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• Optimizing code using PIL

  - by freakazo

  Firstly sorry for the long piece of code pasted below. This is my first time actually having to worry about performance of an application so I haven't really ever worried about performance. This piece of code pretty much searches for an image inside another image, it takes 30 seconds to run on my computer, converting the images to greyscale and other changes shaved of 15 seconds, I need another 15 shaved off. I did read a bunch of pages and looked at examples but I couldn't find the same problems in my code. So any help would be greatly appreciated. From the looks of it (cProfile) 25 seconds is spent within the Image module, and only 5 seconds in my code. from PIL import Image import os, ImageGrab, pdb, time, win32api, win32con import cProfile def GetImage(name): name = name + '.bmp' try: print(os.path.join(os.getcwd(),"Images",name)) image = Image.open(os.path.join(os.getcwd(),"Images",name)) except: print('error opening image;', name) return image def Find(name): image = GetImage(name) imagebbox = image.getbbox() screen = ImageGrab.grab() #screen = Image.open(os.path.join(os.getcwd(),"Images","Untitled.bmp")) YLimit = screen.getbbox()[3] - imagebbox[3] XLimit = screen.getbbox()[2] - imagebbox[2] image = image.convert("L") Screen = screen.convert("L") Screen.load() image.load() #print(XLimit, YLimit) Found = False image = image.getdata() for y in range(0,YLimit): for x in range(0,XLimit): BoxCoordinates = x, y, x+imagebbox[2], y+imagebbox[3] ScreenGrab = screen.crop(BoxCoordinates) ScreenGrab = ScreenGrab.getdata() if image == ScreenGrab: Found = True #print("woop") return x,y if Found == False: return "Not Found" cProfile.run('print(Find("Login"))')

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• Incremental Timer

  - by Donal Rafferty

  I'm currently using a Timer and TimerTask to perform some work every 30 seconds. My problem is that after each time I do this work I want to increment the interval time of the Timer. So for example it starts off with 30 seconds between the timer firing but I want to add 10 seconds to the interval then so that the next time the Timer takes 40 seconds before it fires. Here is my current code: public void StartScanning() { scanTask = new TimerTask() { public void run() { handler.post(new Runnable() { public void run() { wifiManager.startScan(); scanCount++; if(SCAN_INTERVAL_TIME <= SCAN_MAX_INTERVAL){ SCAN_INTERVAL_TIME = SCAN_INTERVAL_TIME + SCAN_INCREASE_INTERVAL; t.schedule(scanTask, 0, SCAN_INTERVAL_TIME); } } }); }}; Log.d("SCAN_INTERVAL_TIME ** ", "SCAN_INTERVAL_TIME ** = " + SCAN_INTERVAL_TIME); t.schedule(scanTask, 0, SCAN_INTERVAL_TIME); } But the above gives the following error: 05-26 11:48:02.472: ERROR/AndroidRuntime(4210): java.lang.IllegalStateException: TimerTask is scheduled already Calling cancel or purge doesn't help. So I was wondering if anyone can help me find a solution? Is a timer even the right way to approach this?

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• bash and flock (file lock) - Doesn't seem to be locking....

  - by Rory

  I am playing with using flock, a bash command for file locks to prevent 2 different instances of the code from running more than once. I am using this testing code: ( ( flock -x 200 ; sleep 10 ; echo "original finished" ; ) 200>./test.lock ) & ( sleep 2 ; ( flock -x -w 2 200 ; echo "a finished" ) 200>./test.lock ) & I am running 2 subshells (backgrounded). The (flock NUM; ...) NUM>FILE syntax is from flock's man page. I expect that the first subshell will get an exclusive lock on test.lock, then wait 10 seconds, then print "original finished", all the time holding the lock. The second subshell will start at more or less the same time, wait 2 seconds, then try to get a lock on test.lock, but timeout after 2 seconds. If it gets a lock, then it'll print "a finished". If it doesn't get the lock, that subshell should stop, and nothing should be printed. Since the first subshell is waiting longer, it will keep the lock for 10 seconds, so the second subshell should not get the lock, and shouldn't finish. i.e. one should see "original finished" printed and not both. What actually happens is that "a finished" is printed, then "original finished" is printed. This implies that that the second subshell is either (a) not using the same lock as the first subhsell or (b) that it fails to get the lock, but continues to execute or (c) something else. Why don't those locks work?

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• Servlet requests are executed sequentially for no apparent reason in Glassfish v3

  - by Fabien Benoit

  Hi, I'm using Glassfish 3 Web profile and can't get http workers to execute concurrently requests on a servlet. This is how i observed the problem. I've made a very simple servlet, that writes the current thread name to the standard output and sleep for 10 seconds : protected void doGet(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException { System.out.println(Thread.currentThread().getName()); try { Thread.sleep(10000); // 10 sec } catch (InterruptedException ex) {} } } And when i'm running several simultaneous requests, I clearly see in the logs that the requests are sequentially executed (one trace every 10 seconds). INFO: http-thread-pool-8080-(2) (10 seconds later...) INFO: http-thread-pool-8080-(1) (10 seconds later...) INFO: http-thread-pool-8080-(2) etc. All my GF settings are untouched - it's the out-of-the-box config (the default thread pool is 2 threads min, 5 max if I recall properly). ...I really don't understand why the sleep() block all the others worker threads. Any insight would be greatly appreciated ! Thanks, Fabien

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• Slow MySQL Query not using filesort

  - by Canadaka

  I have a query on my homepage that is getting slower and slower as my database table grows larger. tablename = tweets_cache rows = 572,327 this is the query I'm currently using that is slow, over 5 seconds. SELECT * FROM tweets_cache t WHERE t.province='' AND t.mp='0' ORDER BY t.published DESC LIMIT 50; If I take out either the WHERE or the ORDER BY, then the query is super fast 0.016 seconds. I have the following indexes on the tweets_cache table. PRIMARY published mp category province author So i'm not sure why its not using the indexes since mp, provice and published all have indexes? Doing a profile of the query shows that its not using an index to sort the query and is using filesort which is really slow. possible_keys = mp,province Extra = Using where; Using filesort I tried adding a new multie-colum index with "profiles & mp". The explain shows that this new index listed under "possible_keys" and "key", but the query time is unchanged, still over 5 seconds. Here is a screenshot of the profiler info on the query. http://i355.photobucket.com/albums/r469/canadaka_bucket/slow_query_profile.png Something weird, I made a dump of my database to test on my local desktop so i don't screw up the live site. The same query on my local runs super fast, milliseconds. So I copied all the same mysql startup variables from the server to my local to make sure there wasn't some setting that might be causing this. But even after that the local query runs super fast, but the one on the live server is over 5 seconds. My database server is only using around 800MB of the 4GB it has available. here are the related my.ini settings i'm using default-storage-engine = MYISAM max_connections = 800 skip-locking key_buffer = 512M max_allowed_packet = 1M table_cache = 512 sort_buffer_size = 4M read_buffer_size = 4M read_rnd_buffer_size = 16M myisam_sort_buffer_size = 64M thread_cache_size = 8 query_cache_size = 128M # Try number of CPU's*2 for thread_concurrency thread_concurrency = 8 # Disable Federated by default skip-federated key_buffer = 512M sort_buffer_size = 256M read_buffer = 2M write_buffer = 2M key_buffer = 512M sort_buffer_size = 256M read_buffer = 2M write_buffer = 2M

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• Fast Lightweight Image Comparisson Metric Algorithm

  - by gav

  Hi All, I am developing an application for the Android platform which contains 1000+ image filters that have been 'evolved'. When a user selects a photo I want to present the most relevant filters first. This 'relevance' should be dependent on previous use cases. I have already developed tools that register when a filtered image is saved; this combination of filter and image can be seen as the training data for my system. The issue is that the comparison must occur between selecting an image and the next screen coming up. From a UI point of view I need the whole process to take less that 4 seconds; select an image- obtain a metric to use for similarity - check against use cases - return 6 closest matches. I figure with 4 seconds I can use animations and progress dialogs to keep the user happy. Due to platform contraints I am fairly limited in the computational expense of the algorithm. I have implemented a technique adapted from various online tutorials for running C code on the G1 and hence this language is available Specific Constraints; Qualcomm® MSM7201A™, 528 MHz Processor 320 x 480 Pixel bitmap in 32 bit ARGB ~ 2 seconds computational time for the native method to get the metric ~ 2 seconds to compare the metric of the current image with training data This is an academic project so all ideas are welcome, anything you can think of or have heard about would be of interest to me. My ideas; I want to keep the complexity down (O(n*m)?) by using pixel data only rather than a neighbourhood function I was looking at using the Colour historgram/Greyscale histogram/Texture/Entropy of the image, combining them to make the measure. There will be an obvious loss of information but I need the resultant metric to be substantially smaller than the memory footprint of the image (~0.512 MB) As I said, any ideas to direct my research would be fantastic. Kind regards, Gavin

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• CLLocationManagerDelegate method not calling in iPodTouch

  - by Siddharth

  HI all, I was using a sample code which uses CLLocationManager class to determine the current location of user. when i run this app on iPad i am getting the correct location but when i run the same app on iPod Touch i am getting a blank label i.e nothing is displayed on the label .although wi-fi signal strength is good in both iPod and iPad.The code looks like... - (void)locationManager:(CLLocationManager *)manager didUpdateToLocation:(CLLocation *)newLocation fromLocation:(CLLocation *)oldLocation{ int degrees = newLocation.coordinate.latitude; double decimal = fabs(newLocation.coordinate.latitude - degrees); int minutes = decimal * 60; double seconds = decimal * 3600 - minutes * 60; NSString *lat = [NSString stringWithFormat:@"%d° %d' %1.4f\"", degrees, minutes, seconds]; latLabel.text = lat; [latLocationArray addObject:lat]; degrees = newLocation.coordinate.longitude; decimal = fabs(newLocation.coordinate.longitude - degrees); minutes = decimal * 60; seconds = decimal * 3600 - minutes * 60; NSString *longt = [NSString stringWithFormat:@"%d° %d' %1.4f\"", degrees, minutes, seconds]; longLabel.text = longt; [longLocationArray addObject:longt]; }

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• C# vs C - Big performance difference

  - by John

  I'm finding massive performance differences between similar code in C anc C#. The C code is: #include <stdio.h> #include <time.h> #include <math.h> main() { int i; double root; clock_t start = clock(); for (i = 0 ; i <= 100000000; i++){ root = sqrt(i); } printf("Time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC); } And the C# (console app) is: using System; using System.Collections.Generic; using System.Text; namespace ConsoleApplication2 { class Program { static void Main(string[] args) { DateTime startTime = DateTime.Now; double root; for (int i = 0; i <= 100000000; i++) { root = Math.Sqrt(i); } TimeSpan runTime = DateTime.Now - startTime; Console.WriteLine("Time elapsed: " + Convert.ToString(runTime.TotalMilliseconds/1000)); } } } With the above code, the C# completes in 0.328125 seconds (release version) and the C takes 11.14 seconds to run. The c is being compiled to a windows executable using mingw. I've always been under the assumption that C/C++ were faster or at least comparable to C#.net. What exactly is causing the C to run over 30 times slower? EDIT: It does appear that the C# optimizer was removing the root as it wasn't being used. I changed the root assignment to root += and printed out the total at the end. I've also compiled the C using cl.exe with the /O2 flag set for max speed. The results are now: 3.75 seconds for the C 2.61 seconds for the C# The C is still taking longer, but this is acceptable

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• Perl: how to pretty-print time duration

  - by sds

  How do I pretty print time duration in perl? The only thing I could come up with so far is my $interval = 1351521657387 - 1351515910623; # milliseconds my $duration = DateTime::Duration->new( seconds => POSIX::floor($interval/1000) , nanoseconds => 1000000 * ($interval % 1000), ); my $df = DateTime::Format::Duration->new( pattern => '%Y years, %m months, %e days, ' . '%H hours, %M minutes, %S seconds, %N nanoseconds', normalize => 1, ); print $df->format_duration($duration); which results in 0 years, 00 months, 0 days, 01 hours, 35 minutes, 46 seconds, 764000000 nanoseconds This is no good for me for the following reasons: I don't want to see "0 years" (space waste) &c and I don't want to remove "%Y years" from the pattern (what if I do need years next time?) I know in advance that my precision is only milliseconds, I don't want to see the 6 zeros in the nanoseconds part. I care about prettiness/compactness/human readability much more than about precision/machine readability. I.e., I want to see something like "1.2 years" or "3.22 months" or "7.88 days" or "5.7 hours" or "75.5 minutes" (or "1.26 hours, whatever looks better to you) or "24.7 seconds" or "133.7 milliseconds" &c (similar to how R prints difftime)

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• CLLocationManager class method not calling in iPodTouch

  - by Siddharth

  HI all, I was using a sample code which uses CLLocationManager class to determine the current location of user. when i run this app on iPad i am getting the correct location but when i run the same app on iPod Touch i am getting a blank label i.e nothing is displayed on the label .although wi-fi signal strength is good in both iPod and iPad.The code looks like... - (void)locationManager:(CLLocationManager *)manager didUpdateToLocation:(CLLocation *)newLocation fromLocation:(CLLocation *)oldLocation{ int degrees = newLocation.coordinate.latitude; double decimal = fabs(newLocation.coordinate.latitude - degrees); int minutes = decimal * 60; double seconds = decimal * 3600 - minutes * 60; NSString *lat = [NSString stringWithFormat:@"%d° %d' %1.4f\"", degrees, minutes, seconds]; latLabel.text = lat; [latLocationArray addObject:lat]; degrees = newLocation.coordinate.longitude; decimal = fabs(newLocation.coordinate.longitude - degrees); minutes = decimal * 60; seconds = decimal * 3600 - minutes * 60; NSString *longt = [NSString stringWithFormat:@"%d° %d' %1.4f\"", degrees, minutes, seconds]; longLabel.text = longt; [longLocationArray addObject:longt]; }

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• jquery callback functions failing to finish execution

  - by calumbrodie

  I'm testing a jquery app i've written and have come across some unexpected behaviour $('button.clickme').live('click',function(){ //do x (takes 2 seconds) //do y (takes 4 seconds) //do z (takes 0.5 seconds) }) The event can be triggered by a number of buttons. What I'm finding is that when I click each button slowly (allowing 10 seconds between clicks) - my callback function executes correctly (actions x, y & z complete). However If I rapidly click buttons on my page it appears that the function sometimes only completes up to step x or y before terminating. My question: Is it the case that if this function is fired by a clicking second DOM element, while the first callback function is completing - will jQuery terminate the first callback and start over again? Do I have to write my callback function explicitly outside the event handler and then call it?? function doStuff() { //do x //do y //do z ( } $('button.clickme).live('click',doStuff()) If this is the case can someone explain why this is happening or give me a link to some advice on best practice on closures etc - I'd like to know the BEST way to write jQuery to improve performance etc. Thanks

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• Weird stuttering issues not related to GC.

  - by Smills

  I am getting some odd stuttering issues with my game even though my FPS never seems to drop below 30. About every 5 seconds my game stutters. I was originally getting stuttering every 1-2 seconds due to my garbage collection issues, but I have sorted those and will often go 15-20 seconds without a garbage collection. Despite this, my game still stutters periodically even when there is no GC listed in logcat anywhere near the stutter. Even when I take out most of my code and simply make my "physics" code the below code I get this weird slowdown issue. I feel that I am missing something or overlooking something. Shouldn't that "elapsed" code that I put in stop any variance in the speed of the main character related to changes in FPS? Any input/theories would be awesome. Physics: private void updatePhysics() { //get current time long now = System.currentTimeMillis(); //added this to see if I could speed it up, it made no difference Thread myThread = Thread.currentThread(); myThread.setPriority(Thread.MAX_PRIORITY); //work out elapsed time since last frame in seconds double elapsed = (now - mLastTime2) / 1000.0; mLastTime2 = now; //measures FPS and displays in logcat once every 30 frames fps+=1/elapsed; fpscount+=1; if (fpscount==30) { fps=fps/fpscount; Log.i("myActivity","FPS: "+fps+" Touch: "+touch); fpscount=0; } //this should make the main character (theoretically) move upwards at a steady pace mY-=100*elapsed; //increase amount I translate the draw to = main characters Y //location if the main character goes upwards if (mY<=viewY) { viewY=mY; } }

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• What about parallelism across network using multiple PCs?

  - by MainMa

  Parallel computing is used more and more, and new framework features and shortcuts make it easier to use (for example Parallel extensions which are directly available in .NET 4). Now what about the parallelism across network? I mean, an abstraction of everything related to communications, creation of processes on remote machines, etc. Something like, in C#: NetworkParallel.ForEach(myEnumerable, () => { // Computing and/or access to web ressource or local network database here }); I understand that it is very different from the multi-core parallelism. The two most obvious differences would probably be: The fact that such parallel task will be limited to computing, without being able for example to use files stored locally (but why not a database?), or even to use local variables, because it would be rather two distinct applications than two threads of the same application, The very specific implementation, requiring not just a separate thread (which is quite easy), but spanning a process on different machines, then communicating with them over local network. Despite those differences, such parallelism is quite possible, even without speaking about distributed architecture. Do you think it will be implemented in a few years? Do you agree that it enables developers to easily develop extremely powerfull stuff with much less pain? Example: Think about a business application which extracts data from the database, transforms it, and displays statistics. Let's say this application takes ten seconds to load data, twenty seconds to transform data and ten seconds to build charts on a single machine in a company, using all the CPU, whereas ten other machines are used at 5% of CPU most of the time. In a such case, every action may be done in parallel, resulting in probably six to ten seconds for overall process instead of forty.

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• vs2002: c# multi threading question..

  - by dotnet-practitioner

  I would like to invoke heavy duty method dowork on a separate thread and kill it if its taking longer than 3 seconds. Is there any problem with the following code? class Class1 { /// <summary> /// The main entry point for the application. /// </summary> /// [STAThread] static void Main(string[] args) { Console.WriteLine("starting new thread"); Thread t = new Thread(new ThreadStart(dowork)); t.Start(); DateTime start = DateTime.Now; TimeSpan span = DateTime.Now.Subtract(start); bool wait = true; while (wait == true) { if (span.Seconds>3) { t.Abort(); wait = false; } span = DateTime.Now.Subtract(start); } Console.WriteLine("ending new thread after seconds = {0}", span.Seconds); Console.WriteLine("all done"); Console.ReadLine(); } static void dowork() { Console.WriteLine("doing heavy work inside hello"); Thread.Sleep(7000); Console.WriteLine("*** finished**** doing heavy work inside hello"); } }

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• PHP shell_exec() - Run directly, or perform a cron (bash/php) and include MySQL layer?

  - by Jimbo

  Sorry if the title is vague - I wasn't quite sure how to word it! What I'm Doing I'm running a Linux command to output data into a variable, parse the data, and output it as an array. Array values will be displayed on a page using PHP, and this PHP page output is requested via AJAX every 10 seconds so, in effect, the data will be retrieved and displayed/updated every 10 seconds. There could be as many as 10,000 characters being parsed on every request, although this is usually much lower. Alternative Idea I want to know if there is a better* alternative method of retrieving this data every 10 seconds, as multiple users (<10) will be having this command executed automatically for them. A cronjob running on the server could execute either bash or php (which is faster?) to grab the data and store it in a MySQL database. Then, any AJAX calls to the PHP output would return values in the MySQL database rather than making a direct call to execute server code every 10 seconds. Why? I know there are security concerns with running execs directly from PHP, and (I hope this isn't micro-optimisation) I'm worried about CPU usage on the server. The server is running a sempron processor. Yes, they do still exist. Having this only execute when the user is on the page (idea #1) means that the server isn't running code that doesn't need to be run. However, is this slow and insecure? Just in case the type of linux command may be of assistance in determining it's efficiency: shell_exec("transmission-remote $host:$port --auth $username:$password -l"); I'm hoping that there are differences in efficiency and level of security with the two methods I have outlined above, and that this isn't just micro-micro-optimisation. If there are alternative methods that are better*, I'd love to learn about these! :)

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• Multi threading question..

  - by dotnet-practitioner

  I would like to invoke heavy duty method dowork on a separate thread and kill it if its taking longer than 3 seconds. Is there any problem with the following code? class Class1 { /// <summary> /// The main entry point for the application. /// </summary> [STAThread] static void Main(string[] args) { Console.WriteLine("starting new thread"); Thread t = new Thread(new ThreadStart(dowork)); t.Start(); DateTime start = DateTime.Now; TimeSpan span = DateTime.Now.Subtract(start); bool wait = true; while (wait == true) { if (span.Seconds > 3) { t.Abort(); wait = false; } span = DateTime.Now.Subtract(start); } Console.WriteLine("ending new thread after seconds = {0}", span.Seconds); Console.WriteLine("all done"); Console.ReadLine(); } static void dowork() { Console.WriteLine("doing heavy work inside hello"); Thread.Sleep(7000); Console.WriteLine("*** finished**** doing heavy work inside hello"); } }

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• C#: Optional Parameters - Pros and Pitfalls

  - by James Michael Hare

  When Microsoft rolled out Visual Studio 2010 with C# 4, I was very excited to learn how I could apply all the new features and enhancements to help make me and my team more productive developers. Default parameters have been around forever in C++, and were intentionally omitted in Java in favor of using overloading to satisfy that need as it was though that having too many default parameters could introduce code safety issues.  To some extent I can understand that move, as I’ve been bitten by default parameter pitfalls before, but at the same time I feel like Java threw out the baby with the bathwater in that move and I’m glad to see C# now has them. This post briefly discusses the pros and pitfalls of using default parameters.  I’m avoiding saying cons, because I really don’t believe using default parameters is a negative thing, I just think there are things you must watch for and guard against to avoid abuses that can cause code safety issues. Pro: Default Parameters Can Simplify Code Let’s start out with positives.  Consider how much cleaner it is to reduce all the overloads in methods or constructors that simply exist to give the semblance of optional parameters.  For example, we could have a Message class defined which allows for all possible initializations of a Message: 1: public class Message 2: { 3: // can either cascade these like this or duplicate the defaults (which can introduce risk) 4: public Message() 5: : this(string.Empty) 6: { 7: } 8:  9: public Message(string text) 10: : this(text, null) 11: { 12: } 13:  14: public Message(string text, IDictionary<string, string> properties) 15: : this(text, properties, -1) 16: { 17: } 18:  19: public Message(string text, IDictionary<string, string> properties, long timeToLive) 20: { 21: // ... 22: } 23: }   Now consider the same code with default parameters: 1: public class Message 2: { 3: // can either cascade these like this or duplicate the defaults (which can introduce risk) 4: public Message(string text = "", IDictionary<string, string> properties = null, long timeToLive = -1) 5: { 6: // ... 7: } 8: }   Much more clean and concise and no repetitive coding!  In addition, in the past if you wanted to be able to cleanly supply timeToLive and accept the default on text and properties above, you would need to either create another overload, or pass in the defaults explicitly.  With named parameters, though, we can do this easily: 1: var msg = new Message(timeToLive: 100);   Pro: Named Parameters can Improve Readability I must say one of my favorite things with the default parameters addition in C# is the named parameters.  It lets code be a lot easier to understand visually with no comments.  Think how many times you’ve run across a TimeSpan declaration with 4 arguments and wondered if they were passing in days/hours/minutes/seconds or hours/minutes/seconds/milliseconds.  A novice running through your code may wonder what it is.  Named arguments can help resolve the visual ambiguity: 1: // is this days/hours/minutes/seconds (no) or hours/minutes/seconds/milliseconds (yes) 2: var ts = new TimeSpan(1, 2, 3, 4); 3:  4: // this however is visually very explicit 5: var ts = new TimeSpan(days: 1, hours: 2, minutes: 3, seconds: 4);   Or think of the times you’ve run across something passing a Boolean literal and wondered what it was: 1: // what is false here? 2: var sub = CreateSubscriber(hostname, port, false); 3:  4: // aha! Much more visibly clear 5: var sub = CreateSubscriber(hostname, port, isBuffered: false);   Pitfall: Don't Insert new Default Parameters In Between Existing Defaults Now let’s consider a two potential pitfalls.  The first is really an abuse.  It’s not really a fault of the default parameters themselves, but a fault in the use of them.  Let’s consider that Message constructor again with defaults.  Let’s say you want to add a messagePriority to the message and you think this is more important than a timeToLive value, so you decide to put messagePriority before it in the default, this gives you: 1: public class Message 2: { 3: public Message(string text = "", IDictionary<string, string> properties = null, int priority = 5, long timeToLive = -1) 4: { 5: // ... 6: } 7: }   Oh boy have we set ourselves up for failure!  Why?  Think of all the code out there that could already be using the library that already specified the timeToLive, such as this possible call: 1: var msg = new Message(“An error occurred”, myProperties, 1000);   Before this specified a message with a TTL of 1000, now it specifies a message with a priority of 1000 and a time to live of -1 (infinite).  All of this with NO compiler errors or warnings. So the rule to take away is if you are adding new default parameters to a method that’s currently in use, make sure you add them to the end of the list or create a brand new method or overload. Pitfall: Beware of Default Parameters in Inheritance and Interface Implementation Now, the second potential pitfalls has to do with inheritance and interface implementation.  I’ll illustrate with a puzzle: 1: public interface ITag 2: { 3: void WriteTag(string tagName = "ITag"); 4: } 5:  6: public class BaseTag : ITag 7: { 8: public virtual void WriteTag(string tagName = "BaseTag") { Console.WriteLine(tagName); } 9: } 10:  11: public class SubTag : BaseTag 12: { 13: public override void WriteTag(string tagName = "SubTag") { Console.WriteLine(tagName); } 14: } 15:  16: public static class Program 17: { 18: public static void Main() 19: { 20: SubTag subTag = new SubTag(); 21: BaseTag subByBaseTag = subTag; 22: ITag subByInterfaceTag = subTag; 23:  24: // what happens here? 25: subTag.WriteTag(); 26: subByBaseTag.WriteTag(); 27: subByInterfaceTag.WriteTag(); 28: } 29: }   What happens?  Well, even though the object in each case is SubTag whose tag is “SubTag”, you will get: 1: SubTag 2: BaseTag 3: ITag   Why?  Because default parameter are resolved at compile time, not runtime!  This means that the default does not belong to the object being called, but by the reference type it’s being called through.  Since the SubTag instance is being called through an ITag reference, it will use the default specified in ITag. So the moral of the story here is to be very careful how you specify defaults in interfaces or inheritance hierarchies.  I would suggest avoiding repeating them, and instead concentrating on the layer of classes or interfaces you must likely expect your caller to be calling from. For example, if you have a messaging factory that returns an IMessage which can be either an MsmqMessage or JmsMessage, it only makes since to put the defaults at the IMessage level since chances are your user will be using the interface only. So let’s sum up.  In general, I really love default and named parameters in C# 4.0.  I think they’re a great tool to help make your code easier to read and maintain when used correctly. On the plus side, default parameters: Reduce redundant overloading for the sake of providing optional calling structures. Improve readability by being able to name an ambiguous argument. But remember to make sure you: Do not insert new default parameters in the middle of an existing set of default parameters, this may cause unpredictable behavior that may not necessarily throw a syntax error – add to end of list or create new method. Be extremely careful how you use default parameters in inheritance hierarchies and interfaces – choose the most appropriate level to add the defaults based on expected usage. Technorati Tags: C#,.NET,Software,Default Parameters

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• C#/.NET Little Wonders: The Timeout static class

  - by James Michael Hare

  Once again, in this series of posts I look at the parts of the .NET Framework that may seem trivial, but can help improve your code by making it easier to write and maintain. The index of all my past little wonders posts can be found here. When I started the “Little Wonders” series, I really wanted to pay homage to parts of the .NET Framework that are often small but can help in big ways.  The item I have to discuss today really is a very small item in the .NET BCL, but once again I feel it can help make the intention of code much clearer and thus is worthy of note. The Problem - Magic numbers aren’t very readable or maintainable In my first Little Wonders Post (Five Little Wonders That Make Code Better) I mention the TimeSpan factory methods which, I feel, really help the readability of constructed TimeSpan instances. Just to quickly recap that discussion, ask yourself what the TimeSpan specified in each case below is 1: // Five minutes? Five Seconds? 2: var fiveWhat1 = new TimeSpan(0, 0, 5); 3: var fiveWhat2 = new TimeSpan(0, 0, 5, 0); 4: var fiveWhat3 = new TimeSpan(0, 0, 5, 0, 0); You’d think they’d all be the same unit of time, right?  After all, most overloads tend to tack additional arguments on the end.  But this is not the case with TimeSpan, where the constructor forms are:     TimeSpan(int hours, int minutes, int seconds);     TimeSpan(int days, int hours, int minutes, int seconds);     TimeSpan(int days, int hours, int minutes, int seconds, int milliseconds); Notice how in the 4 and 5 parameter version we suddenly have the parameter days slipping in front of hours?  This can make reading constructors like those above much harder.  Fortunately, there are TimeSpan factory methods to help make your intention crystal clear: 1: // Ah! Much clearer! 2: var fiveSeconds = TimeSpan.FromSeconds(5); These are great because they remove all ambiguity from the reader!  So in short, magic numbers in constructors and methods can be ambiguous, and anything we can do to clean up the intention of the developer will make the code much easier to read and maintain. Timeout – Readable identifiers for infinite timeout values In a similar way to TimeSpan, let’s consider specifying timeouts for some of .NET’s (or our own) many methods that allow you to specify timeout periods. For example, in the TPL Task class, there is a family of Wait() methods that can take TimeSpan or int for timeouts.  Typically, if you want to specify an infinite timeout, you’d just call the version that doesn’t take a timeout parameter at all: 1: myTask.Wait(); // infinite wait But there are versions that take the int or TimeSpan for timeout as well: 1: // Wait for 100 ms 2: myTask.Wait(100); 3:  4: // Wait for 5 seconds 5: myTask.Wait(TimeSpan.FromSeconds(5); Now, if we want to specify an infinite timeout to wait on the Task, we could pass –1 (or a TimeSpan set to –1 ms), which what the .NET BCL methods with timeouts use to represent an infinite timeout: 1: // Also infinite timeouts, but harder to read/maintain 2: myTask.Wait(-1); 3: myTask.Wait(TimeSpan.FromMilliseconds(-1)); However, these are not as readable or maintainable.  If you were writing this code, you might make the mistake of thinking 0 or int.MaxValue was an infinite timeout, and you’d be incorrect.  Also, reading the code above it isn’t as clear that –1 is infinite unless you happen to know that is the specified behavior. To make the code like this easier to read and maintain, there is a static class called Timeout in the System.Threading namespace which contains definition for infinite timeouts specified as both int and TimeSpan forms: Timeout.Infinite An integer constant with a value of –1 Timeout.InfiniteTimeSpan A static readonly TimeSpan which represents –1 ms (only available in .NET 4.5+) This makes our calls to Task.Wait() (or any other calls with timeouts) much more clear: 1: // intention to wait indefinitely is quite clear now 2: myTask.Wait(Timeout.Infinite); 3: myTask.Wait(Timeout.InfiniteTimeSpan); But wait, you may say, why would we care at all?  Why not use the version of Wait() that takes no arguments?  Good question!  When you’re directly calling the method with an infinite timeout that’s what you’d most likely do, but what if you are just passing along a timeout specified by a caller from higher up?  Or perhaps storing a timeout value from a configuration file, and want to default it to infinite? For example, perhaps you are designing a communications module and want to be able to shutdown gracefully, but if you can’t gracefully finish in a specified amount of time you want to force the connection closed.  You could create a Shutdown() method in your class, and take a TimeSpan or an int for the amount of time to wait for a clean shutdown – perhaps waiting for client to acknowledge – before terminating the connection.  So, assume we had a pub/sub system with a class to broadcast messages: 1: // Some class to broadcast messages to connected clients 2: public class Broadcaster 3: { 4: // ... 5:  6: // Shutdown connection to clients, wait for ack back from clients 7: // until all acks received or timeout, whichever happens first 8: public void Shutdown(int timeout) 9: { 10: // Kick off a task here to send shutdown request to clients and wait 11: // for the task to finish below for the specified time... 12:  13: if (!shutdownTask.Wait(timeout)) 14: { 15: // If Wait() returns false, we timed out and task 16: // did not join in time. 17: } 18: } 19: } We could even add an overload to allow us to use TimeSpan instead of int, to give our callers the flexibility to specify timeouts either way: 1: // overload to allow them to specify Timeout in TimeSpan, would 2: // just call the int version passing in the TotalMilliseconds... 3: public void Shutdown(TimeSpan timeout) 4: { 5: Shutdown(timeout.TotalMilliseconds); 6: } Notice in case of this class, we don’t assume the caller wants infinite timeouts, we choose to rely on them to tell us how long to wait.  So now, if they choose an infinite timeout, they could use the –1, which is more cryptic, or use Timeout class to make the intention clear: 1: // shutdown the broadcaster, waiting until all clients ack back 2: // without timing out. 3: myBroadcaster.Shutdown(Timeout.Infinite); We could even add a default argument using the int parameter version so that specifying no arguments to Shutdown() assumes an infinite timeout: 1: // Modified original Shutdown() method to add a default of 2: // Timeout.Infinite, works because Timeout.Infinite is a compile 3: // time constant. 4: public void Shutdown(int timeout = Timeout.Infinite) 5: { 6: // same code as before 7: } Note that you can’t default the ShutDown(TimeSpan) overload with Timeout.InfiniteTimeSpan since it is not a compile-time constant.  The only acceptable default for a TimeSpan parameter would be default(TimeSpan) which is zero milliseconds, which specified no wait, not infinite wait. Summary While Timeout.Infinite and Timeout.InfiniteTimeSpan are not earth-shattering classes in terms of functionality, they do give you very handy and readable constant values that you can use in your programs to help increase readability and maintainability when specifying infinite timeouts for various timeouts in the BCL and your own applications. Technorati Tags: C#,CSharp,.NET,Little Wonders,Timeout,Task

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• Applications: How to create a custom dialog box for Windows Mobile 6 (native)

  - by TechTwaddle

  Ashraf, on the MSDN forum, asks, “Is there a way to make a default choice for the messagebox that happens after a period of time if the user doesn't choose (Clicked ) Yes or No buttons.” To elaborate, the requirement is to show a message box to the user with certain options to select, and if the user does not respond within a predefined time limit (say 8 seconds) then the message box must dismiss itself and select a default option. Now such a functionality is not available with the MessageBox() api, you will have to write your own custom dialog box. Surely, creating a dialog box is quite a simple task using the DialogBox() api, and we have been creating full screen dialog boxes all the while. So how will this custom message box be any different? It’s not much different from a regular dialog box except for a few changes in its properties. First, it has a title bar but no buttons on the title bar (no ‘x’ or ‘ok’ button on the title bar), it doesn’t occupy full screen and it contains the controls that you put into it, thus justifying the title ‘custom’. So in this post we create a custom dialog box with two buttons, ‘Black’ and ‘White’. The user is given 8 seconds to select one of those colours, if the user doesn’t make a selection in 8 seconds, the default option ‘Black’ is selected. Before going into the implementation here is a video of how the dialog box works; Custom dialog box To start off, add a new dialog resource into your application, size it appropriately and add whatever controls you need to the dialog. In my case, I added two static text labels and two buttons, as below; Now we need to write up the window procedure for this dialog, here is the complete function; BOOL CALLBACK CustomDialogProc(HWND hDlg, UINT uMessage, WPARAM wParam, LPARAM lParam) {     int wmID, wmEvent;     PAINTSTRUCT ps;     HDC hdc;     static int timeCount = 0;     switch(uMessage)     {         case WM_INITDIALOG:             {                 SHINITDLGINFO shidi;                 memset(&shidi, 0, sizeof(shidi));                 shidi.dwMask = SHIDIM_FLAGS;                 //shidi.dwFlags = SHIDIF_DONEBUTTON | SHIDIF_SIPDOWN | SHIDIF_SIZEDLGFULLSCREEN | SHIDIF_EMPTYMENU;                 shidi.dwFlags = SHIDIF_SIPDOWN | SHIDIF_EMPTYMENU;                 shidi.hDlg = hDlg;                 SHInitDialog(&shidi);                 SHDoneButton(hDlg, SHDB_HIDE);                 timeCount = 0;                 SetWindowText(GetDlgItem(hDlg, IDC_STATIC_TIME_REMAINING), L"Time remaining: 8 second(s)");                 SetTimer(hDlg, MY_TIMER, 1000, NULL);             }             return TRUE;         case WM_COMMAND:             {                 wmID = LOWORD(wParam);                 wmEvent = HIWORD(wParam);                 switch(wmID)                 {                     case IDC_BUTTON_BLACK:                         KillTimer(hDlg, MY_TIMER);                         EndDialog(hDlg, IDC_BUTTON_BLACK);                         break;                     case IDC_BUTTON_WHITE:                         KillTimer(hDlg, MY_TIMER);                         EndDialog(hDlg, IDC_BUTTON_WHITE);                         break;                 }             }             break;         case WM_TIMER:             {                 if (wParam == MY_TIMER)                 {                     WCHAR wszText[128];                     memset(&wszText, 0, sizeof(wszText));                     timeCount++;                     //8 seconds are over, dismiss the dialog, select def value                     if (timeCount >= 8)                     {                         KillTimer(hDlg, MY_TIMER);                         EndDialog(hDlg, IDC_BUTTON_BLACK_DEF);                     }                     wsprintf(wszText, L"Time remaining: %d second(s)", 8-timeCount);                     SetWindowText(GetDlgItem(hDlg, IDC_STATIC_TIME_REMAINING), wszText);                     UpdateWindow(GetDlgItem(hDlg, IDC_STATIC_TIME_REMAINING));                 }             }             break;         case WM_PAINT:             {                 hdc = BeginPaint(hDlg, &ps);                 EndPaint(hDlg, &ps);             }             break;     }     return FALSE; } The MSDN documentation mentions that you need to specify the flag WS_NONAVDONEBUTTON, but I got an error saying that the value could not be found, so we can ignore this for now. Next up, while calling SHInitDialog() for your custom dialog, make sure that you don’t specify SHDIF_DONEBUTTON in the dwFlags member of the SHINITDIALOG structure, this member makes the ‘ok’ button appear on the dialog title bar. Finally, we need to call SHDoneButton() with SHDB_HIDE flag to, well, hide the Done button. The ‘Done’ button is the same as the ‘ok’ button, so this step might seem redundant, and the dialog works fine without calling SHDoneButton() too, but it’s better to stick with the documentation (; So you can see that we have followed all these steps above, under WM_INITDIALOG. We also setup a few things like a variable to keep track of the time, and setting off a one second timer. Every time the timer fires, we receive a WM_TIMER message. We then update the static label displaying the amount of time left to the user. If 8 seconds go by without the user selecting any option, we kill the timer and end the dialog with IDC_BUTTON_BLACK_DEF. This is just a #define’d integer value, make sure it’s unique. You’ll see why this is important. If the user makes a selection, either Black or White, we kill the timer and end the dialog with corresponding selection the user made, that is, either IDC_BUTTON_BLACK or IDC_BUTTON_WHITE. Ok, so now our custom dialog is ready to be used. I invoke the custom dialog from a menu entry in the main windows as below, case IDM_MENU_CUSTOMDLG:     {         int ret = DialogBox(g_hInst, MAKEINTRESOURCE(IDD_CUSTOM_DIALOG), hWnd, CustomDialogProc);         switch(ret)         {             case IDC_BUTTON_BLACK_DEF:                 SetWindowText(g_hStaticSelection, L"You Selected: Black (default)");                 break;             case IDC_BUTTON_BLACK:                 SetWindowText(g_hStaticSelection, L"You Selected: Black");                 break;             case IDC_BUTTON_WHITE:                 SetWindowText(g_hStaticSelection, L"You Selected: White");                 break;         }         UpdateWindow(g_hStaticSelection);     }     break; So you see why ending the dialog with the corresponding value was important, that’s what the DialogBox() api returns with. And in the main window I update a static text label to show which option was selected. I cranked this out in about an hour, and unfortunately don’t have time for a managed C# version. That will have to be another post, if I manage to get it working that is (;

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• From Bluehost to WP Engine, My WordPress Story

  - by thatjeffsmith

  This is probably the longest blog post I’ve written in a LONG time. And if you’re used to coming here for the Oracle stuff, this post is not about that. It’s about my blog, and the stuff under the hood that makes it run, AKA WordPress. If you want to skip to the juicy stuff, then use these shortcuts: My Site Slowed Down How I Moved to WP Engine How WP Engine ‘Hooked’ Me Why WP Engine? I started thatJeffSmith.com on May 28th, 2010. I had been already been blogging for several years, but a couple of really smart people I respected (Andy, Brent – thanks again!) suggested that I take ownership of my content and begin building my personal brand. I thought that was a good idea, and so I signed up for service with bluehost. Bluehost makes setting up a WordPress site very, very easy. And, they continued to be easy to work with for the past 2 years. I would even recommend them to anyone looking to host their own WordPress install/site. For $83.40, I purchased a year’s worth of service and my domain name registration – a very good value. And then last year I paid $107.40 for another year’s services. And when that year expired I paid another $190.80 for an additional two year’s service in advance. I had been up to that point, getting my money’s worth. And then, just a few weeks ago… My Site Slowed to a Crawl That spike was from an April Fool's Day Post, I think Why? Well, when I first started blogging, I had the same problem that most beginner bloggers have – not many readers. In my first year of blogging, I think the highest number of readers on a single day was about 125. I remember that day as I was very excited to break 100! Bluehost was very reliable, serving up my content with maybe a total of 3-4 outages in the past 2 years. Support was usually very prompt with answers and solutions, and I love their ‘Chat now’ technology – much nicer than message boards only or pay-to-talk phone support. In the past 6 months however, I noticed a couple of things: daily traffic was increasing – woohoo! my service was experiencing severe CPU throttling – doh! To be honest, I wasn’t aware the throttling was occuring, but I did know that the response time of my blog was starting to lag. Average load times were approaching 20-30 seconds. Not good when good sites are loading in 5 seconds or less. And just this past week, in getting ready to launch a new website for work that sucked in an RSS feed from my blog, the new page was left waiting for more than a minute. Not good! In fact my boss asked, why aren’t you blogging on Blogger? Ugh. I tried a few things to fix the problem: I paid for a premium WordPress theme – Themify’s Grido (thanks to @SQLRockstar for the heads-up) I installed a couple of WP caching plugins I read every WP optimization blog post I could get my greedy little eyes on However, at the same time I was also getting addicted to WordPress bloggers talking about all the cool things you could do with your blog. As a result I had at one point about 30 different plugins installed. WordPress runs on MySQL, and certain queries running via these plugins were starving for CPU. Plugins that would be called every page load meant that as more people clicked on my site, the more CPU I needed. I’m not stupid, so I eventually figured out that maybe less plugins was better, and was able to go down to just 20. But still, the site was running like a dog. CPU Throttling, makes MySQL wait to run a query Bluehost runs shared servers. Your site runs on the same box that several hundred (or thousand?) other services are running on. If you take more CPU than they think you should have, they will limit your service by making you stand in line for CPU, AKA ‘throttling.’ This is not bad. This business model allows them to serve many, many users for a very fair price. It works great until, well, until it doesn’t. I noticed in the last week that for every minute of service, I was being throttled between 60 and 300 seconds. If there were 5 MySQL processes running, then every single one of them were being held in check. The blog visitor notice this as their page requests would take a minute or more to be answered. Bluehost unfortunately doesn’t offer dedicated server hosting, so there was no real upgrade path for me follow and remain one of their customers. So what was I to do? Uninstall every plugin and hope the site sped up? Ask for people to take turns on my blog? I decided to spend my way out of the problem. I signed up for service with WP Engine and moved ThatJeffSmith.com The first 2 months are free, and after that it’s about $29/month to run my site on their system. My math tells me that’s a good bit more expensive than what Bluehost was charging me – to the tune of about 300% more a month. Oh, and I should just say that my blog is a personal blog even though I talk about work stuff here. I don’t get paid for blogging, I don’t sell ads, and I don’t expense the service fees – this is my personal passion. So is it worth it? In the first 4 days, it seems to be totally worth it. Load times have gone from 20-30 seconds to less than 5 seconds. A few folks have told me via Twitter that they notice faster page loads. I anticipate this will indirectly lead to more traffic as Google penalizes you in search results if your site is too slow, and of course some folks won’t even bother waiting more than 5-10 seconds. I noticed right away that writing posts, uploading pictures, and just using the WordPress dashboard in general was much more responsive. So writing is less of a chore now, which means I won’t have a good reason not to write How I Moved to WP Engine I signed up for the service and registered my domain. I then took a full export of my ‘old’ site by doing a FTP GET of all my files, then did a MySQL database backup, exported my WordPress Theme settings to a .zip file, and then finally used the WordPress ‘Export’ feature. I then used the WordPress ‘Import’ on the new site to load up my posts. Then I uploaded the theme .zip package from Themify. Then I FTP’d the ‘wp-content’ directory up to my new server using SFTP (WP Engine only supports secure FTP – good on them!) Using a temporary URL to see my new site, I was able to confirm that everything looked mostly OK – I’ll detail the challenges and issues of fixing the content next – but then it was time to ‘flip the switch.’ I updated the IP address that the DNS lookup tables use to route traffic to my new server. In a matter of minutes the DNS servers around the world were updated and it was time to see the new site! But It Was ‘Broken’ I had never moved a website before, and in my rush to update the DNS, I had changed the records without really finding out what I was supposed to do first. After re-reading the directions provided by WP Engine and following the guidance of their support engineer, I realized I had needed to set the CNAME (Alias) ‘www’ record to point to a different URL than the ‘www.thatjeffsmith.com’ entry I had set. Once corrected the site was up and running in less than a minute. Then It Was Only Mostly Broken Many of my plugins weren’t working. Apparently just ftp’ing the wp-content directory up wasn’t the proper way to re-install the plugin. I suspect file permissions or file ownership wasn’t proper. Some plug-ins were working, many had their settings wiped to the defaults, and a few just didn’t work again. I had to delete the directory of the plug-in manually via SFTP, and then use the WP Dashboard to install it from scratch. And here was my first ‘lesson’ – don’t switch the DNS records until you’ve completely tested your new site. I wasn’t able to navigate the old WP console to review my plug-in settings. Thankfully I was able to use the Wayback Machine to reverse engineer some things, and of course most plug-ins aren’t that complicated to setup to begin with. An example of one that I had to redo from scratch is the ‘Twitter @Anywhere Plus’ plugin that I use to create the form that allows folks to tweet a post they enjoyed at the end of each story. How WP Engine ‘Hooked’ Me I actually signed up with another provider first. They ranked highly in Google searches and a few Tweeps recommended them to me. But hours after signing up and I still didn’t have sever reyady, I was ready to give up on them. They offered no chat or phone support – only mail and message boards. And the message boards were rife with posts about how the service had gone downhill in the past 6 months. To their credit, they did make it easy to cancel, although I did have to do so via email as their website ‘cancel’ button was non-existent. Within minutes of activating my WP Engine account I had received my welcome message and directions on how to get started. I was able to see my staged website right away. They also did something very cool before I even got started – they looked at my existing site and told me by how much they could improve its performance. The proof is in the web pudding. I like this for a few reasons, but primarily I liked their business model. It told me they knew what they were doing, and that they were willing to put their money where their mouth was. This was further evident by their 60-day money back guarantee. And if I understand it correctly, they don’t even take your money until after that 60 day period is over. After a day, I was welcomed by the WP Engine social media team, and was given the opportunity to subscribe to their newsletter and follow their account on Twitter. I noticed their Twitter team is sure to post regular WordPress tips several times a day. It’s not just an account that’s setup for the sake of having a Twitter presence. These little things add up and give me confidence in my decision to choose them as my hosting partner. ‘Partner’ – that’s a lot nicer word than just ‘service provider,’ isn’t it? Oh, and they offered me a t-shirt. Don’t ever doubt the power of a ‘free’ t-shirt! How awesome is this e-mail, from a customer perspective? I wasn’t really expecting any of this. Exceeding expectations before I have even handed over a single dollar seems like a pretty good business plan. This is how you treat customers. Love them to death, and they reward you with loyalty. But Jeff, You Skipped a Piece Here, Why WP Engine? I found them on one of those ‘Top 10′ list posts, and pulled up their webpage. I noticed they offered a specialized service – they host WordPress installs, and that’s it. Their servers are tuned specifically for running WordPress. They had in bolded text, things like ‘INSANELY FAST. INFINITELY SCALABLE.’ and ‘LIGHTNING SPEED.’ And then they offered insurance against hackers and they took care of automatic backups and restores. The only drawbacks I have noticed so far relate to plugins I used that have been ‘blacklisted.’ In order to guarantee that ‘lightning’ speed, they have banned the use of the CPU-suckiest plugins. One of those is the ‘Related Posts’ plugin. So if you are a subscriber and are reading this in your email, you’ll notice there’s no links back to my blog to continue reading other related stories. Since that referral traffic is very small single-digit for my site, I decided that I’m OK with that. I’d rather have the warp-speed page loads. Again, I think that will lead to higher traffic down the road. In 50+ days I will need to decide if WP Engine is a permanent solution. I’ll be sure to update this post when that time comes and let y’all know how it turns out.

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• More Animation - Self Dismissing Dialogs

  - by Duncan Mills

  In my earlier articles on animation, I discussed various slide, grow and  flip transitions for items and containers.  In this article I want to discuss a fade animation and specifically the use of fades and auto-dismissal for informational dialogs.  If you use a Mac, you may be familiar with Growl as a notification system, and the nice way that messages that are informational just fade out after a few seconds. So in this blog entry I wanted to discuss how we could make an ADF popup behave in the same way. This can be an effective way of communicating information to the user without "getting in the way" with modal alerts. This of course, has been done before, but everything I've seen previously requires something like JQuery to be in the mix when we don't really need it to be.  The solution I've put together is nice and generic and will work with either <af:panelWindow> or <af:dialog> as a the child of the popup. In terms of usage it's pretty simple to use we  just need to ensure that the popup itself has clientComponent is set to true and includes the animation JavaScript (animateFadingPopup) on a popupOpened event: <af:popup id="pop1" clientComponent="true">   <af:panelWindow title="A Fading Message...">    ...  </af:panelWindow>   <af:clientListener method="animateFadingPopup" type="popupOpened"/> </af:popup>   The popup can be invoked in the normal way using showPopupBehavior or JavaScript, no special code is required there. As a further twist you can include an additional clientAttribute called preFadeDelay to define a delay before the fade itself starts (the default is 5 seconds) . To set the delay to just 2 seconds for example: <af:popup ...>   ...   <af:clientAttribute name="preFadeDelay" value="2"/>   <af:clientListener method="animateFadingPopup" type="popupOpened"/>  </af:popup> The Animation Styles  As before, we have a couple of CSS Styles which define the animation, I've put these into the skin in my case, and, as in the other articles, I've only defined the transitions for WebKit browsers (Chrome, Safari) at the moment. In this case, the fade is timed at 5 seconds in duration. .popupFadeReset {   opacity: 1; } .popupFadeAnimate {   opacity: 0;   -webkit-transition: opacity 5s ease-in-out; } As you can see here, we are achieving the fade by simply setting the CSS opacity property. The JavaScript The final part of the puzzle is, of course, the JavaScript, there are four functions, these are generic (apart from the Style names which, if you've changed above, you'll need to reflect here): The initial function invoked from the popupOpened event,  animateFadingPopup which starts a timer and provides the initial delay before we start to fade the popup. The function that applies the fade animation to the popup - initiatePopupFade. The callback function - closeFadedPopup used to reset the style class and correctly hide the popup so that it can be invoked again and again.   A utility function - findFadeContainer, which is responsible for locating the correct child component of the popup to actually apply the style to. Function - animateFadingPopup This function, as stated is the one hooked up to the popupOpened event via a clientListener. Because of when the code is called it does not actually matter how you launch the popup, or if the popup is re-used from multiple places. All usages will get the fade behavior. /**  * Client listener which will kick off the animation to fade the dialog and register  * a callback to correctly reset the popup once the animation is complete  * @param event  */ function animateFadingPopup(event) { var fadePopup = event.getSource();   var fadeCandidate = false;   //Ensure that the popup is initially Opaque   //This handles the situation where the user has dismissed   //the popup whilst it was in the process of fading   var fadeContainer = findFadeContainer(fadePopup);   if (fadeContainer != null) {     fadeCandidate = true;     fadeContainer.setStyleClass("popupFadeReset");   }   //Only continue if we can actually fade this popup   if (fadeCandidate) {   //See if a delay has been specified     var waitTimeSeconds = event.getSource().getProperty('preFadeDelay');     //Default to 5 seconds if not supplied     if (waitTimeSeconds == undefined) {     waitTimeSeconds = 5;     }     // Now call the fade after the specified time     var fadeFunction = function () {     initiatePopupFade(fadePopup);     };     var fadeDelayTimer = setTimeout(fadeFunction, (waitTimeSeconds * 1000));   } } The things to note about this function is the initial check that we have to do to ensure that the container is currently visible and reset it's style to ensure that it is.  This is to handle the situation where the popup has begun the fade, and yet the user has still explicitly dismissed the popup before it's complete and in doing so has prevented the callback function (described later) from executing. In this particular situation the initial display of the dialog will be (apparently) missing it's normal animation but at least it becomes visible to the user (and most users will probably not notice this difference in any case). You'll notice that the style that we apply to reset the  opacity - popupFadeReset, is not applied to the popup component itself but rather the dialog or panelWindow within it. More about that in the description of the next function findFadeContainer(). Finally, assuming that we have a suitable candidate for fading, a JavaScript  timer is started using the specified preFadeDelay wait time (or 5 seconds if that was not supplied). When this timer expires then the main animation styleclass will be applied using the initiatePopupFade() function Function - findFadeContainer As a component, the <af:popup> does not support styleClass attribute, so we can't apply the animation style directly.  Instead we have to look for the container within the popup which defines the window object that can have a style attached.  This is achieved by the following code: /**  * The thing we actually fade will be the only child  * of the popup assuming that this is a dialog or window  * @param popup  * @return the component, or null if this is not valid for fading  */ function findFadeContainer(popup) { var children = popup.getDescendantComponents();   var fadeContainer = children[0];   if (fadeContainer != undefined) {   var compType = fadeContainer.getComponentType();     if (compType == "oracle.adf.RichPanelWindow" || compType == "oracle.adf.RichDialog") {     return fadeContainer;     }   }   return null; }  So what we do here is to grab the first child component of the popup and check its type. Here I decided to limit the fade behaviour to only <af:dialog> and <af:panelWindow>. This was deliberate.  If  we apply the fade to say an <af:noteWindow> you would see the text inside the balloon fade, but the balloon itself would hang around until the fade animation was over and then hide.  It would of course be possible to make the code smarter to walk up the DOM tree to find the correct <div> to apply the style to in order to hide the whole balloon, however, that means that this JavaScript would then need to have knowledge of the generated DOM structure, something which may change from release to release, and certainly something to avoid. So, all in all, I think that this is an OK restriction and frankly it's windows and dialogs that I wanted to fade anyway, not balloons and menus. You could of course extend this technique and handle the other types should you really want to. One thing to note here is the selection of the first (children[0]) child of the popup. It does not matter if there are non-visible children such as clientListener before the <af:dialog> or <af:panelWindow> within the popup, they are not included in this array, so picking the first element in this way seems to be fine, no matter what the underlying ordering is within the JSF source.  If you wanted a super-robust version of the code you might want to iterate through the children array of the popup to check for the right type, again it's up to you.  Function -  initiatePopupFade  On to the actual fading. This is actually very simple and at it's heart, just the application of the popupFadeAnimate style to the correct component and then registering a callback to execute once the fade is done. /**  * Function which will kick off the animation to fade the dialog and register  * a callback to correctly reset the popup once the animation is complete  * @param popup the popup we are animating  */ function initiatePopupFade(popup) { //Only continue if the popup has not already been dismissed    if (popup.isPopupVisible()) {   //The skin styles that define the animation      var fadeoutAnimationStyle = "popupFadeAnimate";     var fadeAnimationResetStyle = "popupFadeReset";     var fadeContainer = findFadeContainer(popup);     if (fadeContainer != null) {     var fadeContainerReal = AdfAgent.AGENT.getElementById(fadeContainer.getClientId());       //Define the callback this will correctly reset the popup once it's disappeared       var fadeCallbackFunction = function (event) {       closeFadedPopup(popup, fadeContainer, fadeAnimationResetStyle);         event.target.removeEventListener("webkitTransitionEnd", fadeCallbackFunction);       };       //Initiate the fade       fadeContainer.setStyleClass(fadeoutAnimationStyle);       //Register the callback to execute once fade is done       fadeContainerReal.addEventListener("webkitTransitionEnd", fadeCallbackFunction, false);     }   } } I've added some extra checks here though. First of all we only start the whole process if the popup is still visible. It may be that the user has closed the popup before the delay timer has finished so there is no need to start animating in that case. Again we use the findFadeContainer() function to locate the correct component to apply the style to, and additionally we grab the DOM id that represents that container.  This physical ID is required for the registration of the callback function. The closeFadedPopup() call is then registered on the callback so as to correctly close the now transparent (but still there) popup. Function -  closeFadedPopup The final function just cleans things up: /**  * Callback function to correctly cancel and reset the style in the popup  * @param popup id of the popup so we can close it properly  * @param contatiner the window / dialog within the popup to actually style  * @param resetStyle the syle that sets the opacity back to solid  */ function closeFadedPopup(popup, container, resetStyle) { container.setStyleClass(resetStyle);   popup.cancel(); }  First of all we reset the style to make the popup contents opaque again and then we cancel the popup.  This will ensure that any of your user code that is waiting for a popup cancelled event will actually get the event, additionally if you have done this as a modal window / dialog it will ensure that the glasspane is dismissed and you can interact with the UI again.  What's Next? There are several ways in which this technique could be used, I've been working on a popup here, but you could apply the same approach to in-line messages. As this code (in the popup case) is generic it will make s pretty nice declarative component and maybe, if I get time, I'll look at constructing a formal Growl component using a combination of this technique, and active data push. Also, I'm sure the above code can be improved a little too.  Specifically things like registering a popup cancelled listener to handle the style reset so that we don't loose the subtle animation that takes place when the popup is opened in that situation where the user has closed the in-fade dialog.

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• Using R to Analyze G1GC Log Files

  - by user12620111

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  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.

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• Apache2 benchmarks - very poor performance

  - by andrzejp

  I have two servers on which I test the configuration of apache2. The first server: 4GB of RAM, AMD Athlon (tm) 64 X2 Dual Core Processor 5600 + Apache 2.2.3, mod_php, mpm prefork: Settings: Timeout 100 KeepAlive On MaxKeepAliveRequests 150 KeepAliveTimeout 4 <IfModule Mpm_prefork_module> StartServers 7 MinSpareServers 15 MaxSpareServers 30 MaxClients 250 MaxRequestsPerChild 2000 </ IfModule> Compiled in modules: core.c mod_log_config.c mod_logio.c prefork.c http_core.c mod_so.c Second server: 8GB of RAM, Intel (R) Core (TM) i7 CPU [email protected] Apache 2.2.9, **fcgid, mpm worker, suexec** PHP scripts are running via fcgi-wrapper Settings: Timeout 100 KeepAlive On MaxKeepAliveRequests 100 KeepAliveTimeout 4 <IfModule Mpm_worker_module> StartServers 10 MaxClients 200 MinSpareThreads 25 MaxSpareThreads 75 ThreadsPerChild 25 MaxRequestsPerChild 1000 </ IfModule> Compiled in modules: core.c mod_log_config.c mod_logio.c worker.c http_core.c mod_so.c The following test results, which are very strange! New server (dynamic content - php via fcgid+suexec): Server Software: Apache/2.2.9 Server Hostname: XXXXXXXX Server Port: 80 Document Path: XXXXXXX Document Length: 179512 bytes Concurrency Level: 10 Time taken for tests: 0.26276 seconds Complete requests: 1000 Failed requests: 0 Total transferred: 179935000 bytes HTML transferred: 179512000 bytes Requests per second: 38.06 Transfer rate: 6847.88 kb/s received Connnection Times (ms) min avg max Connect: 2 4 54 Processing: 161 257 449 Total: 163 261 503 Old server (dynamic content - mod_php): Server Software: Apache/2.2.3 Server Hostname: XXXXXX Server Port: 80 Document Path: XXXXXX Document Length: 187537 bytes Concurrency Level: 10 Time taken for tests: 173.073 seconds Complete requests: 1000 Failed requests: 22 (Connect: 0, Length: 22, Exceptions: 0) Total transferred: 188003372 bytes HTML transferred: 187546372 bytes Requests per second: 5777.91 Transfer rate: 1086267.40 kb/s received Connnection Times (ms) min avg max Connect: 3 3 28 Processing: 298 1724 26615 Total: 301 1727 26643 Old server: Static content (jpg file) Server Software: Apache/2.2.3 Server Hostname: xxxxxxxxx Server Port: 80 Document Path: /images/top2.gif Document Length: 40486 bytes Concurrency Level: 100 Time taken for tests: 3.558 seconds Complete requests: 1000 Failed requests: 0 Write errors: 0 Total transferred: 40864400 bytes HTML transferred: 40557482 bytes Requests per second: 281.09 [#/sec] (mean) Time per request: 355.753 [ms] (mean) Time per request: 3.558 [ms] (mean, across all concurrent requests) Transfer rate: 11217.51 [Kbytes/sec] received Connection Times (ms) min mean[+/-sd] median max Connect: 3 11 4.5 12 23 Processing: 40 329 61.4 339 1009 Waiting: 6 282 55.2 293 737 Total: 43 340 63.0 351 1020 New server - static content (jpg file) Server Software: Apache/2.2.9 Server Hostname: XXXXX Server Port: 80 Document Path: /images/top2.gif Document Length: 40486 bytes Concurrency Level: 100 Time taken for tests: 3.571531 seconds Complete requests: 1000 Failed requests: 0 Write errors: 0 Total transferred: 41282792 bytes HTML transferred: 41030080 bytes Requests per second: 279.99 [#/sec] (mean) Time per request: 357.153 [ms] (mean) Time per request: 3.572 [ms] (mean, across all concurrent requests) Transfer rate: 11287.88 [Kbytes/sec] received Connection Times (ms) min mean[+/-sd] median max Connect: 2 63 24.8 66 119 Processing: 124 278 31.8 282 391 Waiting: 3 70 28.5 66 164 Total: 126 341 35.9 350 443 I noticed that in the apache error.log is a lot of entries: [notice] mod_fcgid: call /www/XXXXX/public_html/forum/index.php with wrapper /www/php-fcgi-scripts/XXXXXX/php-fcgi-starter What I have omitted, or do not understand? Such a difference in requests per second? Is it possible? What could be the cause?

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• Monitoring slow nginx/unicorn requests

  - by injekt

  I'm currently using Nginx to proxy requests to a Unicorn server running a Sinatra application. The application only has a couple of routes defined, those of which make fairly simple (non costly) queries to a PostgreSQL database, and finally return data in JSON format, these services are being monitored by God. I'm currently experiencing extremely slow response times from this application server. I have another two Unicorn servers being proxied via Nginx, and these are responding perfectly fine, so I think I can rule out any wrong doing from Nginx. Here is my God configuration: # God configuration APP_ROOT = File.expand_path '../', File.dirname(__FILE__) God.watch do |w| w.name = "app_name" w.interval = 30.seconds # default w.start = "cd #{APP_ROOT} && unicorn -c #{APP_ROOT}/config/unicorn.rb -D" # -QUIT = graceful shutdown, waits for workers to finish their current request before finishing w.stop = "kill -QUIT `cat #{APP_ROOT}/tmp/unicorn.pid`" w.restart = "kill -USR2 `cat #{APP_ROOT}/tmp/unicorn.pid`" w.start_grace = 10.seconds w.restart_grace = 10.seconds w.pid_file = "#{APP_ROOT}/tmp/unicorn.pid" # User under which to run the process w.uid = 'web' w.gid = 'web' # Cleanup the pid file (this is needed for processes running as a daemon) w.behavior(:clean_pid_file) # Conditions under which to start the process w.start_if do |start| start.condition(:process_running) do |c| c.interval = 5.seconds c.running = false end end # Conditions under which to restart the process w.restart_if do |restart| restart.condition(:memory_usage) do |c| c.above = 150.megabytes c.times = [3, 5] # 3 out of 5 intervals end restart.condition(:cpu_usage) do |c| c.above = 50.percent c.times = 5 end end w.lifecycle do |on| on.condition(:flapping) do |c| c.to_state = [:start, :restart] c.times = 5 c.within = 5.minute c.transition = :unmonitored c.retry_in = 10.minutes c.retry_times = 5 c.retry_within = 2.hours end end end Here is my Unicorn configuration: # Unicorn configuration file APP_ROOT = File.expand_path '../', File.dirname(__FILE__) worker_processes 8 preload_app true pid "#{APP_ROOT}/tmp/unicorn.pid" listen 8001 stderr_path "#{APP_ROOT}/log/unicorn.stderr.log" stdout_path "#{APP_ROOT}/log/unicorn.stdout.log" before_fork do |server, worker| old_pid = "#{APP_ROOT}/tmp/unicorn.pid.oldbin" if File.exists?(old_pid) && server.pid != old_pid begin Process.kill("QUIT", File.read(old_pid).to_i) rescue Errno::ENOENT, Errno::ESRCH # someone else did our job for us end end end I have checked God status logs but it appears CPU and Memory Usage are never out of bounds. I also have something to kill high memory workers, which can be found on the GitHub blog page here. When running a tail -f on the Unicorn logs I see some requests, but they're far and few between, when I was at around 60-100 a second before this trouble seemed to have arrived. This log also shows workers being reaped and started as expected. So my question is, how would I go about debugging this? What are the next steps I should be taking? I'm extremely baffled that the server will sometimes respond quickly, but at others time it's very slow, for long periods of time (which may or may not be peak traffic times). Any advice is much appreciated.

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• vagrant up command very slow on OS X Lion

  - by Andy Hume

  When I run vagrant up to provision a new VM on Lion it takes an extremely long time, during which the entire Mac is very laggy and unresponsive. The output is as follows, the key point being the "notice: Finished catalog run in 754.28 seconds" > vagrant up [default] Importing base box 'lucid64'... [default] The guest additions on this VM do not match the install version of VirtualBox! This may cause things such as forwarded ports, shared folders, and more to not work properly. If any of those things fail on this machine, please update the guest additions and repackage the box. Guest Additions Version: 4.1.0 VirtualBox Version: 4.1.6 [default] Matching MAC address for NAT networking... [default] Clearing any previously set forwarded ports... [default] Forwarding ports... [default] -- ssh: 22 => 2222 (adapter 1) [default] -- web: 80 => 4567 (adapter 1) [default] Creating shared folders metadata... [default] Running any VM customizations... [default] Booting VM... [default] Waiting for VM to boot. This can take a few minutes. [default] VM booted and ready for use! [default] Mounting shared folders... [default] -- v-root: /vagrant [default] -- v-data: /var/www [default] -- manifests: /tmp/vagrant-puppet/manifests [default] Running provisioner: Vagrant::Provisioners::Puppet... [default] Running Puppet with lucid64.pp... [default] stdin: is not a tty [default] notice: /Stage[main]/Lucid64/Exec[apt-update]/returns: executed successfully [default] [default] notice: /Stage[main]/Lucid64/Package[apache2]/ensure: ensure changed 'purged' to 'present' [default] [default] notice: /Stage[main]/Lucid64/File[/etc/motd]/ensure: defined content as '{md5}a25e31ba9b8489da9cd5751c447a1741' [default] [default] notice: Finished catalog run in 754.28 seconds [default] [default] err: /File[/var/lib/puppet/rrd]/ensure: change from absent to directory failed: Could not find group puppet [default] [default] err: Could not send report: Got 1 failure(s) while initializing: change from absent to directory failed: Could not find group puppet [default] [default] Running provisioner: Vagrant::Provisioners::Puppet... [default] Running Puppet with lucid64.pp... [default] stdin: is not a tty [default] notice: /Stage[main]/Lucid64/Exec[apt-update]/returns: executed successfully [default] [default] notice: Finished catalog run in 2.05 seconds [default] [default] err: /File[/var/lib/puppet/rrd]: Could not evaluate: Could not find group puppet [default] [default] err: Could not send report: Got 1 failure(s) while initializing: Could not evaluate: Could not find group puppet [default] [default] Running provisioner: Vagrant::Provisioners::Puppet... [default] Running Puppet with lucid64.pp... [default] stdin: is not a tty [default] notice: /Stage[main]/Lucid64/Exec[apt-update]/returns: executed successfully [default] [default] notice: Finished catalog run in 1.36 seconds [default] [default] err: /File[/var/lib/puppet/rrd]: Could not evaluate: Could not find group puppet [default] [default] err: Could not send report: Got 1 failure(s) while initializing: Could not evaluate: Could not find group puppet [default] >

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