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  • Antlr Lexer Quoted String Predicate

    - by Loki
    I'm trying to build a lexer to tokenize lone words and quoted strings. I got the following: STRING: QUOTE (options {greedy=false;} : . )* QUOTE ; WS : SPACE+ { $channel = HIDDEN; } ; WORD : ~(QUOTE|SPACE)+ ; For the corner cases, it needs to parse: "string" word1" word2 As three tokens: "string" as STRING and word1" and word2 as WORD. Basically, if there is a last quote, it needs to be part of the WORD were it is. If the quote is surrounded by white spaces, it should be a WORD. I tried this rule for WORD, without success: WORD: ~(QUOTE|SPACE)+ | (~(QUOTE|SPACE)* QUOTE ~QUOTE*)=> ~(QUOTE|SPACE)* QUOTE ~(QUOTE|SPACE)* ;

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  • Blu-ray BD-R: Would you physically store it in a CaseLogic Wallet pocket?

    - by Rob
    I keep several backup copies of my material and files. For my DVDs, one set of copies is kept in a CaseLogic wallet folder pack, so that I can easily move this around when visiting friends, family or for business. This is highly convenient. The other sets are kept in their jewel cases in hard plastic see thru storage boxes. Although CaseLogic wallet material is designed to be abrasion free, their caveat is that external dust will be the cause of any blemishes. If hard dust gets in these pockets, which is inevitable, this will occasionally cause light hair like scratches on the disc surface as the discs are removed and returned for access to their contents. This is of no consequence as the laser and error correction can more than cope with this. I'm aware that the blu-ray spec requires anti-scratch in disc surfaces but was wondering that, given the smaller pits, would dust and light scratches from wallet storage cause more problems with blu-rays than they would with DVDs? I'm using Blu-ray BD-R and BD-R DL write once media.

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  • concurrency::index<N> from amp.h

    - by Daniel Moth
    Overview C++ AMP introduces a new template class index<N>, where N can be any value greater than zero, that represents a unique point in N-dimensional space, e.g. if N=2 then an index<2> object represents a point in 2-dimensional space. This class is essentially a coordinate vector of N integers representing a position in space relative to the origin of that space. It is ordered from most-significant to least-significant (so, if the 2-dimensional space is rows and columns, the first component represents the rows). The underlying type is a signed 32-bit integer, and component values can be negative. The rank field returns N. Creating an index The default parameterless constructor returns an index with each dimension set to zero, e.g. index<3> idx; //represents point (0,0,0) An index can also be created from another index through the copy constructor or assignment, e.g. index<3> idx2(idx); //or index<3> idx2 = idx; To create an index representing something other than 0, you call its constructor as per the following 4-dimensional example: int temp[4] = {2,4,-2,0}; index<4> idx(temp); Note that there are convenience constructors (that don’t require an array argument) for creating index objects of rank 1, 2, and 3, since those are the most common dimensions used, e.g. index<1> idx(3); index<2> idx(3, 6); index<3> idx(3, 6, 12); Accessing the component values You can access each component using the familiar subscript operator, e.g. One-dimensional example: index<1> idx(4); int i = idx[0]; // i=4 Two-dimensional example: index<2> idx(4,5); int i = idx[0]; // i=4 int j = idx[1]; // j=5 Three-dimensional example: index<3> idx(4,5,6); int i = idx[0]; // i=4 int j = idx[1]; // j=5 int k = idx[2]; // k=6 Basic operations Once you have your multi-dimensional point represented in the index, you can now treat it as a single entity, including performing common operations between it and an integer (through operator overloading): -- (pre- and post- decrement), ++ (pre- and post- increment), %=, *=, /=, +=, -=,%, *, /, +, -. There are also operator overloads for operations between index objects, i.e. ==, !=, +=, -=, +, –. Here is an example (where no assertions are broken): index<2> idx_a; index<2> idx_b(0, 0); index<2> idx_c(6, 9); _ASSERT(idx_a.rank == 2); _ASSERT(idx_a == idx_b); _ASSERT(idx_a != idx_c); idx_a += 5; idx_a[1] += 3; idx_a++; _ASSERT(idx_a != idx_b); _ASSERT(idx_a == idx_c); idx_b = idx_b + 10; idx_b -= index<2>(4, 1); _ASSERT(idx_a == idx_b); Usage You'll most commonly use index<N> objects to index into data types that we'll cover in future posts (namely array and array_view). Also when we look at the new parallel_for_each function we'll see that an index<N> object is the single parameter to the lambda, representing the (multi-dimensional) thread index… In the next post we'll go beyond being able to represent an N-dimensional point in space, and we'll see how to define the N-dimensional space itself through the extent<N> class. Comments about this post by Daniel Moth welcome at the original blog.

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  • Why can't I reclaim my dynamically allocated memory using the "delete" keyword?

    - by synaptik
    I have the following class: class Patient { public: Patient(int x); ~Patient(); private: int* RP; }; Patient::Patient(int x) { RP = new int [x]; } Patient::~Patient() { delete [] RP; } I create an instance of this class on the stack as follows: void f() { Patient p(10); } Now, when f() returns, I get a "double free or corruption" error, which signals to me that something is attempted to be deleted more than once. But I don't understand why that would be so. The space for the array is created on the heap, and just because the function from inside which the space was allocated returns, I wouldn't expect the space to be reclaimed. I thought that if I allocate space on the heap (using the new keyword), then the only way to reclaim that space is to use the delete keyword. Help! :)

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  • Preserve trailing whitespace Sybase

    - by AngryWhenHungry
    I have a big chunk of textual data which I split and write multiple rows of a varchar(255) column of a table. Sometimes, the last character happens to be a space. When I read back this row, the trailing space is chopped and I get only 254 characters. This messes up my data when I append the next row to the end of this one. My code sends the full 255 char (incl space) to the DB API. How can I check that the trailing space is actually written to the table? I am not in a position to rewrite/redesign legacy code. Is there any setting - either in the DB, DB interface, read/write calls etc - that I can use to preserve the trailing space?

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  • What's your opinion in Amazon S3 ?

    - by Space Cracker
    i searching for best online file storage and i found a lot with different features ... i feel that Amazon S3 is the best ... Could any who try such a service give me his opinion on it and if is there any others that are most valuable Amazon S3 ?

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  • How can I make the Outlook "To" field allow auto completion for all my contacts?

    - by Space Cracker
    When we make a new mail message in Outlook 2007 and try to write any letter in To field it shows an auto complete list with all available contacts that contain written letters. This list is displaying all emails that you have send to them before and over time this list grows as you send to more and more new contacts... My Issues: When we reinstall Windows, install new copy of Outlook, create a new mail message, try to write any character in To field it will not show any contacts and this leads to write it or choose from contacts. Is it in any way possible to make Outlook's contacts, or specific contacts I determine to be cached, appear in TO when I write any letter without need to write them again?

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  • How i can make Outlook To field to allow auto complete for all my contacts ?

    - by Space Cracker
    When we make new mail message in outlook 2007 and try to write any letter in To field it show auto complete list with all available contacts that contain written letters. This list is appear with all emails that u send to them before and over time this list be more and more with new contacts you send to ... My Issues : When we reinstall windows ,install new copy of outlook,create new mail message ,try yo write any character in To field it will not show any contacts and this lead to write it or choose from contacts ... Is it any way to make outlook add my contacts or specific contacts I determined to be cached and appear in TOwhen i write any letter without need to write them again ?

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  • Why does IIS 7 return a 500 when I access an HTML page?

    - by Out Into Space
    IIS 7 returns a 500 server error when I request an HTML page with this structure: <html> <head> <title>Test Page</title> </head> <body> Some text </body> </html> It works just fine the first time I access it, but subsequent attempts cause the error. If I remove the HTML tags, the error doesn't occur: <body> Some text </body> It seems very odd that the presence of the HTML tag would cause it to blow up. Any ideas?

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  • Essbase BSO Data Fragmentation

    - by Ann Donahue
    Essbase BSO Data Fragmentation Data fragmentation naturally occurs in Essbase Block Storage (BSO) databases where there are a lot of end user data updates, incremental data loads, many lock and send, and/or many calculations executed.  If an Essbase database starts to experience performance slow-downs, this is an indication that there may be too much fragmentation.  See Chapter 54 Improving Essbase Performance in the Essbase DBA Guide for more details on measuring and eliminating fragmentation: http://docs.oracle.com/cd/E17236_01/epm.1112/esb_dbag/daprcset.html Fragmentation is likely to occur in the following situations: Read/write databases that users are constantly updating data Databases that execute calculations around the clock Databases that frequently update and recalculate dense members Data loads that are poorly designed Databases that contain a significant number of Dynamic Calc and Store members Databases that use an isolation level of uncommitted access with commit block set to zero There are two types of data block fragmentation Free space tracking, which is measured using the Average Fragmentation Quotient statistic. Block order on disk, which is measured using the Average Cluster Ratio statistic. Average Fragmentation Quotient The Average Fragmentation Quotient ratio measures free space in a given database.  As you update and calculate data, empty spaces occur when a block can no longer fit in its original space and will either append at the end of the file or fit in another empty space that is large enough.  These empty spaces take up space in the .PAG files.  The higher the number the more empty spaces you have, therefore, the bigger the .PAG file and the longer it takes to traverse through the .PAG file to get to a particular record.  An Average Fragmentation Quotient value of 3.174765 means the database is 3% fragmented with free space. Average Cluster Ratio Average Cluster Ratio describes the order the blocks actually exist in the database. An Average Cluster Ratio number of 1 means all the blocks are ordered in the correct sequence in the order of the Outline.  As you load data and calculate data blocks, the sequence can start to be out of order.  This is because when you write to a block it may not be able to place back in the exact same spot in the database that it existed before.  The lower this number the more out of order it becomes and the more it affects performance.  An Average Cluster Ratio value of 1 means no fragmentation.  Any value lower than 1 i.e. 0.01032828 means the data blocks are getting further out of order from the outline order. Eliminating Data Block Fragmentation Both types of data block fragmentation can be removed by doing a dense restructure or export/clear/import of the data.  There are two types of dense restructure: 1. Implicit Restructures Implicit dense restructure happens when outline changes are done using EAS Outline Editor or Dimension Build. Essbase restructures create new .PAG files restructuring the data blocks in the .PAG files. When Essbase restructures the data blocks, it regenerates the index automatically so that index entries point to the new data blocks. Empty blocks are NOT removed with implicit restructures. 2. Explicit Restructures Explicit dense restructure happens when a manual initiation of the database restructure is executed. An explicit dense restructure is a full restructure which comprises of a dense restructure as outlined above plus the removal of empty blocks Empty Blocks vs. Fragmentation The existence of empty blocks is not considered fragmentation.  Empty blocks can be created through calc scripts or formulas.  An empty block will add to an existing database block count and will be included in the block counts of the database properties.  There are no statistics for empty blocks.  The only way to determine if empty blocks exist in an Essbase database is to record your current block count, export the entire database, clear the database then import the exported data.  If the block count decreased, the difference is the number of empty blocks that had existed in the database.

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  • iPhone SDK vs Windows Phone 7 Series SDK Challenge, Part 1: Hello World!

    In this series, I will be taking sample applications from the iPhone SDK and implementing them on Windows Phone 7 Series.  My goal is to do as much of an apples-to-apples comparison as I can.  This series will be written to not only compare and contrast how easy or difficult it is to complete tasks on either platform, how many lines of code, etc., but Id also like it to be a way for iPhone developers to either get started on Windows Phone 7 Series development, or for developers in general to learn the platform. Heres my methodology: Run the iPhone SDK app in the iPhone Simulator to get a feel for what it does and how it works, without looking at the implementation Implement the equivalent functionality on Windows Phone 7 Series using Silverlight. Compare the two implementations based on complexity, functionality, lines of code, number of files, etc. Add some functionality to the Windows Phone 7 Series app that shows off a way to make the scenario more interesting or leverages an aspect of the platform, or uses a better design pattern to implement the functionality. You can download Microsoft Visual Studio 2010 Express for Windows Phone CTP here, and the Expression Blend 4 Beta here. Hello World! Of course no first post would be allowed if it didnt focus on the hello world scenario.  The iPhone SDK follows that tradition with the Your First iPhone Application walkthrough.  I will say that the developer documentation for iPhone is pretty good.  There are plenty of walkthoughs and they break things down into nicely sized steps and do a good job of bringing the user along.  As expected, this application is quite simple.  It comprises of a text box, a label, and a button.  When you push the button, the label changes to Hello plus the  word you typed into the text box.  Makes perfect sense for a starter application.  Theres not much to this but it covers a few basic elements: Laying out basic UI Handling user input Hooking up events Formatting text     So, lets get started building a similar app for Windows Phone 7 Series! Implementing the UI: UI in Silverlight (and therefore Windows Phone 7) is defined in XAML, which is a declarative XML language also used by WPF on the desktop.  For anyone thats familiar with similar types of markup, its relatively straightforward to learn, but has a lot of power in it once you get it figured out.  Well talk more about that. This UI is very simple.  When I look at this, I note a couple of things: Elements are arranged vertically They are all centered So, lets create our Application and then start with the UI.  Once you have the the VS 2010 Express for Windows Phone tool running, create a new Windows Phone Project, and call it Hello World: Once created, youll see the designer on one side and your XAML on the other: Now, we can create our UI in one of three ways: Use the designer in Visual Studio to drag and drop the components Use the designer in Expression Blend 4 to drag and drop the components Enter the XAML by hand in either of the above Well start with (1), then kind of move to (3) just for instructional value. To develop this UI in the designer: First, delete all of the markup between inside of the Grid element (LayoutRoot).  You should be left with just this XAML for your MainPage.xaml (i shortened all the xmlns declarations below for brevity): 1: <phoneNavigation:PhoneApplicationPage 2: x:Class="HelloWorld.MainPage" 3: xmlns="...[snip]" 4: FontFamily="{StaticResource PhoneFontFamilyNormal}" 5: FontSize="{StaticResource PhoneFontSizeNormal}" 6: Foreground="{StaticResource PhoneForegroundBrush}"> 7:   8: <Grid x:Name="LayoutRoot" Background="{StaticResource PhoneBackgroundBrush}"> 9:   10: </Grid> 11:   12: </phoneNavigation:PhoneApplicationPage> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; }   Well be adding XAML at line 9, so thats the important part. Now, Click on the center area of the phone surface Open the Toolbox and double click StackPanel Double click TextBox Double click TextBlock Double click Button That will create the necessary UI elements but they wont be arranged quite right.  Well fix it in a second.    Heres the XAML that we end up with: 1: <StackPanel Height="100" HorizontalAlignment="Left" Margin="10,10,0,0" Name="stackPanel1" VerticalAlignment="Top" Width="200"> 2: <TextBox Height="32" Name="textBox1" Text="TextBox" Width="100" /> 3: <TextBlock Height="23" Name="textBlock1" Text="TextBlock" /> 4: <Button Content="Button" Height="70" Name="button1" Width="160" /> 5: </StackPanel> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } The designer does its best at guessing what we want, but in this case we want things to be a bit simpler. So well just clean it up a bit.  We want the items to be centered and we want them to have a little bit of a margin on either side, so heres what we end up with.  Ive also made it match the values and style from the iPhone app: 1: <StackPanel Margin="10"> 2: <TextBox Name="textBox1" HorizontalAlignment="Stretch" Text="You" TextAlignment="Center"/> 3: <TextBlock Name="textBlock1" HorizontalAlignment="Center" Margin="0,100,0,0" Text="Hello You!" /> 4: <Button Name="button1" HorizontalAlignment="Center" Margin="0,150,0,0" Content="Hello"/> 5: </StackPanel> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Now lets take a look at what weve done there. Line 1: We removed all of the formatting from the StackPanel, except for Margin, as thats all we need.  Since our parent element is a Grid, by default the StackPanel will be sized to fit in that space.  The Margin says that we want to reserve 10 pixels on each side of the StackPanel. Line 2: Weve set the HorizontalAlignment of the TextBox to Stretch, which says that it should fill its parents size horizontally.  We want to do this so the TextBox is always full-width.  We also set TextAlignment to Center, to center the text. Line 3: In contrast to the TextBox above, we dont care how wide the TextBlock is, just so long as it is big enough for its text.  Thatll happen automatically, so we just set its Horizontal alignment to Center.  We also set a Margin above the TextBlock of 100 pixels to bump it down a bit, per the iPhone UI. Line 4: We do the same things here as in Line 3. Heres how the UI looks in the designer: Believe it or not, were almost done! Implementing the App Logic Now, we want the TextBlock to change its text when the Button is clicked.  In the designer, double click the Button to be taken to the Event Handler for the Buttons Click event.  In that event handler, we take the Text property from the TextBox, and format it into a string, then set it into the TextBlock.  Thats it! 1: private void button1_Click(object sender, RoutedEventArgs e) 2: { 3: string name = textBox1.Text; 4:   5: // if there isn't a name set, just use "World" 6: if (String.IsNullOrEmpty(name)) 7: { 8: name = "World"; 9: } 10:   11: // set the value into the TextBlock 12: textBlock1.Text = String.Format("Hello {0}!", name); 13:   14: } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } We use the String.Format() method to handle the formatting for us.    Now all thats left is to test the app in the Windows Phone Emulator and verify it does what we think it does! And it does! Comparing against the iPhone Looking at the iPhone example, there are basically three things that you have to touch as the developer: 1) The UI in the Nib file 2) The app delegate 3) The view controller Counting lines is a bit tricky here, but to try to keep this even, Im going to only count lines of code that I could not have (or would not have) generated with the tooling.  Meaning, Im not counting XAML and Im not counting operations that happen in the Nib file with the XCode designer tool.  So in the case of the above, even though I modified the XAML, I could have done all of those operations using the visual designer tool.  And normally I would have, but the XAML is more instructive (and less steps!).  Im interested in things that I, as the developer have to figure out in code.  Im also not counting lines that just have a curly brace on them, or lines that are generated for me (e.g. method names that are generated for me when I make a connection, etc.) So, by that count, heres what I get from the code listing for the iPhone app found here: HelloWorldAppDelegate.h: 6 HelloWorldAppDelegate.m: 12 MyViewController.h: 8 MyViewController.m: 18 Which gives me a grand total of about 44 lines of code on iPhone.  I really do recommend looking at the iPhone code for a comparison to the above. Now, for the Windows Phone 7 Series application, the only code I typed was in the event handler above Main.Xaml.cs: 4 So a total of 4 lines of code on Windows Phone 7.  And more importantly, the process is just A LOT simpler.  For example, I was surprised that the User Interface Designer in XCode doesnt automatically create instance variables for me and wire them up to the corresponding elements.  I assumed I wouldnt have to write this code myself (and risk getting it wrong!).  I dont need to worry about view controllers or anything.  I just write my code.  This blog post up to this point has covered almost every aspect of this apps development in a few pages.  The iPhone tutorial has 5 top level steps with 2-3 sub sections of each. Now, its worth pointing out that the iPhone development model uses the Model View Controller (MVC) pattern, which is a very flexible and powerful pattern that enforces proper separation of concerns.  But its fairly complex and difficult to understand when you first walk up to it.  Here at Microsoft weve dabbled in MVC a bit, with frameworks like MFC on Visual C++ and with the ASP.NET MVC framework now.  Both are very powerful frameworks.  But one of the reasons weve stayed away from MVC with client UI frameworks is that its difficult to tool.  We havent seen the type of value that beats double click, write code! for the broad set of scenarios. Another thing to think about is how many of those lines of code were focused on my apps functionality?.  Or, the converse of How many lines of code were boilerplate plumbing?  In both examples, the actual number of functional code lines is similar.  I count most of them in MyViewController.m, in the changeGreeting method.  Its about 7 lines of code that do the work of taking the value from the TextBox and putting it into the label.  Versus 4 on the Windows Phone 7 side.  But, unfortunately, on iPhone I still have to write that other 37 lines of code, just to get there. 10% of the code, 1 file instead of 4, its just much simpler. Making Some Tweaks It turns out, I can actually do this application with ZERO  lines of code, if Im willing to change the spec a bit. The data binding functionality in Silverlight is incredibly powerful.  And what I can do is databind the TextBoxs value directly to the TextBlock.  Take some time looking at this XAML below.  Youll see that I have added another nested StackPanel and two more TextBlocks.  Why?  Because thats how I build that string, and the nested StackPanel will lay things out Horizontally for me, as specified by the Orientation property. 1: <StackPanel Margin="10"> 2: <TextBox Name="textBox1" HorizontalAlignment="Stretch" Text="You" TextAlignment="Center"/> 3: <StackPanel Orientation="Horizontal" HorizontalAlignment="Center" Margin="0,100,0,0" > 4: <TextBlock Text="Hello " /> 5: <TextBlock Name="textBlock1" Text="{Binding ElementName=textBox1, Path=Text}" /> 6: <TextBlock Text="!" /> 7: </StackPanel> 8: <Button Name="button1" HorizontalAlignment="Center" Margin="0,150,0,0" Content="Hello" Click="button1_Click" /> 9: </StackPanel> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Now, the real action is there in the bolded TextBlock.Text property: Text="{Binding ElementName=textBox1, Path=Text}" .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } That does all the heavy lifting.  It sets up a databinding between the TextBox.Text property on textBox1 and the TextBlock.Text property on textBlock1. As I change the text of the TextBox, the label updates automatically. In fact, I dont even need the button any more, so I could get rid of that altogether.  And no button means no event handler.  No event handler means no C# code at all.  Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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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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  • how to fix: ctags null expansion of name pattern "\1"

    - by bua
    Hi, As the title points I have problem with ctags when trying to parse user-defined language. Basically I've followed those instructions. The quickest and easiest way to do this is by defining a new language using the program options. In order to have Swine support available every time I start ctags, I will place the following lines into the file $HOME/.ctags, which is read in every time ctags starts: --langdef=swine --langmap=swine:.swn --regex-swine=/^def[ \t]*([a-zA-Z0-9_]+)/\1/d,definition/ The first line defines the new language, the second maps a file extension to it, and the third defines a regular expression to identify a language definition and generate a tag file entry for it. I've tried different flags: b,e for regex. My definition of tag is: --regex-q=/^[ \t]*[^[:space:]]*[:space:]*:[:space:]*{/\l/f,function/b When I replace \1 with anything else (ascii caracter set ), It works. the output is: (--regex-q=/^[ \t]*[^[:space:]]*[:space:]*:[:space:]*{/my function name/f,function/b) !_TAG_FILE_FORMAT 2 /extended format; --format=1 will not append ;" to lines/ !_TAG_FILE_SORTED 1 /0=unsorted, 1=sorted, 2=foldcase/ !_TAG_PROGRAM_AUTHOR Darren Hiebert /[email protected]/ !_TAG_PROGRAM_NAME Exuberant Ctags // !_TAG_PROGRAM_URL http://ctags.sourceforge.net /official site/ !_TAG_PROGRAM_VERSION 5.8 // my function name file.q /^.ras.getLocation:{[u]$/;" f my function name file.q /^.a.getResource:{[u; pass]$/;" f my function name file.q /^.a.init:{$/;" f my function name file.q /^.a.kill:{[u; force]$/;" f my function name file.q /^.asdf.status:{[what; u]$/;" f my function name file.q /^.pc:{$/;" f Why \1 doesn't work? (I've tried all 1-9)

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  • GC output clarification

    - by elec
    I'm running a java application with the following settings: -XX:+CMSParallelRemarkEnabled -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintHeapAtGC -XX:+PrintTenuringDistribution I'm not sure how to interpret the related gc logs(below). In particular: Heap after GC invocations=31 (full 3): does this mean there were 31 minor GCs, and 3 full GCs ? What triggers the several consecutive lines of Total time for which the application threads were stopped and Application Time ? Is it possible to get the time stamps associated with each of these lines ? GC logs: Total time for which application threads were stopped: 0.0046910 seconds Application time: 0.7946670 seconds Total time for which application threads were stopped: 0.0002900 seconds Application time: 1.0153640 seconds Total time for which application threads were stopped: 0.0002780 seconds Application time: 1.0161890 seconds Total time for which application threads were stopped: 0.0002760 seconds Application time: 1.0145990 seconds Total time for which application threads were stopped: 0.0002950 seconds Application time: 0.9999800 seconds Total time for which application threads were stopped: 0.0002770 seconds Application time: 1.0151640 seconds Total time for which application threads were stopped: 0.0002730 seconds Application time: 0.9996590 seconds Total time for which application threads were stopped: 0.0002880 seconds Application time: 0.9624290 seconds {Heap before GC invocations=30 (full 3): par new generation total 131008K, used 130944K [0x00000000eac00000, 0x00000000f2c00000, 0x00000000f2c00000) eden space 130944K, 100% used [0x00000000eac00000, 0x00000000f2be0000, 0x00000000f2be0000) from space 64K, 0% used [0x00000000f2bf0000, 0x00000000f2bf0000, 0x00000000f2c00000) to space 64K, 0% used [0x00000000f2be0000, 0x00000000f2be0000, 0x00000000f2bf0000) concurrent mark-sweep generation total 131072K, used 48348K [0x00000000f2c00000, 0x00000000fac00000, 0x00000000fac00000) concurrent-mark-sweep perm gen total 30000K, used 19518K [0x00000000fac00000, 0x00000000fc94c000, 0x0000000100000000) 2010-05-11T09:30:13.888+0100: 384.955: [GC 384.955: [ParNew Desired survivor size 32768 bytes, new threshold 0 (max 0) : 130944K-0K(131008K), 0.0052470 secs] 179292K-48549K(262080K), 0.0053030 secs] [Times: user=0.00 sys=0.00, real=0.01 secs] Heap after GC invocations=31 (full 3): par new generation total 131008K, used 0K [0x00000000eac00000, 0x00000000f2c00000, 0x00000000f2c00000) eden space 130944K, 0% used [0x00000000eac00000, 0x00000000eac00000, 0x00000000f2be0000) from space 64K, 0% used [0x00000000f2be0000, 0x00000000f2be0000, 0x00000000f2bf0000) to space 64K, 0% used [0x00000000f2bf0000, 0x00000000f2bf0000, 0x00000000f2c00000) concurrent mark-sweep generation total 131072K, used 48549K [0x00000000f2c00000, 0x00000000fac00000, 0x00000000fac00000) concurrent-mark-sweep perm gen total 30000K, used 19518K [0x00000000fac00000, 0x00000000fc94c000, 0x0000000100000000) } Total time for which application threads were stopped: 0.0056410 seconds Application time: 0.0475220 seconds Total time for which application threads were stopped: 0.0001800 seconds Application time: 1.0174830 seconds Total time for which application threads were stopped: 0.0003820 seconds Application time: 1.0126350 seconds Total time for which application threads were stopped: 0.0002750 seconds Application time: 1.0155910 seconds Total time for which application threads were stopped: 0.0002680 seconds Application time: 1.0155580 seconds Total time for which application threads were stopped: 0.0002880 seconds Application time: 1.0155480 seconds Total time for which application threads were stopped: 0.0002970 seconds Application time: 0.9896810 seconds

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