366352 0 0 12 972 442 928 1 1 55 44 0 1 1 0 738244 79148 366812 0 0 8 948 549 1126 2 2 54 43 0 0 1 0 737624 79312 367188 0 0 12 996 456 953 2 2 54 43 0 0 1 0 736880 79456 367660 0 0 12 960 444 918 1 1 53 46 0 0 1 0 736260 79584 368124 0 0 8 884 414 921 1 1 54 44 0 0 1 0 735648 79716 368488 0 0 12 976 450 955 2 1 56 41 0 0 1 0 733104 79840 368988 0 0 12 932 453 918 1 2 55 43 0 0 1 0 732608 79996 369356 0 0 16 916 444 889 1 2 54 43 0 1 1 0 731476 80128 369800 0 0 16 852 514 978 2 2 54 43 0 0 1 0 731244 80252 370200 0 0 8 904 398 870 2 1 55 43 0 1 1 0 730624 80384 370612 0 0 12 1032 447 977 1 2 57 41 0 0 1 0 730004 80524 371096 0 0 12 984 469 941 2 2 52 45 0 0 1 0 729508 80636 371544 0 0 12 928 438 922 2 1 52 46 0 0 1 0 728888 80756 371948 0 0 16 972 439 943 2 1 55 43 0 0 1 0 726468 80900 372272 0 0 8 960 545 1024 2 1 54 43 0 1 1 0 726344 81024 372272 0 0 8 464 490 1057 1 2 53 44 0 0 1 0 726096 81148 372276 0 0 4 328 441 1063 2 1 53 45 0 1 1 0 726096 81256 372292 0 0 0 296 387 975 1 1 53 45 0 0 1 0 725848 81380 372284 0 0 4 332 425 1034 2 1 54 44 0 1 1 0 725848 81496 372300 0 0 4 308 386 992 2 1 54 43 0 0 1 0 725600 81616 372296 0 0 4 328 404 1060 1 1 54 44 0 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 1 0 725600 81732 372296 0 0 4 328 439 1011 1 1 53 44 0 0 1 0 725476 81848 372308 0 0 0 316 441 1023 2 2 52 46 0 1 1 0 725352 81972 372300 0 0 4 344 451 1021 1 1 55 43 0 2 1 0 725228 82088 372320 0 0 0 328 427 1058 1 1 54 44 0 1 1 0 724980 82220 372300 0 0 4 336 419 999 2 1 54 44 0 1 1 0 724980 82328 372320 0 0 4 320 430 1019 1 1 54 44 0 1 1 0 724732 82436 372328 0 0 0 388 363 942 2 1 54 44 0 1 1 0 724608 82560 372312 0 0 4 308 419 993 1 2 54 44 0 1 0 0 724360 82684 372320 0 0 0 304 421 1028 2 1 55 42 0 1 0 0 724360 82684 372388 0 0 0 0 158 416 2 1 98 0 0 1 1 0 724236 82720 372360 0 0 0 6464 243 855 3 2 84 12 0 1 0 0 724112 82748 372360 0 0 0 5356 266 895 3 1 84 12 0 2 1 0 724112 82764 372380 0 0 0 3052 221 511 2 2 93 4 0 1 0 0 724112 82796 372372 0 0 0 4548 325 1067 2 2 81 16 0 1 0 0 724112 82816 372368 0 0 0 3240 259 829 3 1 90 6 0 1 0 0 724112 82836 372380 0 0 0 3260 309 822 3 2 88 8 0 1 1 0 724112 82876 372364 0 0 0 4680 326 978 3 1 77 19 0 1 0 0 724112 82884 372380 0 0 0 512 207 508 2 1 95 2 0 1 0 0 724112 82884 372388 0 0 0 0 138 361 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 158 397 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 146 395 2 1 98 0 0 2 0 0 724112 82884 372388 0 0 0 0 160 395 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 163 382 1 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 176 422 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 134 351 2 1 98 0 0 0 0 0 724112 82884 372388 0 0 0 0 190 429 2 1 97 0 0 0 0 0 724104 82884 372392 0 0 0 0 139 358 2 1 98 0 0 0 0 0 724848 82884 372392 0 0 0 4 211 432 2 1 97 0 0 1 0 0 724980 82884 372392 0 0 0 0 166 370 2 1 98 0 0 0 0 0 724980 82884 372392 0 0 0 0 164 397 2 1 98 0 0 ^C [root@localhost ~]#

  Read the article

• MySQL is running VERY slow on CentOS 6x (not 5x)

  - by user1032531

  I have two servers: a VPS and a laptop. I recently re-built both of them, and MySQL is running about 20 times slower on the laptop. Both servers used to run CentOS 5.8 and I think MySQL 5.1, and the laptop used to do great so I do not think it is the hardware. For the VPS, my provider installed CentOS 6.4, and then I installed MySQL 5.1.69 using yum with the CentOS repo. For the laptop, I installed CentOS 6.4 basic server and then installed MySQL 5.1.69 using yum with the CentOS repo. my.cnf for both servers are identical, and I have shown below. For both servers, I've also included below the output from SHOW VARIABLES; as well as output from sysbench, file system information, and cpu information. I have tried adding skip-name-resolve, but it didn't help. The matrix below shows the SHOW VARIABLES output from both servers which is different. Again, MySQL was installed the same way, so I do not know why it is different, but it is and I think this might be why the laptop is executing MySQL so slowly. Why is the laptop running MySQL slowly, and how do I fix it? Differences between SHOW VARIABLES on both servers +---------------------------+-----------------------+-------------------------+ | Variable | Value-VPS | Value-Laptop | +---------------------------+-----------------------+-------------------------+ | hostname | vps.site1.com | laptop.site2.com | | max_binlog_cache_size | 4294963200 | 18446744073709500000 | | max_seeks_for_key | 4294967295 | 18446744073709500000 | | max_write_lock_count | 4294967295 | 18446744073709500000 | | myisam_max_sort_file_size | 2146435072 | 9223372036853720000 | | myisam_mmap_size | 4294967295 | 18446744073709500000 | | plugin_dir | /usr/lib/mysql/plugin | /usr/lib64/mysql/plugin | | pseudo_thread_id | 7568 | 2 | | system_time_zone | EST | PDT | | thread_stack | 196608 | 262144 | | timestamp | 1372252112 | 1372252046 | | version_compile_machine | i386 | x86_64 | +---------------------------+-----------------------+-------------------------+ my.cnf for both servers [root@server1 ~]# cat /etc/my.cnf [mysqld] datadir=/var/lib/mysql socket=/var/lib/mysql/mysql.sock user=mysql # Disabling symbolic-links is recommended to prevent assorted security risks symbolic-links=0 [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid innodb_strict_mode=on sql_mode=TRADITIONAL # sql_mode=STRICT_TRANS_TABLES,NO_ZERO_DATE,NO_ZERO_IN_DATE character-set-server=utf8 collation-server=utf8_general_ci log=/var/log/mysqld_all.log [root@server1 ~]# VPS SHOW VARIABLES Info Same as Laptop shown below but changes per above matrix (removed to allow me to be under the 30000 characters as required by ServerFault) Laptop SHOW VARIABLES Info auto_increment_increment 1 auto_increment_offset 1 autocommit ON automatic_sp_privileges ON back_log 50 basedir /usr/ big_tables OFF binlog_cache_size 32768 binlog_direct_non_transactional_updates OFF binlog_format STATEMENT bulk_insert_buffer_size 8388608 character_set_client utf8 character_set_connection utf8 character_set_database latin1 character_set_filesystem binary character_set_results utf8 character_set_server latin1 character_set_system utf8 character_sets_dir /usr/share/mysql/charsets/ collation_connection utf8_general_ci collation_database latin1_swedish_ci collation_server latin1_swedish_ci completion_type 0 concurrent_insert 1 connect_timeout 10 datadir /var/lib/mysql/ date_format %Y-%m-%d datetime_format %Y-%m-%d %H:%i:%s default_week_format 0 delay_key_write ON delayed_insert_limit 100 delayed_insert_timeout 300 delayed_queue_size 1000 div_precision_increment 4 engine_condition_pushdown ON error_count 0 event_scheduler OFF expire_logs_days 0 flush OFF flush_time 0 foreign_key_checks ON ft_boolean_syntax + -><()~*:""&| ft_max_word_len 84 ft_min_word_len 4 ft_query_expansion_limit 20 ft_stopword_file (built-in) general_log OFF general_log_file /var/run/mysqld/mysqld.log group_concat_max_len 1024 have_community_features YES have_compress YES have_crypt YES have_csv YES have_dynamic_loading YES have_geometry YES have_innodb YES have_ndbcluster NO have_openssl DISABLED have_partitioning YES have_query_cache YES have_rtree_keys YES have_ssl DISABLED have_symlink DISABLED hostname server1.site2.com identity 0 ignore_builtin_innodb OFF init_connect init_file init_slave innodb_adaptive_hash_index ON innodb_additional_mem_pool_size 1048576 innodb_autoextend_increment 8 innodb_autoinc_lock_mode 1 innodb_buffer_pool_size 8388608 innodb_checksums ON innodb_commit_concurrency 0 innodb_concurrency_tickets 500 innodb_data_file_path ibdata1:10M:autoextend innodb_data_home_dir innodb_doublewrite ON innodb_fast_shutdown 1 innodb_file_io_threads 4 innodb_file_per_table OFF innodb_flush_log_at_trx_commit 1 innodb_flush_method innodb_force_recovery 0 innodb_lock_wait_timeout 50 innodb_locks_unsafe_for_binlog OFF innodb_log_buffer_size 1048576 innodb_log_file_size 5242880 innodb_log_files_in_group 2 innodb_log_group_home_dir ./ innodb_max_dirty_pages_pct 90 innodb_max_purge_lag 0 innodb_mirrored_log_groups 1 innodb_open_files 300 innodb_rollback_on_timeout OFF innodb_stats_method nulls_equal innodb_stats_on_metadata ON innodb_support_xa ON innodb_sync_spin_loops 20 innodb_table_locks ON innodb_thread_concurrency 8 innodb_thread_sleep_delay 10000 innodb_use_legacy_cardinality_algorithm ON insert_id 0 interactive_timeout 28800 join_buffer_size 131072 keep_files_on_create OFF key_buffer_size 8384512 key_cache_age_threshold 300 key_cache_block_size 1024 key_cache_division_limit 100 language /usr/share/mysql/english/ large_files_support ON large_page_size 0 large_pages OFF last_insert_id 0 lc_time_names en_US license GPL local_infile ON locked_in_memory OFF log OFF log_bin OFF log_bin_trust_function_creators OFF log_bin_trust_routine_creators OFF log_error /var/log/mysqld.log log_output FILE log_queries_not_using_indexes OFF log_slave_updates OFF log_slow_queries OFF log_warnings 1 long_query_time 10.000000 low_priority_updates OFF lower_case_file_system OFF lower_case_table_names 0 max_allowed_packet 1048576 max_binlog_cache_size 18446744073709547520 max_binlog_size 1073741824 max_connect_errors 10 max_connections 151 max_delayed_threads 20 max_error_count 64 max_heap_table_size 16777216 max_insert_delayed_threads 20 max_join_size 18446744073709551615 max_length_for_sort_data 1024 max_long_data_size 1048576 max_prepared_stmt_count 16382 max_relay_log_size 0 max_seeks_for_key 18446744073709551615 max_sort_length 1024 max_sp_recursion_depth 0 max_tmp_tables 32 max_user_connections 0 max_write_lock_count 18446744073709551615 min_examined_row_limit 0 multi_range_count 256 myisam_data_pointer_size 6 myisam_max_sort_file_size 9223372036853727232 myisam_mmap_size 18446744073709551615 myisam_recover_options OFF myisam_repair_threads 1 myisam_sort_buffer_size 8388608 myisam_stats_method nulls_unequal myisam_use_mmap OFF net_buffer_length 16384 net_read_timeout 30 net_retry_count 10 net_write_timeout 60 new OFF old OFF old_alter_table OFF old_passwords OFF open_files_limit 1024 optimizer_prune_level 1 optimizer_search_depth 62 optimizer_switch index_merge=on,index_merge_union=on,index_merge_sort_union=on,index_merge_intersection=on pid_file /var/run/mysqld/mysqld.pid plugin_dir /usr/lib64/mysql/plugin port 3306 preload_buffer_size 32768 profiling OFF profiling_history_size 15 protocol_version 10 pseudo_thread_id 3 query_alloc_block_size 8192 query_cache_limit 1048576 query_cache_min_res_unit 4096 query_cache_size 0 query_cache_type ON query_cache_wlock_invalidate OFF query_prealloc_size 8192 rand_seed1 rand_seed2 range_alloc_block_size 4096 read_buffer_size 131072 read_only OFF read_rnd_buffer_size 262144 relay_log relay_log_index relay_log_info_file relay-log.info relay_log_purge ON relay_log_space_limit 0 report_host report_password report_port 3306 report_user rpl_recovery_rank 0 secure_auth OFF secure_file_priv server_id 0 skip_external_locking ON skip_name_resolve OFF skip_networking OFF skip_show_database OFF slave_compressed_protocol OFF slave_exec_mode STRICT slave_load_tmpdir /tmp slave_max_allowed_packet 1073741824 slave_net_timeout 3600 slave_skip_errors OFF slave_transaction_retries 10 slow_launch_time 2 slow_query_log OFF slow_query_log_file /var/run/mysqld/mysqld-slow.log socket /var/lib/mysql/mysql.sock sort_buffer_size 2097144 sql_auto_is_null ON sql_big_selects ON sql_big_tables OFF sql_buffer_result OFF sql_log_bin ON sql_log_off OFF sql_log_update ON sql_low_priority_updates OFF sql_max_join_size 18446744073709551615 sql_mode sql_notes ON sql_quote_show_create ON sql_safe_updates OFF sql_select_limit 18446744073709551615 sql_slave_skip_counter sql_warnings OFF ssl_ca ssl_capath ssl_cert ssl_cipher ssl_key storage_engine MyISAM sync_binlog 0 sync_frm ON system_time_zone PDT table_definition_cache 256 table_lock_wait_timeout 50 table_open_cache 64 table_type MyISAM thread_cache_size 0 thread_handling one-thread-per-connection thread_stack 262144 time_format %H:%i:%s time_zone SYSTEM timed_mutexes OFF timestamp 1372254399 tmp_table_size 16777216 tmpdir /tmp transaction_alloc_block_size 8192 transaction_prealloc_size 4096 tx_isolation REPEATABLE-READ unique_checks ON updatable_views_with_limit YES version 5.1.69 version_comment Source distribution version_compile_machine x86_64 version_compile_os redhat-linux-gnu wait_timeout 28800 warning_count 0 VPS Sysbench Info Deleted to stay under 30000 characters. Laptop Sysbench Info [root@server1 ~]# cat sysbench.txt sysbench 0.4.12: multi-threaded system evaluation benchmark Running the test with following options: Number of threads: 8 Doing OLTP test. Running mixed OLTP test Doing read-only test Using Special distribution (12 iterations, 1 pct of values are returned in 75 pct cases) Using "BEGIN" for starting transactions Using auto_inc on the id column Threads started! Time limit exceeded, exiting... (last message repeated 7 times) Done. OLTP test statistics: queries performed: read: 634718 write: 0 other: 90674 total: 725392 transactions: 45337 (755.56 per sec.) deadlocks: 0 (0.00 per sec.) read/write requests: 634718 (10577.78 per sec.) other operations: 90674 (1511.11 per sec.) Test execution summary: total time: 60.0048s total number of events: 45337 total time taken by event execution: 479.4912 per-request statistics: min: 2.04ms avg: 10.58ms max: 85.56ms approx. 95 percentile: 19.70ms Threads fairness: events (avg/stddev): 5667.1250/42.18 execution time (avg/stddev): 59.9364/0.00 [root@server1 ~]# VPS File Info [root@vps ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/simfs simfs 20971520 16187440 4784080 78% / none tmpfs 6224432 4 6224428 1% /dev none tmpfs 6224432 0 6224432 0% /dev/shm [root@vps ~]# Laptop File Info [root@server1 ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/mapper/vg_server1-lv_root ext4 72383800 4243964 64462860 7% / tmpfs tmpfs 956352 0 956352 0% /dev/shm /dev/sdb1 ext4 495844 60948 409296 13% /boot [root@server1 ~]# VPS CPU Info Removed to stay under the 30000 character limit required by ServerFault Laptop CPU Info [root@server1 ~]# cat /proc/cpuinfo processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 0 cpu cores : 2 apicid : 0 initial apicid : 0 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: processor : 1 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 1 cpu cores : 2 apicid : 1 initial apicid : 1 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: [root@server1 ~]# EDIT New Info requested by shakalandy [root@localhost ~]# cat /proc/meminfo MemTotal: 2044804 kB MemFree: 761464 kB Buffers: 68868 kB Cached: 369708 kB SwapCached: 0 kB Active: 881080 kB Inactive: 246016 kB Active(anon): 688312 kB Inactive(anon): 4416 kB Active(file): 192768 kB Inactive(file): 241600 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 4095992 kB SwapFree: 4095992 kB Dirty: 0 kB Writeback: 0 kB AnonPages: 688428 kB Mapped: 65156 kB Shmem: 4216 kB Slab: 92428 kB SReclaimable: 31260 kB SUnreclaim: 61168 kB KernelStack: 2392 kB PageTables: 28356 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 5118392 kB Committed_AS: 1530212 kB VmallocTotal: 34359738367 kB VmallocUsed: 343604 kB VmallocChunk: 34359372920 kB HardwareCorrupted: 0 kB AnonHugePages: 520192 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 8556 kB DirectMap2M: 2078720 kB [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501360 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3036 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14449 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501356 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3048 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14470 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# vmstat 1 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 0 0 742172 76376 371064 0 0 6 6 78 202 2 1 97 1 0 0 0 0 742164 76380 371060 0 0 0 16 191 467 2 1 93 5 0 0 0 0 742164 76380 371064 0 0 0 0 148 388 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 418 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 145 380 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 166 429 2 1 97 0 0 1 0 0 742164 76380 371064 0 0 0 0 148 373 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 149 382 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 168 408 2 0 97 0 0 0 0 0 742164 76380 371064 0 0 0 0 165 394 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 354 2 1 98 0 0 0 0 0 742164 76388 371060 0 0 0 16 180 447 2 0 91 6 0 0 0 0 742164 76388 371064 0 0 0 0 143 344 2 1 98 0 0 0 1 0 742784 76416 370044 0 0 28 580 360 678 3 1 74 23 0 1 0 0 744768 76496 367772 0 0 40 1036 437 865 3 1 53 43 0 0 1 0 747248 76596 365412 0 0 48 1224 561 923 3 2 53 43 0 0 1 0 749232 76696 363092 0 0 32 1132 512 883 3 2 52 44 0 0 1 0 751340 76772 361020 0 0 32 1008 472 872 2 1 52 45 0 0 1 0 753448 76840 358540 0 0 36 1088 512 860 2 1 51 46 0 0 1 0 755060 76936 357636 0 0 28 1012 481 922 2 2 52 45 0 0 1 0 755060 77064 357988 0 0 12 896 444 902 2 1 53 45 0 0 1 0 754688 77148 358448 0 0 16 1096 506 1007 1 1 56 42 0 0 2 0 754192 77268 358932 0 0 12 1060 481 957 1 2 53 44 0 0 1 0 753696 77380 359392 0 0 12 1052 512 1025 2 1 55 42 0 0 1 0 751028 77480 359828 0 0 8 984 423 909 2 2 52 45 0 0 1 0 750524 77620 360200 0 0 8 788 367 869 1 2 54 44 0 0 1 0 749904 77700 360664 0 0 8 928 439 924 2 2 55 43 0 0 1 0 749408 77796 361084 0 0 12 976 468 967 1 1 56 43 0 0 1 0 748788 77896 361464 0 0 12 992 453 944 1 2 54 43 0 1 1 0 748416 77992 361996 0 0 12 784 392 868 2 1 52 46 0 0 1 0 747920 78092 362336 0 0 4 896 382 874 1 1 52 46 0 0 1 0 745252 78172 362780 0 0 12 1040 444 923 1 1 56 42 0 0 1 0 744764 78288 363220 0 0 8 1024 448 934 2 1 55 43 0 0 1 0 744144 78408 363668 0 0 8 1000 461 982 2 1 53 44 0 0 1 0 743648 78488 364148 0 0 8 872 443 888 2 1 54 43 0 0 1 0 743152 78548 364468 0 0 16 1020 511 995 2 1 55 43 0 0 1 0 742656 78632 365024 0 0 12 928 431 913 1 2 53 44 0 0 1 0 742160 78728 365468 0 0 12 996 470 955 2 2 54 44 0 1 1 0 739492 78840 365896 0 0 8 988 447 939 1 2 52 46 0 0 1 0 738872 78996 366352 0 0 12 972 442 928 1 1 55 44 0 1 1 0 738244 79148 366812 0 0 8 948 549 1126 2 2 54 43 0 0 1 0 737624 79312 367188 0 0 12 996 456 953 2 2 54 43 0 0 1 0 736880 79456 367660 0 0 12 960 444 918 1 1 53 46 0 0 1 0 736260 79584 368124 0 0 8 884 414 921 1 1 54 44 0 0 1 0 735648 79716 368488 0 0 12 976 450 955 2 1 56 41 0 0 1 0 733104 79840 368988 0 0 12 932 453 918 1 2 55 43 0 0 1 0 732608 79996 369356 0 0 16 916 444 889 1 2 54 43 0 1 1 0 731476 80128 369800 0 0 16 852 514 978 2 2 54 43 0 0 1 0 731244 80252 370200 0 0 8 904 398 870 2 1 55 43 0 1 1 0 730624 80384 370612 0 0 12 1032 447 977 1 2 57 41 0 0 1 0 730004 80524 371096 0 0 12 984 469 941 2 2 52 45 0 0 1 0 729508 80636 371544 0 0 12 928 438 922 2 1 52 46 0 0 1 0 728888 80756 371948 0 0 16 972 439 943 2 1 55 43 0 0 1 0 726468 80900 372272 0 0 8 960 545 1024 2 1 54 43 0 1 1 0 726344 81024 372272 0 0 8 464 490 1057 1 2 53 44 0 0 1 0 726096 81148 372276 0 0 4 328 441 1063 2 1 53 45 0 1 1 0 726096 81256 372292 0 0 0 296 387 975 1 1 53 45 0 0 1 0 725848 81380 372284 0 0 4 332 425 1034 2 1 54 44 0 1 1 0 725848 81496 372300 0 0 4 308 386 992 2 1 54 43 0 0 1 0 725600 81616 372296 0 0 4 328 404 1060 1 1 54 44 0 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 1 0 725600 81732 372296 0 0 4 328 439 1011 1 1 53 44 0 0 1 0 725476 81848 372308 0 0 0 316 441 1023 2 2 52 46 0 1 1 0 725352 81972 372300 0 0 4 344 451 1021 1 1 55 43 0 2 1 0 725228 82088 372320 0 0 0 328 427 1058 1 1 54 44 0 1 1 0 724980 82220 372300 0 0 4 336 419 999 2 1 54 44 0 1 1 0 724980 82328 372320 0 0 4 320 430 1019 1 1 54 44 0 1 1 0 724732 82436 372328 0 0 0 388 363 942 2 1 54 44 0 1 1 0 724608 82560 372312 0 0 4 308 419 993 1 2 54 44 0 1 0 0 724360 82684 372320 0 0 0 304 421 1028 2 1 55 42 0 1 0 0 724360 82684 372388 0 0 0 0 158 416 2 1 98 0 0 1 1 0 724236 82720 372360 0 0 0 6464 243 855 3 2 84 12 0 1 0 0 724112 82748 372360 0 0 0 5356 266 895 3 1 84 12 0 2 1 0 724112 82764 372380 0 0 0 3052 221 511 2 2 93 4 0 1 0 0 724112 82796 372372 0 0 0 4548 325 1067 2 2 81 16 0 1 0 0 724112 82816 372368 0 0 0 3240 259 829 3 1 90 6 0 1 0 0 724112 82836 372380 0 0 0 3260 309 822 3 2 88 8 0 1 1 0 724112 82876 372364 0 0 0 4680 326 978 3 1 77 19 0 1 0 0 724112 82884 372380 0 0 0 512 207 508 2 1 95 2 0 1 0 0 724112 82884 372388 0 0 0 0 138 361 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 158 397 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 146 395 2 1 98 0 0 2 0 0 724112 82884 372388 0 0 0 0 160 395 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 163 382 1 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 176 422 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 134 351 2 1 98 0 0 0 0 0 724112 82884 372388 0 0 0 0 190 429 2 1 97 0 0 0 0 0 724104 82884 372392 0 0 0 0 139 358 2 1 98 0 0 0 0 0 724848 82884 372392 0 0 0 4 211 432 2 1 97 0 0 1 0 0 724980 82884 372392 0 0 0 0 166 370 2 1 98 0 0 0 0 0 724980 82884 372392 0 0 0 0 164 397 2 1 98 0 0 ^C [root@localhost ~]# Database size mysql> SELECT table_schema "Data Base Name", sum( data_length + index_length ) / 1024 / 1024 "Data Base Size in MB", sum( data_free )/ 1024 / 1024 "Free Space in MB" FROM information_schema.TABLES GROUP BY table_schema; +--------------------+----------------------+------------------+ | Data Base Name | Data Base Size in MB | Free Space in MB | +--------------------+----------------------+------------------+ | bidjunction | 4.68750000 | 0.00000000 | | information_schema | 0.00976563 | 0.00000000 | | mysql | 0.63899899 | 0.00105286 | +--------------------+----------------------+------------------+ 3 rows in set (0.01 sec) mysql> Before Query mysql> SHOW SESSION STATUS like '%Tmp%'; +-------------------------+-------+ | Variable_name | Value | +-------------------------+-------+ | Created_tmp_disk_tables | 0 | | Created_tmp_files | 6 | | Created_tmp_tables | 0 | +-------------------------+-------+ 3 rows in set (0.00 sec) mysql> After Query mysql> SHOW SESSION STATUS like '%Tmp%'; +-------------------------+-------+ | Variable_name | Value | +-------------------------+-------+ | Created_tmp_disk_tables | 0 | | Created_tmp_files | 6 | | Created_tmp_tables | 2 | +-------------------------+-------+ 3 rows in set (0.00 sec) mysql>

  Read the article

• SQL SERVER – Beginning SQL Server: One Step at a Time – SQL Server Magazine

  - by pinaldave

  I am glad to announce that along with SQLAuthority.com, I will be blogging on the prominent site of SQL Server Magazine. My very first blog post there is already live; read here: Beginning SQL Server: One Step at a Time. My association with SQL Server Magazine has been quite long, I have written nearly 7 to 8 SQL Server articles for the print magazine and it has been a great experience. I used to stay in the United States at that time. I moved back to India for good, and during this process, I had put everything on hold for a while. Just like many things, “temporary” things become “permanent” – coming back to SQLMag was on hold for long time. Well, this New Year, things have changed – once again, I am back with my online presence at SQLMag.com. Everybody is a beginner at every task or activity at some point of his/her life: spelling words for the first time; learning how to drive for the first time, etc. No one is perfect at the start of any task, but every human is different. As time passes, we all develop our interests and begin to study our subject of interest. Most of us dream to get a job in the area of our study – however things change as time passes. I recently read somewhere online (I could not find the link again while writing this one) that all the successful people in various areas have never studied in the area in which they are successful. After going through a formal learning process of what we love, we refuse to stop learning, and we finally stop changing career and focus areas. We move, we dare and we progress. IT field is similar to our life. New IT professionals come to this field every day. There are two types of beginners – a) those who are associated with IT field but not familiar with other technologies, and b) those who are absolutely new to the IT field. Learning a new technology is always exciting and overwhelming for enthusiasts. I am working with database (in particular) for SQL Server for more than 7 years but I am still overwhelmed with so many things to learn. I continue to learn and I do not think that I should ever stop doing so. Just like everybody, I want to be in the race and get ahead in learning the technology. For the same, I am always looking for good guidance. I always try to find a good article, blog or book chapter, which can teach me what I really want to learn at this stage in my career and can be immensely helpful. Quite often, I prefer to read the material where the author does not judge me or assume my understanding. I like to read new concepts like a child, who takes his/her first steps of learning without any prior knowledge. Keeping my personal philosophy and preference in mind, I will be blogging on SQL Server Magazine site. I will be blogging on the beginners stuff. I will be blogging for them, who really want to start and make a mark in this area. I will be blogging for all those who have an extreme passion for learning. I am happy that this is a good start for this year. One of my resolutions is to help every beginner. It is totally possible that in future they all will grow and find the same article quite ‘easy‘ – well when that happens, it indicates the success of the article and material! Well, I encourage everybody to read my SQL Server Magazine blog – I will be blogging there frequently on various topics. To begin, we will be talking about performance tuning, and I assure that I will not shy away from other multiple areas. Read my SQL Server Magazine Blog: Beginning SQL Server: One Step at a Time I think the title says it all. Do leave your comments and feedback to indicate your preference of subject and interest. I am going to continue writing on subject, and the aim is of course to help grow in this field. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority News, T SQL, Technology

  Read the article

• SQLAuthority News – Guest Post – Performance Counters Gathering using Powershell

  - by pinaldave

  Laerte Junior Laerte Junior has previously helped me personally to resolve the issue with Powershell installation on my computer. He did awesome job to help. He has send this another wonderful article regarding performance counter for readers of this blog. I really liked it and I expect all of you who are Powershell geeks, you will like the same as well. As a good DBA, you know that our social life is restricted to a few movies over the year and, when possible, a pizza in a restaurant next to your company’s place, of course. So what we have to do is to create methods through which we can facilitate our daily processes to go home early, and eventually have a nice time with our family (and not sleeping on the couch). As a consultant or fixed employee, one of our daily tasks is to monitor performance counters using Perfmom. To be honest, IDE is getting more complicated. To deal with this, I thought a solution using Powershell. Yes, with some lines of Powershell, you can configure which counters to use. And with one more line, you can already start collecting data. Let’s see one scenario: You are a consultant who has several clients and has just closed another project in troubleshooting an SQL Server environment. You are to use Perfmom to collect data from the server and you already have its XML configuration files made with the counters that you will be using- a file for memory bottleneck f, one for CPU, etc. With one Powershell command line for each XML file, you start collecting. The output of such a TXT file collection is set to up in an SQL Server. With two lines of command for each XML, you make the whole process of data collection. Creating an XML configuration File to Memory Counters: Get-PerfCounterCategory -CategoryName "Memory" | Get-PerfCounterInstance  | Get-PerfCounterCounters |Save-ConfigPerfCounter -PathConfigFile "c:\temp\ConfigfileMemory.xml" -newfile Creating an XML Configuration File to Buffer Manager, counters Page lookups/sec, Page reads/sec, Page writes/sec, Page life expectancy: Get-PerfCounterCategory -CategoryName "SQLServer:Buffer Manager" | Get-PerfCounterInstance | Get-PerfCounterCounters -CounterName "Page*" | Save-ConfigPerfCounter -PathConfigFile "c:\temp\BufferManager.xml" –NewFile Then you start the collection: Set-CollectPerfCounter -DateTimeStart "05/24/2010 08:00:00" -DateTimeEnd "05/24/2010 22:00:00" -Interval 10 -PathConfigFile c:\temp\ConfigfileMemory.xml -PathOutputFile c:\temp\ConfigfileMemory.txt To let the Buffer Manager collect, you need one more counters, including the Buffer cache hit ratio. Just add a new counter to BufferManager.xml, omitting the new file parameter Get-PerfCounterCategory -CategoryName "SQLServer:Buffer Manager" | Get-PerfCounterInstance | Get-PerfCounterCounters -CounterName "Buffer cache hit ratio" | Save-ConfigPerfCounter -PathConfigFile "c:\temp\BufferManager.xml" And start the collection: Set-CollectPerfCounter -DateTimeStart "05/24/2010 08:00:00" -DateTimeEnd "05/24/2010 22:00:00" -Interval 10 -PathConfigFile c:\temp\BufferManager.xml -PathOutputFile c:\temp\BufferManager.txt You do not know which counters are in the Category Buffer Manager? Simple! Get-PerfCounterCategory -CategoryName "SQLServer:Buffer Manager" | Get-PerfCounterInstance | Get-PerfCounterCounters Let’s see one output file as shown below. It is ready to bulk insert into the SQL Server. As you can see, Powershell makes this process incredibly easy and fast. Do you want to see more examples? Visit my blog at Shell Your Experience You can find more about Laerte Junior over here: www.laertejuniordba.spaces.live.com www.simple-talk.com/author/laerte-junior www.twitter.com/laertejuniordba SQL Server Powershell Extension Team: http://sqlpsx.codeplex.com/ Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: SQL, SQL Add-On, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology Tagged: Powershell

  Read the article

• Developer’s Life – Summary of Superhero Articles

  - by Pinal Dave

  Earlier this year, I wrote an article series where I talked about developer’s life and compared it with Superhero. I have got amazing response to this series and I have been receiving quite a lots of email suggesting that I should write more blog post about them. Currently I am not planning to write more blog post but I will soon continue another series. In this blog post, I have summarized the entire series. Let me know if you want me to write about any superhero. I will see what I can do about that hero. Developer’s Life – Every Developer is a Captain America Captain America was first created as a comic book character in the 1940’s as a way to boost morale during World War II.  Aimed at a children’s audience, his legacy faded away when the war ended.  However, he has recently has a major reboot to become a popular movie character that deals with modern issues. Developer’s Life – Every Developer is the Incredible Hulk The Incredible Hulk is possibly one of the scariest superheroes out there.  All superheroes are meant to be “out of this world” and awe-inspiring, but I think most people will agree with I say The Hulk takes this to the next level.  He is the result of an industrial accident, which is scary enough in it’s own right.  Plus, when mild-mannered Bruce Banner is angered, he goes completely out-of-control and transforms into a destructive monster that he cannot control and has no memories of. Developer’s Life – Every Developer is a Wonder Woman We have focused a lot lately on this “superhero series.”  I love fantasy books and movies, and I feel like there is a lot to be learned from them.  As I am writing this series, though, I have noticed that every super hero I write about is a man.  So today, I would like to talk about the major female super hero – Wonder Woman. Developer’s Life – Every Developer is a Harry Potter Harry Potter might not be a superhero in the traditional sense, but I believe he still has a lot to teach us and show us about life as a developer.  If you have been living under a rock for the last 17 years, you might not know that Harry Potter is the main character in an extremely popular series of books and movies documenting the education and tribulation of a young wizard (and his friends). Developer’s Life – Every Developer is Like Transformers Transformers may not be superheroes – they don’t wear capes, they don’t have amazing powers outside of their size and folding ability, they’re not even human (technically).  Part of their enduring popularity is that while we are enjoying over-the-top movies, we are learning about good leadership and strong personal skills. Developer’s Life – Every Developer is a Iron Man Iron Man is another superhero who is not naturally “super,” but relies on his brain (and money) to turn him into a fighting machine.  While traditional superheroes are still popular, a three-movie franchise and incorporation into the new Avengers series shows that Iron Man is popular enough on his own. Developer’s Life – Every Developer is a Sherlock Holmes I have been thinking a lot about how developers are like super heroes, and I have written two blog posts now comparing them to Spiderman and Superman.  I have a lot of love and respect for developers, and I hope that they are enjoying these articles, and others are learning a little bit about the profession.  There is another fictional character who, while not technically asuper hero, is very powerful, and I also think stands as a good example of a developer. That character is Sherlock Holmes.  Sherlock Holmes is a British detective, first made popular at the turn of the 19thcentury by author Sir Arthur Conan Doyle.  The original Sherlock Holmes was a brilliant detective who could solve the most mind-boggling crime through simple observations and deduction. Developer’s Life – Every Developer is a Chhota Bheem Chhota Bheem is a cartoon character that is extremely popular where I live.  He is my daughter’s favorite characters.  I like to say that children love Chhota Bheem more than their parents – it is lucky for us he is not real!  Children love Chhota Bheem because he is the absolute “good guy.”  He is smart, loyal, and strong.  He and his friends live in Dholakpur and fight off their many enemies – and always win – in every episode.  In each episode, they learn something about friendship, bravery, and being kind to others.  Chhota Bheem is a good role model for children, and I think that he is a good role model for developers are well. Developer’s Life – Every Developer is a Batman Batman is one of the darkest superheroes in the fantasy canon.  He does not come to his powers through any sort of magical coincidence or radioactive insect, but through a lot of psychological scarring caused by witnessing the death of his parents.  Despite his dark back story, he possesses a lot of admirable abilities that I feel bear comparison to developers. Developer’s Life – Every Developer is a Superman I enjoyed comparing developers to Spiderman so much, that I have decided to continue the trend and encourage some of my favorite people (developers) with another favorite superhero – Superman.  Superman is probably the most famous superhero – and one of the most inspiring. Developer’s Life – Every Developer is a Spiderman I have to admit, Spiderman is my favorite superhero.  The most recent movie recently was released in theaters, so it has been at the front of my mind for some time. Spiderman was my favorite superhero even before the latest movie came out, but of course I took my whole family to see the movie as soon as I could!  Every one of us loved it, including my daughter.  We all left the movie thinking how great it would be to be Spiderman.  So, with that in mind, I started thinking about how we are like Spiderman in our everyday lives, especially developers. I would like to know which Superhero is your favorite hero! Reference: Pinal Dave (http://blog.SQLAuthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Developer, Superhero

  Read the article

• SQLAuthority News – Tips for Traveling to Nepal

  - by pinaldave

  If you are a regular reader of this blog, you might know that I travel nearly 20+ days out of 30 days in a month. There are cases when I don’t have a chance to go home for an entire month and my family has to travel to different cities just to meet me. During my recent visit, one of my acquaintances suggested that I should blog about my travel experiences as well. This can be helpful to others who are traveling to the country or city. I have previously written about my experience about all the airlines in India. I would be writing about a few tips about traveling to the beautiful country Nepal today. Kathmandu, the capital of Nepal is very scenic. There are lots of historical places to see and visit. I was fortunate enough to stopover the Pashupatinath Temple, Bhaktapur, Vasantpur and the temple of Kumari Goddess. I also visited casinos there, but even if  I have stayed in Las Vegas for 3 and a half years before, I was not keen on them so I left the casinos just like what I did in Las Vegas . I also traveled to the famous Thamel area by car. Here are my quick tips for anyone who is planning to visit Nepal. They are not categorized but just written in the order that came to my mind. Please note that if you are an Indian, you will get a special privilege everywhere in Nepal, beginning right from the Indian airports. Use the expression “Nameste!” If you want to greet any Indian or Nepali. Indian Nationals do not need visa/passport to enter Nepal. In fact, Indian Nationals can just walk in to Nepal without any passport; but should have any valid Indian ID. There is no use of a passport since it will not be stamped at any immigration ports, whether in India or Nepal. Indian currency is widely accepted everywhere. However, please bring only Rs. 100 bills/notes as Rs. 500 or Rs. 1000 are not accepted. However, casinos there will accept larger bills. Indian National Language – Hindi is widely spoken and understood everywhere. I did not find a single person who had trouble speaking it. Nepali language uses the scripting language as Devnagari, which is similar to Hindi. Here, you will find food of almost every country.  The taste of Nepali food is authentic and very delicious. It is very safe to travel and move around in Kathmandu (despite what media suggests). However, it will really help if you have a friend who speaks Nepali. You can negotiate a few deals and cut off to almost 1/5 of the original quoted price of products sold here. If you are from Gujarat, India – you will find Nepali language sharing many common words. Temples are everywhere, so do not miss to visit a few of them. Pashupatinath is a must. Only followers of Hindu religion (from Nepal and India only) are allowed in most of the holy places. Camera is allowed everywhere except on the holy places. Now it is your turn to share your opinions or any suggestions. I think Nepal is a great country as there are lots of places to visit. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, T SQL, Technology

  Read the article

< Previous Page | 118 119 120 121 122 123 124 125 126 127 128 129  | Next Page >