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  • Is MD5 really that bad?

    - by Col. Shrapnel
    Everyone says that MD5 is "broken". Though I have never seen a code that can show it's weakness. So, I hope someone of local experts can prove it with simple test. I have an MD5 hash c1e877411f5cb44d10ece283a37e1668 And a simple code to produce it $salt="#bh35^&Res%"; $pass="***"; echo $hash=md5($salt.$pass); So, the question is: 1. Is MD% really that bad? 2. If so, what's the pass behind the asterisks?

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  • Simple matrix example using C++ template class

    - by skyeagle
    I am trying to write a trivial Matrix class, using C++ templates in an attempt to brush up my C++, and also to explain something to a fellow coder. This is what I have som far: template class<T> class Matrix { public: Matrix(const unsigned int rows, const unsigned int cols); Matrix(const Matrix& m); Matrix& operator=(const Matrix& m); ~Matrix(); unsigned int getNumRows() const; unsigned int getNumCols() const; template <class T> T getCellValue(unsigned int row, unsigned col) const; template <class T> void setCellValue(unsigned int row, unsigned col, T value) const; private: // Note: intentionally NOT using smart pointers here ... T * m_values; }; template<class T> inline T Matrix::getCellValue(unsigned int row, unsigned col) const { } template<class T> inline void Matrix::setCellValue(unsigned int row, unsigned col, T value) { } I'm stuck on the ctor, since I need to allocate a new[] T, it seems like it needs to be a template method - however, I'm not sure I have come accross a templated ctor before. How can I implemnt the ctor?

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  • Basic FreeMat/MATLAB syntax - dimension error

    - by 0x90
    I am using FreeMat, and I have an RGB picture which is a 3D matrix contains the columns and rows of the pictures and the RGB values for each pixel. Since there is not an intrinsic function to convert RGB picture to YIQ, I have implement one. I came up with this code: Assume I have a 3D array, image_rgb: matrix = [0.299 0.587 0.114; 0.596 -0.274 -0.322; 0.211 -0.523 0.312]; row = 1:length(image_rgb(:,1,1)); col = 1:length(image_rgb(1,:,1)); p = image_rgb(row,col,:); %Here I have the problem mage_yiq(row,col,:) = matrix*image_rgb(row,col,:); max_y = max (max(image_yiq(:,:,1))); max_i = max (max(image_yiq(:,:,2))); max_q = max (max(image_yiq(:,:,3))); %Renormalize the image again after the multipication % to [0,1]. image_yiq(:,:,1) = image_yiq(:,:,1)/max_y; image_yiq(:,:,2) = image_yiq(:,:,2)/max_i; image_yiq(:,:,3) = image_yiq(:,:,3)/max_q; I can't understand why the matrix multiplication fails. I want the code to be nice and not just to, multiply the matrix by hand...

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  • CSS Zebra Stripe a Specific Table tr:nth-child(even)

    - by BillR
    I want to zebra stripe only select tables using. I do not want to use jQuery for this. tbody tr:nth-child(even) td, tbody tr.even td {background:#e5ecf9;} When I put that in a css file it affects all tables on all pages that call the same stylesheet. What I would like to do is selectively apply it to specific tables. I have tried this, but it doesn't work. // in stylesheet .zebra_stripe{ tbody tr:nth-child(even) td, tbody tr.even td {background:#e5ecf9;} } // in html <table class="zebra_even"> <colgroup> <col class="width_10em" /> <col class="width_15em" /> </colgroup> <tr> <td>Odd row nice and clear.</td> <td>Some Stuff</td> </tr> <tr> <td>Even row nice and clear but it should be shaded.</td> <td>Some Stuff</td> </tr> </table> And this: <table> <colgroup> <col class="width_10em" /> <col class="width_15em" /> </colgroup> <tbody class="zebra_even"> The stylesheet works as it is properly formatting other elements of the html. Can someone help me with an answer to this problem? Thanks.

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  • why doesnt this program print?

    - by Alex
    What I'm trying to do is to print my two-dimensional array but i'm lost. The first function is running perfect, the problem is the second or maybe the way I'm passing it to the "Print" function. #include <stdio.h> #include <stdlib.h> #define ROW 2 #define COL 2 //Memory allocation and values input void func(int **arr) { int i, j; arr = (int**)calloc(ROW,sizeof(int*)); for(i=0; i < ROW; i++) arr[i] = (int*)calloc(COL,sizeof(int)); printf("Input: \n"); for(i=0; i<ROW; i++) for(j=0; j<COL; j++) scanf_s("%d", &arr[i][j]); } //This is where the problem begins or maybe it's in the main void print(int **arr) { int i, j; for(i=0; i<ROW; i++) { for(j=0; j<COL; j++) printf("%5d", arr[i][j]); printf("\n"); } } void main() { int *arr; func(&arr); print(&arr); //maybe I'm not passing the arr right ? }

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  • mcsCustomscrollbar append new content not working

    - by Dariel Pratama
    i have this script in my website. $(document).ready(function(){ var comment = $('textarea[name=comment_text]').val(); var vid = $('input[name=video_id]').val(); $('#add_comment').on('click', function(){ $.post('<?php echo site_url('comment/addcomments'); ?>', $('#comment-form').serialize(), function(data){ data = JSON.parse(data); if(data.userdata){ var date = new Date(data.userdata.comment_create_time * 1000); var picture = data.userdata.user_image.length > 0 ? 'fileupload/'+data.userdata.user_image:'images/no_pic.gif'; var newComment = '<div class="row">\ <div class="col-md-4">\ <img src="<?php echo base_url(); ?>'+picture+'" class="profile-pic margin-top-15" />\ </div>\ <div class="col-md-8 no-pade">\ <p id="comment-user" class="margin-top-15">'+data.userdata.user_firstname+' '+data.userdata.user_lastname+'</p>\ <p id="comment-time">'+date.getTime()+'</p>\ </div>\ <div class="clearfix"></div>\ <div class="col-md-12 margin-top-15" id="comment-text">'+data.userdata.comment_text +'</div>\ <div class="col-md-12">\ <div class="hr-grey margin-top-15"></div>\ </div>\ </div>'; $('#comment-scroll').append($(newComment)); $('#comment').modal('hide'); } }); }); }); what i expect when a comment added to the DB and the PHP page give JSON response, the new comment will be added to the last line of $('#comment-scroll'). #comment-scroll is also have custom scroll bar by mcsCustomscrollbar. the above script also hiding the modal dialog when comment saved and it's working fine which is mean data.userdata is not empty, but why the append() isnt?

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  • tile_static, tile_barrier, and tiled matrix multiplication with C++ AMP

    - by Daniel Moth
    We ended the previous post with a mechanical transformation of the C++ AMP matrix multiplication example to the tiled model and in the process introduced tiled_index and tiled_grid. This is part 2. tile_static memory You all know that in regular CPU code, static variables have the same value regardless of which thread accesses the static variable. This is in contrast with non-static local variables, where each thread has its own copy. Back to C++ AMP, the same rules apply and each thread has its own value for local variables in your lambda, whereas all threads see the same global memory, which is the data they have access to via the array and array_view. In addition, on an accelerator like the GPU, there is a programmable cache, a third kind of memory type if you'd like to think of it that way (some call it shared memory, others call it scratchpad memory). Variables stored in that memory share the same value for every thread in the same tile. So, when you use the tiled model, you can have variables where each thread in the same tile sees the same value for that variable, that threads from other tiles do not. The new storage class for local variables introduced for this purpose is called tile_static. You can only use tile_static in restrict(direct3d) functions, and only when explicitly using the tiled model. What this looks like in code should be no surprise, but here is a snippet to confirm your mental image, using a good old regular C array // each tile of threads has its own copy of locA, // shared among the threads of the tile tile_static float locA[16][16]; Note that tile_static variables are scoped and have the lifetime of the tile, and they cannot have constructors or destructors. tile_barrier In amp.h one of the types introduced is tile_barrier. You cannot construct this object yourself (although if you had one, you could use a copy constructor to create another one). So how do you get one of these? You get it, from a tiled_index object. Beyond the 4 properties returning index objects, tiled_index has another property, barrier, that returns a tile_barrier object. The tile_barrier class exposes a single member, the method wait. 15: // Given a tiled_index object named t_idx 16: t_idx.barrier.wait(); 17: // more code …in the code above, all threads in the tile will reach line 16 before a single one progresses to line 17. Note that all threads must be able to reach the barrier, i.e. if you had branchy code in such a way which meant that there is a chance that not all threads could reach line 16, then the code above would be illegal. Tiled Matrix Multiplication Example – part 2 So now that we added to our understanding the concepts of tile_static and tile_barrier, let me obfuscate rewrite the matrix multiplication code so that it takes advantage of tiling. Before you start reading this, I suggest you get a cup of your favorite non-alcoholic beverage to enjoy while you try to fully understand the code. 01: void MatrixMultiplyTiled(vector<float>& vC, const vector<float>& vA, const vector<float>& vB, int M, int N, int W) 02: { 03: static const int TS = 16; 04: array_view<const float,2> a(M, W, vA); 05: array_view<const float,2> b(W, N, vB); 06: array_view<writeonly<float>,2> c(M,N,vC); 07: parallel_for_each(c.grid.tile< TS, TS >(), 08: [=] (tiled_index< TS, TS> t_idx) restrict(direct3d) 09: { 10: int row = t_idx.local[0]; int col = t_idx.local[1]; 11: float sum = 0.0f; 12: for (int i = 0; i < W; i += TS) { 13: tile_static float locA[TS][TS], locB[TS][TS]; 14: locA[row][col] = a(t_idx.global[0], col + i); 15: locB[row][col] = b(row + i, t_idx.global[1]); 16: t_idx.barrier.wait(); 17: for (int k = 0; k < TS; k++) 18: sum += locA[row][k] * locB[k][col]; 19: t_idx.barrier.wait(); 20: } 21: c[t_idx.global] = sum; 22: }); 23: } Notice that all the code up to line 9 is the same as per the changes we made in part 1 of tiling introduction. If you squint, the body of the lambda itself preserves the original algorithm on lines 10, 11, and 17, 18, and 21. The difference being that those lines use new indexing and the tile_static arrays; the tile_static arrays are declared and initialized on the brand new lines 13-15. On those lines we copy from the global memory represented by the array_view objects (a and b), to the tile_static vanilla arrays (locA and locB) – we are copying enough to fit a tile. Because in the code that follows on line 18 we expect the data for this tile to be in the tile_static storage, we need to synchronize the threads within each tile with a barrier, which we do on line 16 (to avoid accessing uninitialized memory on line 18). We also need to synchronize the threads within a tile on line 19, again to avoid the race between lines 14, 15 (retrieving the next set of data for each tile and overwriting the previous set) and line 18 (not being done processing the previous set of data). Luckily, as part of the awesome C++ AMP debugger in Visual Studio there is an option that helps you find such races, but that is a story for another blog post another time. May I suggest reading the next section, and then coming back to re-read and walk through this code with pen and paper to really grok what is going on, if you haven't already? Cool. Why would I introduce this tiling complexity into my code? Funny you should ask that, I was just about to tell you. There is only one reason we tiled our extent, had to deal with finding a good tile size, ensure the number of threads we schedule are correctly divisible with the tile size, had to use a tiled_index instead of a normal index, and had to understand tile_barrier and to figure out where we need to use it, and double the size of our lambda in terms of lines of code: the reason is to be able to use tile_static memory. Why do we want to use tile_static memory? Because accessing tile_static memory is around 10 times faster than accessing the global memory on an accelerator like the GPU, e.g. in the code above, if you can get 150GB/second accessing data from the array_view a, you can get 1500GB/second accessing the tile_static array locA. And since by definition you are dealing with really large data sets, the savings really pay off. We have seen tiled implementations being twice as fast as their non-tiled counterparts. Now, some algorithms will not have performance benefits from tiling (and in fact may deteriorate), e.g. algorithms that require you to go only once to global memory will not benefit from tiling, since with tiling you already have to fetch the data once from global memory! Other algorithms may benefit, but you may decide that you are happy with your code being 150 times faster than the serial-version you had, and you do not need to invest to make it 250 times faster. Also algorithms with more than 3 dimensions, which C++ AMP supports in the non-tiled model, cannot be tiled. Also note that in future releases, we may invest in making the non-tiled model, which already uses tiling under the covers, go the extra step and use tile_static memory on your behalf, but it is obviously way to early to commit to anything like that, and we certainly don't do any of that today. Comments about this post by Daniel Moth welcome at the original blog.

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  • Who could ask for more with LESS CSS? (Part 3 of 3&ndash;Clrizr)

    - by ToString(theory);
    Welcome back!  In the first two posts in this series, I covered some of the awesome features in CSS precompilers such as SASS and LESS, as well as how to get an initial project setup up and running in ASP.Net MVC 4. In this post, I will cover an actual advanced example of using LESS in a project, and show some of the great productivity features we gain from its usage. Introduction In the first post, I mentioned two subjects that I will be using in this example – constants, and color functions.  I’ve always enjoyed using online color scheme utilities such as Adobe Kuler or Color Scheme Designer to come up with a scheme based off of one primary color.  Using these tools, and requesting a complementary scheme you can get a couple of shades of your primary color, and a couple of shades of a complementary/accent color to display. Because there is no way in regular css to do color operations or store variables, there was no way to accomplish something like defining a primary color, and have a site theme cascade off of that.  However with tools such as LESS, that impossibility becomes a reality!  So, if you haven’t guessed it by now, this post is on the creation of a plugin/module/less file to drop into your project, plugin one color, and have your primary theme cascade from it.  I only went through the trouble of creating a module for getting Complementary colors.  However, it wouldn’t be too much trouble to go through other options such as Triad or Monochromatic to get a module that you could use off of that. Step 1 – Analysis I decided to mimic Adobe Kuler’s Complementary theme algorithm as I liked its simplicity and aesthetics.  Color Scheme Designer is great, but I do believe it can give you too many color options, which can lead to chaos and overload.  The first thing I had to check was if the complementary values for the color schemes were actually hues rotated by 180 degrees at all times – they aren’t.  Apparently Adobe applies some variance to the complementary colors to get colors that are actually more aesthetically appealing to users.  So, I opened up Excel and began to plot complementary hues based on rotation in increments of 10: Long story short, I completed the same calculations for Hue, Saturation, and Lightness.  For Hue, I only had to record the Complementary hue values, however for saturation and lightness, I had to record the values for ALL of the shades.  Since the functions were too complicated to put into LESS since they aren’t constant/linear, but rather interval functions, I instead opted to extrapolate the HSL values using the trendline function for each major interval, onto intervals of spacing 1. For example, using the hue extraction, I got the following values: Interval Function 0-60 60-140 140-270 270-360 Saturation and Lightness were much worse, but in the end, I finally had functions for all of the intervals, and then went the route of just grabbing each shades value in intervals of 1.  Step 2 – Mapping I declared variable names for each of these sections as something that shouldn’t ever conflict with a variable someone would define in their own file.  After I had each of the values, I extracted the values and put them into files of their own for hue variables, saturation variables, and lightness variables…  Example: /*HUE CONVERSIONS*/@clrizr-hue-source-0deg: 133.43;@clrizr-hue-source-1deg: 135.601;@clrizr-hue-source-2deg: 137.772;@clrizr-hue-source-3deg: 139.943;@clrizr-hue-source-4deg: 142.114;.../*SATURATION CONVERSIONS*/@clrizr-saturation-s2SV0px: 0;@clrizr-saturation-s2SV1px: 0;@clrizr-saturation-s2SV2px: 0;@clrizr-saturation-s2SV3px: 0;@clrizr-saturation-s2SV4px: 0;.../*LIGHTNESS CONVERSIONS*/@clrizr-lightness-s2LV0px: 30;@clrizr-lightness-s2LV1px: 31;@clrizr-lightness-s2LV2px: 32;@clrizr-lightness-s2LV3px: 33;@clrizr-lightness-s2LV4px: 34;...   In the end, I have 973 lines of mapping/conversion from source HSL to shade HSL for two extra primary shades, and two complementary shades. The last bit of the work was the file to compose each of the shades from these mappings. Step 3 – Clrizr Mapper The final step was the hardest to overcome as I was still trying to understand LESS to its fullest extent.  Imports As mentioned previously, I had separated the HSL mappings into different files, so the first necessary step is to import those for use into the Clrizr plugin: @import url("hue.less");@import url("saturation.less");@import url("lightness.less"); Extract Component Values For Each Shade Next, I extracted the necessary information for each shade HSL before shade composition: @clrizr-input-saturation: 1px+floor(saturation(@clrizr-input))-1;@clrizr-input-lightness: 1px+floor(lightness(@clrizr-input))-1; @clrizr-complementary-hue: formatstring("clrizr-hue-source-{0}", ceil(hue(@clrizr-input))); @clrizr-primary-2-saturation: formatstring("clrizr-saturation-s2SV{0}",@clrizr-input-saturation);@clrizr-primary-1-saturation: formatstring("clrizr-saturation-s1SV{0}",@clrizr-input-saturation);@clrizr-complementary-1-saturation: formatstring("clrizr-saturation-c1SV{0}",@clrizr-input-saturation); @clrizr-primary-2-lightness: formatstring("clrizr-lightness-s2LV{0}",@clrizr-input-lightness);@clrizr-primary-1-lightness: formatstring("clrizr-lightness-s1LV{0}",@clrizr-input-lightness);@clrizr-complementary-1-lightness: formatstring("clrizr-lightness-c1LV{0}",@clrizr-input-lightness); Here, you can see a couple of odd things…  On the first line, I am using operations to add units to the saturation and lightness.  This is due to some limitations in the operations that would give me saturation or lightness in %, which can’t be in a variable name.  So, I use first add 1px to it, which casts the result of the following functions as px instead of %, and then at the end, I remove that pixel.  You can also see here the formatstring method which is exactly what it sounds like – something like String.Format(string str, params object[] obj). Get Primary & Complementary Shades Now that I have components for each of the different shades, I can now compose them into each of their pieces.  For this, I use the @@ operator which will look for a variable with the name specified in a string, and then call that variable: @clrizr-primary-2: hsl(hue(@clrizr-input), @@clrizr-primary-2-saturation, @@clrizr-primary-2-lightness);@clrizr-primary-1: hsl(hue(@clrizr-input), @@clrizr-primary-1-saturation, @@clrizr-primary-1-lightness);@clrizr-primary: @clrizr-input;@clrizr-complementary-1: hsl(@@clrizr-complementary-hue, @@clrizr-complementary-1-saturation, @@clrizr-complementary-1-lightness);@clrizr-complementary-2: hsl(@@clrizr-complementary-hue, saturation(@clrizr-input), lightness(@clrizr-input)); That’s is it, for the most part.  These variables now hold the theme for the one input color – @clrizr-input.  However, I have one last addition… Perceptive Luminance Well, after I got the colors, I decided I wanted to also get the best font color that would go on top of it.  Black or white depending on light or dark color.  Now I couldn’t just go with checking the lightness, as that is half the story.  You see, the human eye doesn’t see ALL colors equally well but rather has more cells for interpreting green light compared to blue or red.  So, using the ratio, we can calculate the perceptive luminance of each of the shades, and get the font color that best matches it! @clrizr-perceptive-luminance-ps2: round(1 - ( (0.299 * red(@clrizr-primary-2) ) + ( 0.587 * green(@clrizr-primary-2) ) + (0.114 * blue(@clrizr-primary-2)))/255)*255;@clrizr-perceptive-luminance-ps1: round(1 - ( (0.299 * red(@clrizr-primary-1) ) + ( 0.587 * green(@clrizr-primary-1) ) + (0.114 * blue(@clrizr-primary-1)))/255)*255;@clrizr-perceptive-luminance-ps: round(1 - ( (0.299 * red(@clrizr-primary) ) + ( 0.587 * green(@clrizr-primary) ) + (0.114 * blue(@clrizr-primary)))/255)*255;@clrizr-perceptive-luminance-pc1: round(1 - ( (0.299 * red(@clrizr-complementary-1)) + ( 0.587 * green(@clrizr-complementary-1)) + (0.114 * blue(@clrizr-complementary-1)))/255)*255;@clrizr-perceptive-luminance-pc2: round(1 - ( (0.299 * red(@clrizr-complementary-2)) + ( 0.587 * green(@clrizr-complementary-2)) + (0.114 * blue(@clrizr-complementary-2)))/255)*255; @clrizr-col-font-on-primary-2: rgb(@clrizr-perceptive-luminance-ps2, @clrizr-perceptive-luminance-ps2, @clrizr-perceptive-luminance-ps2);@clrizr-col-font-on-primary-1: rgb(@clrizr-perceptive-luminance-ps1, @clrizr-perceptive-luminance-ps1, @clrizr-perceptive-luminance-ps1);@clrizr-col-font-on-primary: rgb(@clrizr-perceptive-luminance-ps, @clrizr-perceptive-luminance-ps, @clrizr-perceptive-luminance-ps);@clrizr-col-font-on-complementary-1: rgb(@clrizr-perceptive-luminance-pc1, @clrizr-perceptive-luminance-pc1, @clrizr-perceptive-luminance-pc1);@clrizr-col-font-on-complementary-2: rgb(@clrizr-perceptive-luminance-pc2, @clrizr-perceptive-luminance-pc2, @clrizr-perceptive-luminance-pc2); Conclusion That’s it!  I have posted a project on clrizr.codePlex.com for this, and included a testing page for you to test out how it works.  Feel free to use it in your own project, and if you have any questions, comments or suggestions, please feel free to leave them here as a comment, or on the contact page!

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  • Know more about Enqueue Deadlock Detection

    - by Liu Maclean(???)
    ??? ORACLE ALLSTAR???????????????????,??????? ???????enqueue lock?????????3 ??????,????????????????????????????ora-00060 dead lock??process???3s: SQL> select * from v$version; BANNER ---------------------------------------------------------------- Oracle Database 10g Enterprise Edition Release 10.2.0.5.0 - 64bi PL/SQL Release 10.2.0.5.0 - Production CORE 10.2.0.5.0 Production TNS for Linux: Version 10.2.0.5.0 - Production NLSRTL Version 10.2.0.5.0 - Production SQL> select * from global_name; GLOBAL_NAME -------------------------------------------------------------------------------- www.oracledatabase12g.com PROCESS A: set timing on; update maclean1 set t1=t1+1; PROCESS B: update maclean2 set t1=t1+1; PROCESS A: update maclean2 set t1=t1+1; PROCESS B: update maclean1 set t1=t1+1; ??3s? PROCESS A ?? ERROR at line 1: ORA-00060: deadlock detected while waiting for resource Elapsed: 00:00:03.02 ????Process A????????????? 3s,?????????????,??????? ?????????? ???????: SQL> col name for a30 SQL> col value for a5 SQL> col DESCRIB for a50 SQL> set linesize 140 pagesize 1400 SQL> SELECT x.ksppinm NAME, y.ksppstvl VALUE, x.ksppdesc describ 2 FROM SYS.x$ksppi x, SYS.x$ksppcv y 3 WHERE x.inst_id = USERENV ('Instance') 4 AND y.inst_id = USERENV ('Instance') 5 AND x.indx = y.indx 6 AND x.ksppinm='_enqueue_deadlock_scan_secs'; NAME VALUE DESCRIB ------------------------------ ----- -------------------------------------------------- _enqueue_deadlock_scan_secs 0 deadlock scan interval SQL> alter system set "_enqueue_deadlock_scan_secs"=18 scope=spfile; System altered. Elapsed: 00:00:00.01 SQL> startup force; ORACLE instance started. Total System Global Area 851443712 bytes Fixed Size 2100040 bytes Variable Size 738198712 bytes Database Buffers 104857600 bytes Redo Buffers 6287360 bytes Database mounted. Database opened. PROCESS A: SQL> set timing on; SQL> update maclean1 set t1=t1+1; 1 row updated. Elapsed: 00:00:00.06 Process B SQL> update maclean2 set t1=t1+1; 1 row updated. SQL> update maclean1 set t1=t1+1; Process A: SQL> SQL> alter session set events '10704 trace name context forever,level 10:10046 trace name context forever,level 8'; Session altered. SQL> update maclean2 set t1=t1+1; update maclean2 set t1=t1+1 * ERROR at line 1: ORA-00060: deadlock detected while waiting for resource  Elapsed: 00:00:18.05 ksqcmi: TX,90011,4a9 mode=6 timeout=21474836 WAIT #12: nam='enq: TX - row lock contention' ela= 2930070 name|mode=1415053318 usn<<16 | slot=589841 sequence=1193 obj#=56810 tim=1308114759849120 WAIT #12: nam='enq: TX - row lock contention' ela= 2930636 name|mode=1415053318 usn<<16 | slot=589841 sequence=1193 obj#=56810 tim=1308114762779801 WAIT #12: nam='enq: TX - row lock contention' ela= 2930439 name|mode=1415053318 usn<<16 | slot=589841 sequence=1193 obj#=56810 tim=1308114765710430 *** 2012-06-12 09:58:43.089 WAIT #12: nam='enq: TX - row lock contention' ela= 2931698 name|mode=1415053318 usn<<16 | slot=589841 sequence=1193 obj#=56810 tim=1308114768642192 WAIT #12: nam='enq: TX - row lock contention' ela= 2930428 name|mode=1415053318 usn<<16 | slot=589841 sequence=1193 obj#=56810 tim=1308114771572755 WAIT #12: nam='enq: TX - row lock contention' ela= 2931408 name|mode=1415053318 usn<<16 | slot=589841 sequence=1193 obj#=56810 tim=1308114774504207 DEADLOCK DETECTED ( ORA-00060 ) [Transaction Deadlock] The following deadlock is not an ORACLE error. It is a deadlock due to user error in the design of an application or from issuing incorrect ad-hoc SQL. The following information may aid in determining the deadlock: ??????Process A?’enq: TX – row lock contention’ ?????ORA-00060 deadlock detected????3s ??? 18s , ???hidden parameter “_enqueue_deadlock_scan_secs”?????,????????0? ??????????: SQL> alter system set "_enqueue_deadlock_scan_secs"=4 scope=spfile; System altered. Elapsed: 00:00:00.01 SQL> alter system set "_enqueue_deadlock_time_sec"=9 scope=spfile; System altered. Elapsed: 00:00:00.00 SQL> startup force; ORACLE instance started. Total System Global Area 851443712 bytes Fixed Size 2100040 bytes Variable Size 738198712 bytes Database Buffers 104857600 bytes Redo Buffers 6287360 bytes Database mounted. Database opened. SQL> set linesize 140 pagesize 1400 SQL> show parameter dead NAME TYPE VALUE ------------------------------------ -------------------------------- ------------------------------ _enqueue_deadlock_scan_secs integer 4 _enqueue_deadlock_time_sec integer 9 SQL> set timing on SQL> select * from maclean1 for update wait 8; T1 ---------- 11 Elapsed: 00:00:00.01 PROCESS B SQL> select * from maclean2 for update wait 8; T1 ---------- 3 SQL> select * from maclean1 for update wait 8; select * from maclean1 for update wait 8 PROCESS A SQL> select * from maclean2 for update wait 8; select * from maclean2 for update wait 8 * ERROR at line 1: ORA-30006: resource busy; acquire with WAIT timeout expired Elapsed: 00:00:08.00 ???????? ??? select for update wait?enqueue request timeout ?????8s? ,???????”_enqueue_deadlock_scan_secs”=4(deadlock scan interval),?4s???deadlock detected,????Process A????deadlock ???, ??????? ??Process A?????8s?raised??”ORA-30006: resource busy; acquire with WAIT timeout expired”??,??ORA-00060,?????process A???????? ????????”_enqueue_deadlock_time_sec”(requests with timeout <= this will not have deadlock detection)???,?enqueue request time < “_enqueue_deadlock_time_sec”?Server process?????dead lock detection,?????????enqueue request ??????timeout??????(_enqueue_deadlock_time_sec????5,?timeout<5s),???????????????;??????timeout>”_enqueue_deadlock_time_sec”???,Oracle????????????????????? ??????????: SQL> show parameter dead NAME TYPE VALUE ------------------------------------ -------------------------------- ------------------------------ _enqueue_deadlock_scan_secs integer 4 _enqueue_deadlock_time_sec integer 9 Process A: SQL> set timing on; SQL> select * from maclean1 for update wait 10; T1 ---------- 11 Process B: SQL> select * from maclean2 for update wait 10; T1 ---------- 3 SQL> select * from maclean1 for update wait 10; PROCESS A: SQL> select * from maclean2 for update wait 10; select * from maclean2 for update wait 10 * ERROR at line 1: ORA-00060: deadlock detected while waiting for resource Elapsed: 00:00:06.02 ??????? select for update wait 10?10s??, ?? 10s?????_enqueue_deadlock_time_sec???(9s),??Process A???????? ???????????????6s ???????_enqueue_deadlock_scan_secs?4s ? ???????????,???????????_enqueue_deadlock_scan_secs?????????3???? ??: enqueue lock?????????????? 1. ?????????deadlock detection??3s????, ????????_enqueue_deadlock_scan_secs(deadlock scan interval)???,??????0,????????_enqueue_deadlock_scan_secs?????????3???, ?_enqueue_deadlock_scan_secs=0 ??3s??, ?_enqueue_deadlock_scan_secs=4??6s??,????? 2. ???????_enqueue_deadlock_time_sec(requests with timeout <= this will not have deadlock detection)???,?enqueue request timeout< _enqueue_deadlock_time_sec(????5),?Server process?????????enqueue request timeout>_enqueue_deadlock_time_sec ????_enqueue_deadlock_scan_secs???????, ??request timeout??????select for update wait [TIMEOUT]??? ??: ???10.2.0.1?????????2?hidden parameter , ???patchset 10.2.0.3????? _enqueue_deadlock_time_sec, ?patchset 10.2.0.5??????_enqueue_deadlock_scan_secs? ?????RAC???????????10s, ???????_lm_dd_interval(dd time interval in seconds) ,????????8.0.6???? ???????????????,??????,  ?10g???????60s,?11g???????10s?  ???????11g??_lm_dd_interval?????????????,?????11g??LMD????????????,??????????RAC?LMD?Deadlock Detection???????CPU,???11g?Oracle????Team???LMD????????CPU????: ????????11g?LMD???????,???????11g??? UTS TRACE ????? DD???: SQL> select * from v$version; BANNER -------------------------------------------------------------------------------- Oracle Database 11g Enterprise Edition Release 11.2.0.3.0 - 64bit Production PL/SQL Release 11.2.0.3.0 - Production CORE 11.2.0.3.0 Production TNS for Linux: Version 11.2.0.3.0 - Production NLSRTL Version 11.2.0.3.0 - Production SQL> SQL> select * from global_name 2 ; GLOBAL_NAME -------------------------------------------------------------------------------- www.oracledatabase12g.com SQL> alter system set "_lm_dd_interval"=20 scope=spfile; System altered. SQL> startup force; ORACLE instance started. Total System Global Area 1570009088 bytes Fixed Size 2228704 bytes Variable Size 1325403680 bytes Database Buffers 234881024 bytes Redo Buffers 7495680 bytes Database mounted. Database opened. SQL> set linesize 140 pagesize 1400 SQL> show parameter lm_dd NAME TYPE VALUE ------------------------------------ -------------------------------- ------------------------------ _lm_dd_interval integer 20 SQL> select count(*) from gv$instance; COUNT(*) ---------- 2 instance 1: SQL> oradebug setorapid 12 Oracle pid: 12, Unix process pid: 8608, image: [email protected] (LMD0) ? LMD0??? UTS TRACE??RAC???????????? SQL> oradebug event 10046 trace name context forever,level 8:10708 trace name context forever,level 103: trace[rac.*] disk high; Statement processed. Elapsed: 00:00:00.00 SQL> update maclean1 set t1=t1+1; 1 row updated. instance 2: SQL> update maclean2 set t1=t1+1; 1 row updated. SQL> update maclean1 set t1=t1+1; Instance 1: SQL> update maclean2 set t1=t1+1; update maclean2 set t1=t1+1 * ERROR at line 1: ORA-00060: deadlock detected while waiting for resource Elapsed: 00:00:20.51 LMD0???UTS TRACE 2012-06-12 22:27:00.929284 : [kjmpbmsg:process][type 22][msg 0x7fa620ac85a8][from 1][seq 8148.0][len 192] 2012-06-12 22:27:00.929346 : [kjmxmpm][type 22][seq 0.0][msg 0x7fa620ac85a8][from 1] *** 2012-06-12 22:27:00.929 * kjddind: received DDIND msg with subtype x6 * reqp->dd_master_inst_kjxmddi == 1 * kjddind: dump sgh: 2012-06-12 22:27:00.929346*: kjddind: req->timestamp [0.15], kjddt [0.13] 2012-06-12 22:27:00.929346*: >> DDmsg:KJX_DD_REMOTE,TS[0.15],Inst 1->2,ddxid[id1,id2,inst:2097153,31,1],ddlock[0x95023930,829],ddMasterInst 1 2012-06-12 22:27:00.929346*: lock [0x95023930,829], op = [mast] 2012-06-12 22:27:00.929346*: reqp->timestamp [0.15], kjddt [0.13] 2012-06-12 22:27:00.929346*: kjddind: updated local timestamp [0.15] * kjddind: case KJX_DD_REMOTE 2012-06-12 22:27:00.929346*: ADD IO NODE WFG: 0 frame pointer 2012-06-12 22:27:00.929346*: PUSH: type=res, enqueue(0xffffffff.0xffffffff)=0xbbb9af40, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929346*: PROCESS: type=res, enqueue(0xffffffff.0xffffffff)=0xbbb9af40, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929346*: POP: type=res, enqueue(0xffffffff.0xffffffff)=0xbbb9af40, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929346*: kjddopr[TX 0xe000c.0x32][ext 0x5,0x0]: blocking lock 0xbbb9a800, owner 2097154 of inst 2 2012-06-12 22:27:00.929346*: PUSH: type=txn, enqueue(0xffffffff.0xffffffff)=0xbbb9a800, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929346*: PROCESS: type=txn, enqueue(0xffffffff.0xffffffff)=0xbbb9a800, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929346*: ADD NODE TO WFG: type=txn, enqueue(0xffffffff.0xffffffff)=0xbbb9a800, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929346*: POP: type=txn, enqueue(0xffffffff.0xffffffff)=0xbbb9a800, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929346*: kjddopt: converting lock 0xbbce92f8 on 'TX' 0x80016.0x5d4,txid [2097154,34]of inst 2 2012-06-12 22:27:00.929346*: PUSH: type=res, enqueue(0xffffffff.0xffffffff)=0xbbce92f8, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929346*: PROCESS: type=res, enqueue(0xffffffff.0xffffffff)=0xbbce92f8, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929346*: ADD NODE TO WFG: type=res, enqueue(0xffffffff.0xffffffff)=0xbbce92f8, block=KJUSEREX, snode=1 2012-06-12 22:27:00.929855 : GSIPC:AMBUF: rcv buff 0x7fa620aa8cd8, pool rcvbuf, rqlen 1102 2012-06-12 22:27:00.929878 : GSIPC:GPBMSG: new bmsg 0x7fa620aa8d48 mb 0x7fa620aa8cd8 msg 0x7fa620aa8d68 mlen 192 dest x100 flushsz -1 2012-06-12 22:27:00.929878*: << DDmsg:KJX_DD_REMOTE,TS[0.15],Inst 2->1,ddxid[id1,id2,inst:2097153,31,1],ddlock[0x95023930,829],ddMasterInst 1 2012-06-12 22:27:00.929878*: lock [0xbbce92f8,287], op = [mast] 2012-06-12 22:27:00.929878*: ADD IO NODE WFG: 0 frame pointer 2012-06-12 22:27:00.929923 : [kjmpbmsg:compl][msg 0x7fa620ac8588][typ p][nmsgs 1][qtime 0][ptime 0] 2012-06-12 22:27:00.929947 : GSIPC:PBAT: flush start. flag 0x79 end 0 inc 4.4 2012-06-12 22:27:00.929963 : GSIPC:PBAT: send bmsg 0x7fa620aa8d48 blen 224 dest 1.0 2012-06-12 22:27:00.929979 : GSIPC:SNDQ: enq msg 0x7fa620aa8d48, type 65521 seq 8325, inst 1, receiver 0, queued 1 012-06-12 22:27:00.929979 : GSIPC:SNDQ: enq msg 0x7fa620aa8d48, type 65521 seq 8325, inst 1, receiver 0, queued 1 2012-06-12 22:27:00.929996 : GSIPC:BSEND: flushing sndq 0xb491dd28, id 0, dcx 0xbc517770, inst 1, rcvr 0 qlen 0 1 2012-06-12 22:27:00.930014 : GSIPC:BSEND: no batch1 msg 0x7fa620aa8d48 type 65521 len 224 dest (1:0) 2012-06-12 22:27:00.930088 : kjbsentscn[0x0.3f72dc][to 1] 2012-06-12 22:27:00.930144 : GSIPC:SENDM: send msg 0x7fa620aa8d48 dest x10000 seq 8325 type 65521 tkts x1 mlen xe00110 2012-06-12 22:27:00.930531 : GSIPC:KSXPCB: msg 0x7fa620aa8d48 status 30, type 65521, dest 1, rcvr 0 WAIT #0: nam='ges remote message' ela= 1372 waittime=80 loop=0 p3=74 obj#=-1 tim=1339554420931640 2012-06-12 22:27:00.931728 : GSIPC:RCVD: ksxp msg 0x7fa620af6490 sndr 1 seq 0.8149 type 65521 tkts 1 2012-06-12 22:27:00.931746 : GSIPC:RCVD: watq msg 0x7fa620af6490 sndr 1, seq 8149, type 65521, tkts 1 2012-06-12 22:27:00.931763 : GSIPC:RCVD: seq update (0.8148)->(0.8149) tp -15 fg 0x4 from 1 pbattr 0x0 2012-06-12 22:27:00.931779 : GSIPC:TKT: collect msg 0x7fa620af6490 from 1 for rcvr 0, tickets 1 2012-06-12 22:27:00.931794 : kjbrcvdscn[0x0.3f72dc][from 1][idx 2012-06-12 22:27:00.931810 : kjbrcvdscn[no bscn dd_master_inst_kjxmddi == 1 * kjddind: dump sgh: NXTIN (nil) 0 wq 0 cvtops x0 0x0.0x0(ext 0x0,0x0)[0000-0000-00000000] inst 1 BLOCKER 0xbbb9a800 5 wq 1 cvtops x28 TX 0xe000c.0x32(ext 0x5,0x0)[20000-0002-00000022] inst 2 BLOCKED 0xbbce92f8 5 wq 2 cvtops x1 TX 0x80016.0x5d4(ext 0x2,0x0)[20000-0002-00000022] inst 2 NXTOUT (nil) 0 wq 0 cvtops x0 0x0.0x0(ext 0x0,0x0)[0000-0000-00000000] inst 1 2012-06-12 22:27:00.932058*: kjddind: req->timestamp [0.15], kjddt [0.15] 2012-06-12 22:27:00.932058*: >> DDmsg:KJX_DD_VALIDATE,TS[0.15],Inst 1->2,ddxid[id1,id2,inst:2097153,31,1],ddlock[0x95023930,829],ddMasterInst 1 2012-06-12 22:27:00.932058*: lock [(nil),0], op = [vald_dd] 2012-06-12 22:27:00.932058*: kjddind: updated local timestamp [0.15] * kjddind: case KJX_DD_VALIDATE *** 2012-06-12 22:27:00.932 * kjddvald called: kjxmddi stuff: * cont_lockp (nil) * dd_lockp 0x95023930 * dd_inst 1 * dd_master_inst 1 * sgh graph: NXTIN (nil) 0 wq 0 cvtops x0 0x0.0x0(ext 0x0,0x0)[0000-0000-00000000] inst 1 BLOCKER 0xbbb9a800 5 wq 1 cvtops x28 TX 0xe000c.0x32(ext 0x5,0x0)[20000-0002-00000022] inst 2 BLOCKED 0xbbce92f8 5 wq 2 cvtops x1 TX 0x80016.0x5d4(ext 0x2,0x0)[20000-0002-00000022] inst 2 NXTOUT (nil) 0 wq 0 cvtops x0 0x0.0x0(ext 0x0,0x0)[0000-0000-00000000] inst 1 POP WFG NODE: lock=(nil) * kjddvald: dump the PRQ: BLOCKER 0xbbb9a800 5 wq 1 cvtops x28 TX 0xe000c.0x32(ext 0x5,0x0)[20000-0002-00000022] inst 2 BLOCKED 0xbbce92f8 5 wq 2 cvtops x1 TX 0x80016.0x5d4(ext 0x2,0x0)[20000-0002-00000022] inst 2 * kjddvald: KJDD_NXTONOD ->node_kjddsg.dinst_kjddnd =1 * kjddvald: ... which is not my node, my subgraph is validated but the cycle is not complete Global blockers dump start:--------------------------------- DUMP LOCAL BLOCKER/HOLDER: block level 5 res [0x80016][0x5d4],[TX][ext 0x2,0x0] ??dead lock!!! ???????11.2.0.3???? RAC LMD???????????”_lm_dd_interval”????????????20s?  ???????10g?_lm_dd_interval???60s,??????Processes?????????????????,????????????Server Process????????60s??????11g?????(??????LMD???????)???????,???????????10s??? Enqueue Deadlock Detection? ?11g??? RAC?LMD???????hidden parameter ????”_lm_dd_interval”???,RAC????????????????,???????????: SQL> col name for a50 SQL> col describ for a60 SQL> col value for a20 SQL> set linesize 140 pagesize 1400 SQL> SELECT x.ksppinm NAME, y.ksppstvl VALUE, x.ksppdesc describ 2 FROM SYS.x$ksppi x, SYS.x$ksppcv y 3 WHERE x.inst_id = USERENV ('Instance') 4 AND y.inst_id = USERENV ('Instance') 5 AND x.indx = y.indx 6 AND x.ksppinm like '_lm_dd%'; NAME VALUE DESCRIB -------------------------------------------------- -------------------- ------------------------------------------------------------ _lm_dd_interval 20 dd time interval in seconds _lm_dd_scan_interval 5 dd scan interval in seconds _lm_dd_search_cnt 3 number of dd search per token get _lm_dd_max_search_time 180 max dd search time per token _lm_dd_maxdump 50 max number of locks to be dumped during dd validation _lm_dd_ignore_nodd FALSE if TRUE nodeadlockwait/nodeadlockblock options are ignored 6 rows selected.

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  • Using jQuery validation plugin with tabbed navigation

    - by user3438917
    I have a tabbed navigation wizard, for which the first section needs to be validated before proceeding to the next tab. The validation should trigger when the user hits the "next" button. I am unable to get the validation to trigger though: <form id="target-group" novalidate="novalidate"> <div class="box"> <div class='box-header-main'><h2><img src="assets/img/list.png" /> Target Group Information</h2></div> <br /> <div class='box'> <div class='box-header-property'><h2><span data-bind="text:Name">New Target Group</span> | <i class='fa fa-file'></i></h2></div> <br /> <div class='row'> <div id='flight-wizard'> <div id='content' class='col-lg-12'> <div class='col-lg-12'> <div id='tabs'> <ul> <li id="targetgroup-info-tab"><a href='#tabs-1'><i class="fa fa-info-circle"></i>Target Group Info</a></li> <li id="zone-tab"><a href='#tabs-2'><i class="fa fa-map-marker"></i>Zones</a></li> </ul> <div id='tabs-1'> <div class='row'> <div class='col-xs-6'> <div class='form-group'> Name<sup>*</sup> <input id="selectError0" name="name" class='form-control col-xs-12' data-bind="value: asdf" placeholder='Enter Name ...' /> </div> <form class='form-horizontal'> <div class='form-group'> Product(s)<sup>*</sup> <div class='controls' id='products'> <select id='selectError3' class='form-control' data-bind="options:test, optionsText: 'Name', optionsValue : 'test', value: test, optionsCaption: 'Choose Product...'"></select> </div> </div> </form> </div> <!--RIGHT PANE--> <div class='col-xs-6'> <div class='form-group'> Platform<sup>*</sup> <div class='controls'> <select id="selectError2" class='form-control' data-bind="options:test, optionsText: 'Name', optionsValue: 'test', value : test, optionsCaption: 'Choose Platform...'"></select> </div> </div> <form class='form-horizontal'> <div class='form-group'> AdTypes(s)<sup>*</sup> <div class='controls' id='adtypes'> <select multiple="" id='adtypesselect' class='form-control' data-rel="chosen" data-bind="options:test, optionsText: 'Name', optionsValue : 'test', selectedOptions: test, optionsCaption: 'test...'"></select> </div> </div> </form> <button id="btn_cancel_large" class='btn btn-large btn-primary btn-round'><i class='fa fa-ban' /></i> Cancel</button> <button id="btn-next-large" class='btn btn-large btn-primary btn-round'>Next <i class='fa fa-arrow-circle-right'></i></button> </div> <!--end of right pane--> </div> </div> <div id='tabs-2'> <div class='row'> <div class='col-lg-12'> <div class='row'> <div class='col-lg-12'> <div id='zones_list' class='box-content'> <div id='add-new-targetgroupzone' class='add-new'><i class='fa fa-plus-circle'></i><a href='/#/inventory/targeting/' onclick="return false;">Add Zone</a></div> <table id="results" width="100%"> <thead> <tr> <th>Publisher</th> <th>Property</th> <th>Zone</th> <th>AdTypes</th> <th width='10%'>Quick&nbsp;Actions</th> </tr> </thead> </table> </div> </div> </div> </div> </div> <br /> <div class="btn_row"> <button id="btn_cancel_large2" class='btn btn-large btn-primary btn-round'><i class='fa fa-ban' /></i> Cancel</button> <button id="btn-submit-large" class='btn btn-large btn-primary btn-round'>Submit <i class='fa fa-arrow-circle-down'></i></button> </div> </div> </div> </div> </div> </div> </div> </div> </div> </form> <form id="zones-form" style="display: none;" novalidate="novalidate" class="slideup-form"> <div class="box"> <div class="box-header-panel"> <h2>Add Target Group Zone</h2> <div class="box-icon" id="zones-form-close"> <i class="fa fa-arrow-circle-down"></i> </div> </div> <div class="box-content clearfix"> <div class="box-content"> <table id="zones-list" width="100%"> <thead> <tr> <th>Publisher</th> <th>Property</th> <th>Zone</th> <th>AdTypes</th> <th width='10%'>Quick&nbsp;Actions</th> </tr> </thead> </table> </div> </div> </div> </div> </form> jQuery: $("#target-group").validate({ rules: { name: { required: true } }, messages: { name: "Name required", } }); $('#btn-next-large').click(function () { if ($('#target-group').valid()) $tabs.tabs('select', $(this).attr("rel")); });

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  • Using R to Analyze G1GC Log Files

    - by user12620111
    Using R to Analyze G1GC Log Files body, td { font-family: sans-serif; background-color: white; font-size: 12px; margin: 8px; } tt, code, pre { font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace; } h1 { font-size:2.2em; } h2 { font-size:1.8em; } h3 { font-size:1.4em; } h4 { font-size:1.0em; } h5 { font-size:0.9em; } h6 { font-size:0.8em; } a:visited { color: rgb(50%, 0%, 50%); } pre { margin-top: 0; max-width: 95%; border: 1px solid #ccc; white-space: pre-wrap; } pre code { display: block; padding: 0.5em; } code.r, code.cpp { background-color: #F8F8F8; } table, td, th { border: none; } blockquote { color:#666666; margin:0; padding-left: 1em; border-left: 0.5em #EEE solid; } hr { height: 0px; border-bottom: none; border-top-width: thin; border-top-style: dotted; border-top-color: #999999; } @media print { * { background: transparent !important; color: black !important; filter:none !important; -ms-filter: none !important; } body { 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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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  • Error: (subscript) logical subscript too long

    - by frespider
    Can some one let me know why I am getting this error and how I can fix it? Here is the code What I am trying to do is remove the rows that associated 1's if the column of that one's less than 10 a0=rep(1,40) a=rep(0:1,20) b=c(rep(1,20),rep(0,20)) c0=c(rep(0,12),rep(1,28)) c1=c(rep(1,5),rep(0,35)) c2=c(rep(1,8),rep(0,32)) c3=c(rep(1,23),rep(0,17)) c4=c(rep(1,6),rep(0,34)) x=matrix(cbind(a0,a,b,c0,c1,c2,c3,c4),nrow=40,ncol=8) nam <- paste("V",2:9,sep="") colnames(x)<-nam dat <- cbind(y=rnorm(40,50,7),x) #=================================== toSum <- colSums(dat) Col <- Val <- NULL for(i in 1:length(toSum)){ if(toSum[i]<10){ Col <- c(Col,colnames(dat)[i]) Val <- c(Val,toSum[i])} } cs <- colSums(dat) < 10 indx <- dat[,which(cs)]==0 for(i in 1:dim(indx)[2]){ datnw <- dat[indx[,i],] dat <- datnw} datnw2 <- dat[, -which(cs)] Thanks

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  • UltraWebGrid: How to use a drop-down list in a column

    - by Crossbrowser
    I'm using the Infragistics grid and I'm having a difficult time using a drop-down list as the value selector for one of my columns. I tried reading the documentation but Infragistics' documentation is not so good. I've also taken a look at this discussion with no luck. What I'm doing so far: col.Type = ColumnType.DropDownList; col.DataType = "System.String"; col.ValueList = myValueList; where myValueList is: ValueList myValueList = new ValueList(); myValueList.Prompt = "My text prompt"; myValueList.DisplayStyle = ValueListDisplayStyle.DisplayText; foreach(MyObjectType item in MyObjectTypeCollection) { myValueList.ValueItems.Add(item.ID, item.Text); // Note that the ID is a string (not my design) } When I look at the page, I expect to see a drop-down list in the cells for this column, but my columns are empty.

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  • performance of linq extension method ElementAt

    - by Fabiano
    Hi The MSDN library entry to Enumerable.ElementAt(TSource) Method says "If the type of source implements IList, that implementation is used to obtain the element at the specified index. Otherwise, this method obtains the specified element." Let's say we have following example: ICollection<int> col = new List<int>() { /* fill with items */ }; IList<int> list = new List<int>() { /* fill with items */ }; col.ElementAt(10000000); list.ElementAt(10000000); Is there any difference in execution? or does ElementAt recognize that col also implements IList< although it's only declared as ICollection<? Thanks

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  • How do I create an empty array/matrix in NumPy?

    - by Ben
    I'm sure I must be being very dumb, but I can't figure out how to use an array or matrix in the way that I would normally use a list. I.e., I want to create an empty array (or matrix) and then add one column (or row) to it at a time. At the moment the only way I can find to do this is like: mat = None for col in columns: if mat is None: mat = col else: mat = hstack((mat, col)) Whereas if it were a list, I'd do something like this: list = [] for item in data: list.append(item) Is there a way to use that kind of notation for NumPy arrays or matrices? (Or a better way -- I'm still pretty new to python!)

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  • Uibutton events

    - by Raju
    //My Button code --------------------------------------------------------------------------------------------------- UIButton *ticketButtonObj=[[ticketButton alloc]initWithFrame:CGRectMake(0.0f, 115.0f, 500.0f, 40.0f) ; int col=10; [ticketButtonObj addTarget:self action:@selector(ShowNumber:) forControlEvents:UIControlEventTouchUpInside]; [self.window addSubview:ticketButtonObj]; -(void) ShowNumber:(id)sender{ // here i want to get the Value of Col } in the above code when i pressed the button.. i want print the value of col variable in ShowNumber method .. how it is ? pls Help me ... thanks and regards... by raju

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  • How to get the row number of the QComboBox in QTableWidget

    - by dreamxiuhuishan
    Here is the code, but it dos not work. Who can create the code. Thanks very much! void add() { QComboBox *ziduan = new QComboBox; ziduan->addItem("??","nd"); int row =0; int col =1; QSignalMapper* signalMapper = new QSignalMapper(this); connect(ziduan, SIGNAL(currentIndexChanged(int)), signalMapper, SLOT(map())); signalMapper->setMapping(ziduan, QString("%1-%2").arg(row).arg(col)); connect(signalMapper, SIGNAL(mapped(const QString &)),this, SIGNAL(changeZiduan(const QString &))); } void sqlGenerator::changeZiduan(const QString &position) { QStringList coordinates = position.split("-"); int row = coordinates[0].toInt(); int col = coordinates[1].toInt(); }

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  • XSLT 1.0 count element with the same value in an attribute, and show it

    - by Erick
    I have a variable containing: <col p1="Newman" p2="Paul"/> ... <col p1="Newman" p2="Paolo"/> <col p1="Newman" p2="Paul"/> i wold in output a table with in the first column the value of p2 and in the second the number of time it appear. For each value of p2 should i have only a row. <table> <tr><td>p2</td><td>num</td></tr> <tr><td>Pault</td><td>2</td> ... <tr><td>Paolo</td><td>1</td> </table>

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  • Coldfusion returning typed objects / AMF remoting

    - by Chin
    Is the same possible in ColdFusion? Currently I am using .Net/Fluorine to return objects to the client. Whilst in testing I like to pass strings representing the select statement and the custom object I wish to have returned from my service. Fluorine has a class ASObject to which you can set the var 'typeName'; which works great. I am hoping that this is possible in Coldfusion. Does anyone know whether you can set the type of the returned object in a similar way. This is especially helpful with large collections as the flash player will convert them to a local object of the same name thus saving interating over the collection to convert the objects to a particular custom object. foreach (DataRow row in ds.Tables[0].Rows) { ASObject obj = new ASObject(); foreach (DataColumn col in ds.Tables[0].Columns) { obj.Add(col.ColumnName, row[col.ColumnName]); } obj.TypeName = pObjType; al.Add(obj); } Many thanks,

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  • Processing CSV File

    - by nettguy
    I am using Sebastien LorionReference CSV reader to process my CSV file in C# 3.0. Say example id|name|dob (Header) 1|sss|19700101 (data) 2|xx|19700201 (data) My Business Object is class Employee { public string ID {get;set;} public string Name {get;set;} public string Dob {get;set;} } I read the CSV stream and stored it in List<string[]> List<string[]> col = new List<string[]>(); using (CsvReader csv = new CsvReader (new StreamReader("D:\\sample.txt"), true, '|')) { col = csv.ToList(); } How to iterate over the list to get each Employee like foreach (var q in col) { foreach (var r in q) { Employee emp=new Employee(); emp.ID =r[0]; emp.Name=r[1]; emp.Dob=r[2]; } } If i call r[0],r[1],r[2] i am getting "index out of range exception".How the process the list to avoid the error?

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  • Excel VBA pass array of arrays to a function

    - by user429400
    I have one function that creates an array of arrays, and one function that should get the resulting array and write it to the spreadsheet. I don't find the syntax which will allow me to pass the array of arrays to the second function... Could you please help? Here is my code: The function that creates the array of arrays: Function GetCellDetails(dict1 As Dictionary, dict2 As Dictionary) As Variant Dim arr1, arr2 arr1 = dict1.Items arr2 = dict2.Items GetCellDetails = Array(arr1, arr2) End Function the function that writes it to the spreadsheet: Sub WriteCellDataToMemory(arr As Variant, day As Integer, cellId As Integer, nCells As Integer) row = CellIdToMemRow(cellId, nCells) col = DayToMemCol(day) arrSize = UBound(arr, 2) Range(Cells(row, col), Cells(row + arrSize , col + 2)) = Application.Transpose(arr) End Sub The code that calls the functions: Dim CellDetails CellDetails = GetCellDetails(dict1, dict2) WriteCellDataToMemory CellDetails, day, cellId, nCells Thanks, Li

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  • changing css properties via javascript

    - by tic
    I need a function to change the appearance of some elements in my html page "on the fly", but I am not able to do. The problem is that I cannot use a command like document.write ('body {background-color: #cccccc;}'); because I need to make the changes effective when the page is already loaded, using a link like <a onmouseclick="Clicker(1)" href="#">clic</a> and I cannot use a command like document.body.style.background='#cccccc'; because I do not know if it can be applied to other not so easy cases, because I need to change the appearance of elements such as td.myclass or sibling elements such as th[scope=col]+th[scope=col]+th[scope=col]. How can I do it? Thanks!

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  • How to print an isosceles triangle

    - by Steve
    Hello, I'm trying to learn programming by myself, I'm working from a book that has the following problem which I can't solve: Allow the user to input two values: a character to be used for printing an isosceles triangle and the size of the peak for the triangle. For example, if the user inputs # for the character and 6 for the peak, you should produce the following display: # ## ### #### ##### ###### ##### #### ### ## # This is the code I've got so far: char character; int peak; InputValues(out character, out peak); for (int row = 1; row < peak * 2; row++) { for (int col = 1; col <= row; col++) { Console.Write(character); } Console.WriteLine(); } Console.Read() // hold console open Thanks in advance.

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  • How to obtain multiple lines in a single density plot, with a corrected scale?

    - by user1677055
    I have recently started working with microarray datasets and am trying to get my hands on R. I wish to make some plots out of my result data, but however I am stuck at the following. I have the following data (myData), cpg samp1 samp2 samp3 cpg1 0.43 0.32 0.21 cpg2 0.43 0.22 1.00 cpg3 0.11 0.99 0.78 cpg4 0.65 0.32 0.12 cpg5 0.11 0.43 0.89 And I wish to obtain a density plot for this, I did the following, plot (density(MyData$samp1), col="red") lines (density(MyData$samp2), col="green") lines (density(MyData$samp3), col="blue") But doing this does not give me correct plots, because not all sample curves fit within the plot limits. I did try looking for answers, but honestly i am still not able to work this out. Can you help me know how do i set my scale for the above? Or what additional should I do to the above code, so that all the curves are in range?? I have got many samples, so i need a something that could also automatically assign a different colour curve for each of my sample, after scaling it right. Thanks in advance..

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