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• Can I get a raw pointer from boost's weak_ptr?

  - by Czubaka

  Is it possible to get a raw pointer from boost::weak_ptr? Boost's shared_ptr has get() method and "-" operator. Is there some rationale behind weak_ptr not having the same functionality?

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• Groovy , what does -> mean

  - by user350325

  In examples of groovy code I find the -> operator everywhere, but the groovy tutorials nor the book I have seem to provide any explaination as to what this means.

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• What is the difference between is_a and instanceof?

  - by Daniel L

  I am aware that instanceof is an operator and that is_a is a method. Is the method slower in performance? What would you prefer to use?

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• Explanation about a Java statement

  - by monn

  public static void main(String[] args) { int x = 1 + + + + + + + + + 2; System.out.println(x); } I can compile above method. Is there any explanation about the allowed multiple "+" operator?

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• LINQ display row numbers

  - by timvaines

  I simply want to include a row number against the returned results of my query. I found the following post that describes what I am trying to achieve but gives me an exception http://vaultofthoughts.net/LINQRowNumberColumn.aspx "An expression tree may not contain an assignment operator" In MS SQL I would just use the ROWNUMBER() function, I'm simply looking for the equivalent in LINQ.

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• MongoDB using NOT and AND together

  - by Stankalank

  I'm trying to negate an $and clause with MongoDB and I'm getting a MongoError: invalid operator: $and message back. Basically what I want to achieve is the following: query = { $not: { $and: [{institution_type:'A'}, {type:'C'}] } } Is this possible to express in a mongo query? Here is a sample collection: { "institution_type" : "A", "type" : "C" } { "institution_type" : "A", "type" : "D" } { "institution_type" : "B", "type" : "C" } { "institution_type" : "B", "type" : "D" } What I want to get back is the following: { "institution_type" : "A", "type" : "D" } { "institution_type" : "B", "type" : "C" } { "institution_type" : "B", "type" : "D" }

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• generating random enums

  - by null_radix

  How do I randomly select a value for an enum type in C++? I would like to do something like this. enum my_type(A,B,C,D,E,F,G,h,J,V); my_type test(rand() % 10); But this is illegal... there is not an implicit conversion from int to an enum type.

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• Why doesn't this inner class compile?

  - by Vincenzo

  This is my code: #include <algorithm> class A { void f() { struct CompareMe { bool operator() (int i, int j) { return i < j; } } comp; int a[] = {1, 2, 3, 4}; int found = std::min_element(a[0], a[3], comp); } } Error message: no matching function for call to ‘min_element(int&, int&, A::f()::CompareMe&) What am I doing wrong?

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• sql 2008 query. I am trying to correct this error message

  - by getbruce

  What is wrong with this code? What would be the correct syntax? SELECT EmployeeID, SUM('More than 2 orders') FROM Orders WHERE EmployeeID 2 GROUP BY EmployeeID Msg 8117, Level 16, State 1, Line 1 Operand data type varchar is invalid for sum operator.

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• Using rowDiffs() to calculate difference in values in matrix

  - by user1723765

  I'm using the rowDiffs() command to calculate the step by step difference in 116 rows in a matrix. I get the following error: Error in r[i1] - r[-length(r):-(length(r) - lag + 1L)] : non-numeric argument to binary operator I have no idea why this is happening. I could take the diff() separately for each row and it would work. Any ideas? Here's the data: https://dl.dropbox.com/u/22681355/data.csv Code: a=rowDiffs(data)

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• AS3 - Can I know if a class implements an interface (or is a subclass of another class) ?

  - by lk

  With this code function someFunction(classParam:Class):Boolean { // how to know if classParam implements some interface? } i.e. Comparing classParam with IEventDispatcher interface: someFunction(EventDispatcher) // returns true someFunction(Object) // returns false I know it can't be done with is operator. But, is there a way to do it? Is there a way to know if a class implements some interface? (or is a subclass of another class?)

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• Intermediate values in C++

  - by sterh

  Hello. I can not find how to implement a design in C++. In the language of Delphi in case the operator can write the following design: case s[j] of '0'..'9','A'..'Z','a'..'z','_': doSomeThing(); How can i do the same in c++. Attracts me is the construction type 'a' .. 'z' and etc... Thank you

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• Why does Convert.ToBoolean("0") fail?

  - by JL

  I know that trying to convert string "0" to boolean will fail, I also know how to fix this, thanks to Jon Skeets answers on other questions. What I would like to know is WHY does C# not recognize "0" as a valid input for a boolean conversion, surely you could look at it like 0 = false, 1 = true, or even -1 = false and 0 = true, anyways, my logic tells me that it could be a valid input, so is there a very good reason why its not? My bet is old vb6 would be able to recognize the string input "0" as valid.

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• Interview Question : to find a result array where ith element is the product of all other elements e

  - by frictionlesspulley

  There is an array A[N] of N numbers. You have to compose an array Output[N] such that Output[i] will be equal to multiplication of all the elements of A[N] except A[i]. For example Output[0] will be multiplication of A[1] to A[N-1] and Output[1] will be multiplication of A[0] and from A[2] to A[N-1]. Solve it without division operator and in O(n).

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• When I do ""+1 I get a String - Why

  - by steve

  Hi, Please understand firstly that I fully understand that Java will return a String when I use ""+int. What I'm really not sure about is what exactly is happening down at the memory aspect. How exactly is java performing this conversion. I mean this in a very indepth way, not 'auto boxing' or anything like that :) I'm hoping someone with a deeper understanding can explain what exactly is done.

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• Return an empty C-String

  - by Evorlor

  Simple Question: How do you return an empty C-String with as little code as possible? I have code that needs to return an empty char*. I am looking for something along the lines of return "";. I know there are several ways to do this, but I am looking for the most efficient way possible. Using return ""; gives warning: conversion from string literal to 'char *' is deprecated [-Wdeprecated-writable-strings] Thanks!

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• VC++ 6.0 application crashing inside CString::Format when %d is given.

  - by viswanathan

  A VC++ 6.0 application is crashing when doing a CString::Format operation with %d format specifier. This does not occur always but occurs when the application memory grows upto 100MB or more. ALso sometimes same crash observed when a CString copy is done. The call stack would look like this mfc42u!CFixedAlloc::Alloc+82 mfc42u!CString::AllocBuffer+3f 00000038 00000038 005b5b64 mfc42u!CString::AllocBeforeWrite+31 00000038 0a5bfdbc 005b5b64 mfc42u!CString::AssignCopy+13 00000038 057cb83f 0a5bfe90 mfc42u!CString::operator=+4b and this throws an access violation exception.

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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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• Make exact mp4 (H264) format for uploading to youtube

  - by WHITECOLOR

  With ffmpeg I'm converting video from mp3 and picture to upload it to youtube. After upload, conversion fails. Reasons are unknown. I believe the problem is in format. By the way If I'm uploading file 5 minutes length, it fails if I upload 30 seconds of this file it succeeds. I have donwload mp4 file from youtube. Then I uploaded it, it is done very fast. So a nice solution would be to convert videos to the same format that is done by google. I got the following output by mpeg: ffmpeg version N-44264-g070b0e1 Copyright (c) 2000-2012 the FFmpeg developers built on Sep 7 2012 17:38:57 with gcc 4.7.1 (GCC) configuration: --enable-gpl --enable-version3 --disable-pthreads --enable-runt ime-cpudetect --enable-avisynth --enable-bzlib --enable-frei0r --enable-libass - -enable-libcelt --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-l ibfreetype --enable-libgsm --enable-libmp3lame --enable-libnut --enable-libopenj peg --enable-librtmp --enable-libschroedinger --enable-libspeex --enable-libtheo ra --enable-libutvideo --enable-libvo-aacenc --enable-libvo-amrwbenc --enable-li bvorbis --enable-libvpx --enable-libx264 --enable-libxavs --enable-libxvid --ena ble-zlib libavutil 51. 72.100 / 51. 72.100 libavcodec 54. 55.100 / 54. 55.100 libavformat 54. 25.105 / 54. 25.105 libavdevice 54. 2.100 / 54. 2.100 libavfilter 3. 16.100 / 3. 16.100 libswscale 2. 1.101 / 2. 1.101 libswresample 0. 15.100 / 0. 15.100 libpostproc 52. 0.100 / 52. 0.100 Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'youtubetrack0.mp4': Metadata: major_brand : mp42 minor_version : 0 compatible_brands: isommp42 creation_time : 2012-10-02 22:58:57 Duration: 00:06:46.66, start: 0.000000, bitrate: 176 kb/s Stream #0:0(und): Video: h264 (Constrained Baseline) (avc1 / 0x31637661), yu v420p, 450x360, 78 kb/s, 6 fps, 6 tbr, 12 tbn, 12 tbc Metadata: creation_time : 1970-01-01 00:00:00 handler_name : VideoHandler Stream #0:1(und): Audio: aac (mp4a / 0x6134706D), 44100 Hz, stereo, s16, 95 kb/s Metadata: creation_time : 2012-10-02 22:58:57 handler_name : IsoMedia File Produced by Google, 5-11-2011 Is it possible to construct ffmpeg parameters so that that would give the same format that google internally does? Is the information above sufficient? I couldn't construct needed params. For example I don't understand how to set tbn and what 95 kb/s mean in "Stream #0:1(und): Audio:". Now I just do: ffmpeg -i videoimage.jpg -i audio.mp3 video.mp4 Info I've got: ffmpeg version N-44998-gdf82454 Copyright (c) 2000-2012 the FFmpeg developers built on Oct 2 2012 23:03:12 with gcc 4.7.1 (GCC) configuration: --disable-static --enable-shared --enable-gpl --enable-version3 --disable-pthreads --enable-runtime-cpudetect --enable-avisynth --enable-bzlib --enable-frei0r --enable-libass --enable-libcelt --enable-libopencore-amrnb --en able-libopencore-amrwb --enable-libfreetype --enable-libgsm --enable-libmp3lame --enable-libnut --enable-libopenjpeg --enable-librtmp --enable-libschroedinger - -enable-libspeex --enable-libtheora --enable-libutvideo --enable-libvo-aacenc -- enable-libvo-amrwbenc --enable-libvorbis --enable-libvpx --enable-libx264 --enab le-libxavs --enable-libxvid --enable-zlib libavutil 51. 73.101 / 51. 73.101 libavcodec 54. 63.100 / 54. 63.100 libavformat 54. 29.105 / 54. 29.105 libavdevice 54. 3.100 / 54. 3.100 libavfilter 3. 19.102 / 3. 19.102 libswscale 2. 1.101 / 2. 1.101 libswresample 0. 16.100 / 0. 16.100 libpostproc 52. 1.100 / 52. 1.100 Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'video.mp4': Metadata: major_brand : isom minor_version : 512 compatible_brands: isomiso2avc1mp41 encoder : Lavf54.25.105 Duration: 00:06:46.81, start: 0.000000, bitrate: 129 kb/s Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuvj420p, 450x360, 3392 kb/s, 25 fps, 25 tbr, 25 tbn, 50 tbc Metadata: handler_name : VideoHandler Stream #0:1(und): Audio: aac (mp4a / 0x6134706D), 44100 Hz, stereo, s16, 127 kb/s Metadata: handler_name : SoundHandler This video fails the conversion on youtube. I also tried to use other vcode parmam and extensions of output file (mp4, wmv, avi) but failed too. Would be greatful for help.

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• Convert from apache rewrite to nginx

  - by Linux Intel

  I want to convert from apache rewrite modules to nginx RewriteCond %{QUERY_STRING} mosConfig_[a-zA-Z_]{1,21}(=|\%3D) [OR] RewriteCond %{QUERY_STRING} base64_encode.*\(.*\) [OR] RewriteCond %{QUERY_STRING} (\<|%3C).*script.*(\>|%3E) [NC,OR] RewriteCond %{QUERY_STRING} GLOBALS(=|\[|\%[0-9A-Z]{0,2}) [OR] RewriteCond %{QUERY_STRING} _REQUEST(=|\[|\%[0-9A-Z]{0,2}) RewriteCond %{QUERY_STRING} SELECT(=|\[|\%[0-9A-Z]{0,2}) [OR] RewriteCond %{QUERY_STRING} UNION(=|\[|\%[0-9A-Z]{0,2}) [OR] RewriteCond %{QUERY_STRING} UPDATE(=|\[|\%[0-9A-Z]{0,2}) [OR] RewriteRule ^([^.]*)/?$ index.php [L] RewriteRule ^domain/trial/cms$ index/index.php?%{QUERY_STRING} [L] RewriteCond %{HTTP:Range} ([a-z]+) [NC] RewriteRule ([0-9_\-]+)flv$ http://www.domain.com [R,L] RewriteCond %{ENV:byte-ranges-specifier} !^$ RewriteRule ([0-9_\-]+)flv$ http://www.domain.com [R,L] RewriteCond %{HTTP_USER_AGENT} !^Mozilla/5 [NC] RewriteCond %{HTTP_USER_AGENT} !^Mozilla/4 [NC] RewriteCond %{HTTP_USER_AGENT} !^Opera [NC] RewriteRule ([0-9_\-]+)flv$ http://www.domain.com [R,L] RewriteRule ^$ index/index.php?%{QUERY_STRING} [L] RewriteCond %{SCRIPT_FILENAME} !sss.php [NC] RewriteCond %{SCRIPT_FILENAME} !m-administrator [NC] RewriteRule ^([^/^.]*)$ sss.php?encrypted=$1&%{QUERY_STRING} [L] RewriteCond %{SCRIPT_FILENAME} !sss.php [NC] RewriteCond %{SCRIPT_FILENAME} !m-administrator [NC] RewriteRule ^([^/^.]*)/([^/^.]*)$ sss.php?tab=$1&page=$2&%{QUERY_STRING} [L] RewriteCond %{SCRIPT_FILENAME} !sss.php [NC] RewriteCond %{SCRIPT_FILENAME} !m-administrator [NC] RewriteRule ^([^/^.]*)/([^/^.]*)/([^.]*)$ sss.php?tab=$1&page=$2&queryString=$3&%{QUERY_STRING} [L] RewriteCond %{SCRIPT_FILENAME} !sss.php [NC] RewriteCond %{SCRIPT_FILENAME} !security.php [NC] RewriteRule ^([^/]*)$ index/$1?%{QUERY_STRING} [L] I tried to convert it by online tools such as : http://www.anilcetin.com/convert-apache-htaccess-to-nginx/ but it didn't convert it correctly. The conversion output is : if ($args ~ "mosConfig_[a-zA-Z_]{1,21}(=|%3D)"){ set $rule_0 1; } if ($args ~ "base64_encode.*(.*)"){ set $rule_0 1; } if ($args ~* "(<|%3C).*script.*(>|%3E)"){ set $rule_0 1; } if ($args ~ "GLOBALS(=|[|%[0-9A-Z]{0,2})"){ set $rule_0 1; } if ($args ~ "_REQUEST(=|[|%[0-9A-Z]{0,2})"){ set $rule_0 1; } if ($args ~ "SELECT(=|[|%[0-9A-Z]{0,2})"){ set $rule_0 1; } if ($args ~ "UNION(=|[|%[0-9A-Z]{0,2})"){ set $rule_0 1; } if ($args ~ "UPDATE(=|[|%[0-9A-Z]{0,2})"){ set $rule_0 1; } if ($rule_0 = "1"){ rewrite ^/([^.]*)/?$ /index.php last; } if ($rule_1 = ""){ rewrite ^/domain/trial/cms$ /index/index.php?$args last; } if ($http_range ~* "([a-z]+)"){ set $rule_2 1$rule_2; } if ($rule_2 = "1"){ rewrite /([0-9_-]+)flv$ http://www.domain.com redirect; } #ignored: condition 0 if ($rule_3 = "1"){ rewrite /([0-9_-]+)flv$ http://www.domain.com redirect; } if ($http_user_agent !~* "^Mozilla/5"){ set $rule_4 1$rule_4; } if ($http_user_agent !~* "^Mozilla/4"){ set $rule_4 2$rule_4; } if ($http_user_agent !~* "^Opera"){ set $rule_4 3$rule_4; } if ($rule_4 = "321"){ rewrite /([0-9_-]+)flv$ http://www.domain.com redirect; } if ($rule_5 = ""){ rewrite ^/$ /index/index.php?$args last; } if ($uri !~* "sss.php"){ set $rule_6 1$rule_6; } if ($uri !~* "m-administrator"){ set $rule_6 2$rule_6; } if ($rule_6 = "21"){ rewrite ^/([^/^.]*)$ /sss.php?encrypted=$1&$args last; } if ($uri !~* "sss.php"){ set $rule_7 1$rule_7; } if ($uri !~* "m-administrator"){ set $rule_7 2$rule_7; } if ($rule_7 = "21"){ rewrite ^/([^/^.]*)/([^/^.]*)$ /sss.php?tab=$1&page=$2&$args last; } if ($uri !~* "sss.php"){ set $rule_8 1$rule_8; } if ($uri !~* "m-administrator"){ set $rule_8 2$rule_8; } if ($rule_8 = "21"){ rewrite ^/([^/^.]*)/([^/^.]*)/([^.]*)$ /sss.php?tab=$1&page=$2&queryString=$3&$args last; } if ($uri !~* "sss.php"){ set $rule_9 1$rule_9; } if ($uri !~* "security.php"){ set $rule_9 2$rule_9; } if ($rule_9 = "21"){ rewrite ^/([^/]*)$ /index/$1?$args last; } Please help me with the proper conversion result for nginx in order to work perfectly.

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• CodePlex Daily Summary for Sunday, September 30, 2012

  CodePlex Daily Summary for Sunday, September 30, 2012Popular ReleasesCAPTCHA Solver: Initial Release: This is the initial Release :) Still very much a WIP.MCEBuddy 2.x: MCEBuddy 2.2.17: Reccomended update to 2.2.16 Changelog for 2.2.17 (32bit and 64bit) 1. Fixed bugs around thread synchronization with new remote model (fixes cause the app to crash or hang) 2. Updated UPnP code base, faster and more reliable now 3. Now you can get audio/video properties for multiple files on main page. Selected multiple files and right click, all selected files properties will be shown. 4. Fix a bug, not able to enter a conversion task name in the GUIAggravation: Version 1.0: This version 1.0 release is pretty stable. You need the Silverlight 4 runtime, developer tools, and Experssion Blend 4 installed.Readable Passphrase Generator: KeePass Plugin 0.7.1: See the KeePass Plugin Step By Step Guide for instructions on how to install the plugin. Changes Built against KeePass 2.20Windows 8 Toolkit - Charts and More: Beta 1.0: The First Compiled Version of my LibraryPDF.NET: PDF.NET.Ver4.5-OpenSourceCode: PDF.NET Ver4.5 ????，????Web??????。 PDF.NET Ver4.5 Open Source Code,include a sample Web application project.D3 Loot Tracker: 1.4: Session name is displayed in the UI. Changes data directory for clickonce deployment so that sessions files are persisted between versions. Added a delete button in the sessions list window. Allow opening of the sessions local folder from the session list widow. Display the session name in the main window Ability to select which diablo process to hook up to when pressing new () function BUT only if multi-process support is selected in the generals settings tab menu. Session picker...CRM 2011 Visual Ribbon Editor: Visual Ribbon Editor 1.1 Beta: Visual Ribbon Editor 1.1 Beta What's New: Fixed scrolling issue in UnHide dialog Added support for connecting via ADFS / IFD Added support for more than one action for a button Added support for empty StringParameter for Javascript functions Fixed bug in rule CrmClientTypeRule when selecting Outlook option Extended Prefix field in New Button dialogVisual Studio Icon Patcher: Version 1.5.2: This version contains no new images from v1.5.1 Contains the following improvements: Better support for detecting the installed languages The extract & inject commands won’t run if Visual Studio is running You may now run in extract or inject mode The p/invoke code was cleaned up based on Code Analysis recommendations When a p/invoke method fails the Win32 error message is now displayed Error messages use red text Status messages use green textZXing.Net: ZXing.Net 0.9.0.0: On the way to a release 1.0 the API should be stable now with this version. sync with rev. 2393 of the java version improved api better Unity support Windows RT binaries Windows CE binaries new Windows Service demo new WPF demo WindowsCE Hotfix: Fixes an error with ISO8859-1 encoding and scannning of QR-Codes. The hotfix is only needed for the WindowsCE platform.C.B.R. : Comic Book Reader: CBR 0.7: Synthesis since 0.6 : ePUB : Complete refactoring Add a new dedicated feed viewer for opds stream PDF conversion : improved with image merge Make all backstage panel scrollable Integrate the new AvalonDock 2 library. Support multi-document. Library explorer and Table of content are now toolboxes Designer for dynamic books is now mvvm and much better New BrowserForControl Customized xps viewer to suppress toolbars and bind it to cbr commands Add quick start manual and button ...menu4web: menu4web 1.0 - free javascript menu for web sites: menu4web 1.0 has been tested with all major browsers: Firefox, Chrome, IE, Opera and Safari. Minified m4w.js library is less than 9K. Includes 21 menu examples of different styles. Can be freely distributed under The MIT License (MIT).Rawr: Rawr 5.0.0: This is the Downloadable WPF version of Rawr!For web-based version see http://elitistjerks.com/rawr.php You can find the version notes at: http://rawr.codeplex.com/wikipage?title=VersionNotes Rawr Addon (NOT UPDATED YET FOR MOP)We now have a Rawr Official Addon for in-game exporting and importing of character data hosted on Curse. The Addon does not perform calculations like Rawr, it simply shows your exported Rawr data in wow tooltips and lets you export your character to Rawr (including ba...Coevery - Free CRM: Coevery 1.0.0.26: The zh-CN issue has been solved. We also add a project management module.VidCoder: 1.4.1 Beta: Updated to HandBrake 4971. This should fix some issues with stuck PGS subtitles. Fixed build break which prevented pre-compiled XML serializers from showing up. Fixed problem where a preset would get errantly marked as modified when re-opening the encode settings window or importing a new preset.Snake!: Snake 1.0: Version 1 StablePaging SharePoint ListItems using listitems position: Paginglistitems V1.0: This is a console application which has two methods both on CSOM and SOM to display the listitems in a paged manner.SharePoint Move Discussion Threads: SharePoint Move Discussion Threads ver 0.1: ver 0.1NTCPMSG: V1.1.1.0: increase the performance. Support .net framework 4.0.BlackJumboDog: Ver5.7.2: 2012.09.23 Ver5.7.2 (1)InetTest?? (2)HTTP?????????????????100???????????New Projects2D Sprite Editor: This is a 2d sprite editor. Import your sprite sheet, trace your animations frame and export the coordinates points in a simple txt file, ready to import.caifenweb1: test project.CatchThatException: This is a small logging library We created at developerpath.com to help us log exceptions. It write it to a text file and you can easilay open that txt.FsxWs - WebServices for Microsoft FSX: WebServices for MS Flight Simulator. Get flights data as JSON, KML. !! Still in SetUp phase - be patient !!GetTPB: Some training in downloading and parsing web pages, with multithreading too.JSON-RPC Client Generator (for XBMC): The goal of this project is to provide a .Net client for the XBMC JSONRPC API. The main part is not XBMC dependent and may be used for any JSON-RPC client.matlab-silhouette-pose-wtf: Whatevermfp: this is random codeMVC Grid: MVC Grid ExampleMyWebSocketTry: sssssssssssssssssssssssssssssssssssssssNetduino Console: Netduino Console is an interface with built in messaging layers that allows you as a developer to dynamically create plugins following a provided interface to iSharePoint ASP.NET Verifier: Project will allow to verify SharePoint 2010 components using ASP.NET web applicationSharepoint Custom Upload: This is a SharePoint solution that allows an administrator to customize the upload page individually for each document library in a site.. It allows you to makeWinWeb Browser Deluxe: WinWeb Browser Deluxe es un navegador web de código abierto basado en Internet Explorer hecho en Visual Basic .NET. Descargalo ya!writethatoutput: This is the official release page for WriteThatOutPut from developerpath.com

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• Preserving Permalinks

  - by Daniel Moth

  One of the things that gets me on a rant is websites that break permalinks. If you have posted something somewhere and there is a public URL pointing to it, that URL should never ever return a 404. You are breaking all websites that ever linked to you and you are breaking all search engine links to your content (that others will try and follow). It is a pet peeve of mine. So when I had to move my blog, obviously I would preserve the root URL (www.danielmoth.com/Blog/), but I also wanted to preserve every URL my blog has generated over the years. To be clear, our focus here is on the URL formatting, not the content migration which I'll talk about in my next post. In this post, I'll describe my solution first and then what it solves. 1. The IIS7 Rewrite Module and web.config There are a few ways you can map an old URL to a new one (so when requests to the old URL come in, they get redirected to the new one). The new blog engine I use (dasBlog) has built-in functionality to do that (Scott refers to it here). Instead, the way I chose to address the issue was to use the IIS7 rewrite module. The IIS7 rewrite module allows redirecting URLs based on pattern matching, regular expressions and, of course, hardcoded full URLs for things that don't fall into any pattern. You can configure it visually from IIS Manager using a handy dialog that allows testing patterns against input URLs. Here is what mine looked like after configuring a few rules: To learn more about this technology check out this video, the reference page and this overview blog post; all 3 pages have a collection of related resources at the bottom worth checking out too. All the visual configuration ends up in a web.config file at the root folder of your website. If you are on a shared hosting service, probably the only way you can use the Rewrite Module is by directly editing the web.config file. Next, I'll describe the URLs I had to map and how that manifested itself in the web.config file. What I did was create the rules locally using the GUI, and then took the generated web.config file and uploaded it to my live site. You can view my web.config here. 2. Monthly Archives Observe the difference between the way the two blog engines generate this type of URL Blogger: /Blog/2004_07_01_mothblog_archive.html dasBlog: /Blog/default,month,2004-07.aspx In my web.config file, the rule that deals with this is the one named "monthlyarchive_redirect". 3. Categories Observe the difference between the way the two blog engines generate this type of URL Blogger: /Blog/labels/Personal.html dasBlog: /Blog/CategoryView,category,Personal.aspx In my web.config file the rule that deals with this is the one named "category_redirect". 4. Posts Observe the difference between the way the two blog engines generate this type of URL Blogger: /Blog/2004/07/hello-world.html dasBlog: /Blog/Hello-World.aspx In my web.config file the rule that deals with this is the one named "post_redirect". Note: The decision is taken to use dasBlog URLs that do not include the date info (see the description of my Appearance settings). If we included the date info then it would have to include the day part, which blogger did not generate. This makes it impossible to redirect correctly and to have a single permalink for blog posts moving forward. An implication of this decision, is that no two blog posts can have the same title. The tool I will describe in my next post (inelegantly) deals with duplicates, but not with triplicates or higher. 5. Unhandled by a generic rule Unfortunately, the two blog engines use different rules for generating URLs for blog posts. Most of the time the conversion is as simple as the example of the previous section where a post titled "Hello World" generates a URL with the words separated by a hyphen. Some times that is not the case, for example: /Blog/2006/05/medc-wrap-up.html /Blog/MEDC-Wrapup.aspx or /Blog/2005/01/best-of-moth-2004.html /Blog/Best-Of-The-Moth-2004.aspx or /Blog/2004/11/more-windows-mobile-2005-details.html /Blog/More-Windows-Mobile-2005-Details-Emerge.aspx In short, blogger does not add words to the title beyond ~39 characters, it drops some words from the title generation (e.g. a, an, on, the), and it preserve hyphens that appear in the title. For this reason, we need to detect these and explicitly list them for redirects (no regular expression can help here because the full set of rules is not listed anywhere). In my web.config file the rule that deals with this is the one named "Redirect rule1 for FullRedirects" combined with the rewriteMap named "StaticRedirects". Note: The tool I describe in my next post will detect all the URLs that need to be explicitly redirected and will list them in a file ready for you to copy them to your web.config rewriteMap. 6. C# code doing the same as the web.config I wrote some naive code that does the same thing as the web.config: given a string it will return a new string converted according to the 3 rules above. It does not take into account the 4th case where an explicit hard-coded conversion is needed (the tool I present in the next post does take that into account). static string REGEX_post_redirect = "[0-9]{4}/[0-9]{2}/([0-9a-z-]+).html"; static string REGEX_category_redirect = "labels/([_0-9a-z-% ]+).html"; static string REGEX_monthlyarchive_redirect = "([0-9]{4})_([0-9]{2})_[0-9]{2}_mothblog_archive.html"; static string Redirect(string oldUrl) { GroupCollection g; if (RunRegExOnIt(oldUrl, REGEX_post_redirect, 2, out g)) return string.Concat(g[1].Value, ".aspx"); if (RunRegExOnIt(oldUrl, REGEX_category_redirect, 2, out g)) return string.Concat("CategoryView,category,", g[1].Value, ".aspx"); if (RunRegExOnIt(oldUrl, REGEX_monthlyarchive_redirect, 3, out g)) return string.Concat("default,month,", g[1].Value, "-", g[2], ".aspx"); return string.Empty; } static bool RunRegExOnIt(string toRegEx, string pattern, int groupCount, out GroupCollection g) { if (pattern.Length == 0) { g = null; return false; } g = new Regex(pattern, RegexOptions.IgnoreCase | RegexOptions.Compiled).Match(toRegEx).Groups; return (g.Count == groupCount); } Comments about this post welcome at the original blog.

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• CodePlex Daily Summary for Thursday, April 15, 2010

  CodePlex Daily Summary for Thursday, April 15, 2010New ProjectsApplication Logging Repository (ALR): The ALR is a light-weight logging framework that allows applications to log events and exceptions to a central repository.Arkane.FileProperties.DSS: Arkane.FileProperties.Dss is a library for parsing the file header of a .DSS file (as used by Olympus digital dictaphone systems) to obtain time, v...B in conTrol project: This project enables controling log-in and locking your workstation automatically, identifyng you bluetooth.DarkBook: DarkBook is a personal library project.Direct2D for Microsoft .Net: Direct2D, DirectWrite and Windows Imaging wrappers for .Net. This library allows to access Direct2D, DirectWrite and Windows Imaging Windows API f...DJ Ware: DJ Ware is an extensible music player with plugin support and innovative features to organize and explore music files. It is developed with C#, WPF...gpsMe: gpsMe is a Windows Mobile 6.x mapping solution allowing to place the user on a personnalized map. The screen requirements are VGA or WVGA but, you ...jErrorLog: jErrorLog is an error logging component for use in DotNet 2.0 or later applications. It can log error messages to any of the following: database, e...KEMET_API: Java Library (open - source). This library is a help to study egyptian hieroglyphs.Meadow: A web site project for a Swedish floorball team called Slackers. Home page built with ASP.NET 2.0, ASP.NET AJAX and SQL Server 2005.Mustang Math: Mustang Math makes it easier for young children to practice basic math facts on the computer. No keyboard or mouse required - just say the answer!...Net.Formats.oEmbed: oEmbed format implementation in c#. oEmbed is a format for allowing an embedded representation of a URL on third party sites. The simple API allows...Normlize O/R Mapper: Open source O/RM tool that participates with traditional inheritance object models as well as Hibernate/nHibernate style class shells. As I have t...N-Twill Twitter Client for VB.NET: Proyecto de cliente twitter hecho con la libreria TwitterVB2 y hecho en VB.net 2008.SIQM: Spatial Information Quality Management Toolset TIMETABLEASY Web: Under developmentTweetSharp: TweetSharp is a complete .NET library for micro-blogging platforms that allows you to write short and sweet expressions that fly to Twitter, Yammer...UISandbox: UISandbox is a sample C# source code showing how to deal with plugins requiring sandbox, when those plugins must interact with WPF application inte...WinForm SharePoint Web Part Manager: The SharePoint Web Part Manager is a WinForm tool using the SharePoint object model that enables developers and power users to add, update, delete,...WoW Character Viewer: View your World of Warcraft character (or anyone else's character), using this application. Written using Visual Basic Express 2008, then ported t...Xrns2XMod: Xrns2XMod converts from Renoise format (xrns) to mod or xm, which are more compatible formats playable from xmplay or vlc.New ReleasesArkane.FileProperties.DSS: 1.0 stable release: Executables and merge module for 1.0. (See documentation.)Bluetooth Radar: Version 2.0: Add IrDA reference for Bluetooth sending using Obex Add Project icon Add Bluetooth detection mode (Auto close application is there is no blueto...BUtil: BUtil 5.0 Alpha: Backup tasks adding.... in progressChronos WPF: Chronos v1.0 RC 1: Chronos v1.0 RC 1. Development will be feature frozen after this release, only bug fixes will be allowed. Updated nRoute assembly to v0.4 (http:...clipShow: Version 2.5: Release that addresses the canonical syntax issues in search discoverd by Tschachim (thanks again!). Also, the play list and play all menu items s...DarkBook: DarkBook alpha: Hi, here comes the alpha version of Darkbook. It has all the functions already but is still in developing. I hope it's helpful for you, at least it...DirectQ: Release 1.8.3a: Improvements to 1.8.2, which will be shortly be removed. This replaces the original 1.8.3 release from earlier today which had some late-breaking ...Effect Custom Tool for Visual Studio: Effect Custom Tool v1.1: Effect Custom Tool for Visual Studio is a visual studio 2008 extension that helps you generate c# classes from effect (*.fx) files for use with Xna...Folder Bookmarks: Folder Bookmarks 1.4.3: This is the latest version of Folder Bookmarks (1.4.3), with general improvements. It has an installer - it will create a directory 'CPascoe' in My...gpsMe: gpsMe v0.3: Required Hardware Windows Mobile 6 .Net Compact Framework 3.5 integrated gps device VGA or WVGA screen (normally works on others)IST435: Lab 4 - Enterprise Level CMS with DotNetNuke: Lab 4 - Enterprise Level CMS with DotNetNukeThis is the "starter kit" that you must base your Lab 4 on. This lab must be completed in-class.Mouse Jiggler: MouseJiggle-1.1: 1.1 release of Mouse Jiggler, now with x64 compatibility and the ability to start jiggling on run with the --jiggle or -j command-line switch.Mustang Math: MustangMath.exe: This is a quick and dirty "0.1" prototype to demonstrate the speech recognition idea. It starts asking you questions automatically on launch and k...MvcContrib: a Codeplex Foundation project: 2.0.36.0 for MVC2 (RTW): Please see the Change Log for a complete list of changes. MVC BootCamp Description of the releases: MvcContrib.Release.zip MvcContrib.dll MvcC...Nito.LINQ: Beta (v0.3): New features for this release: Several new supported platforms (see below). PDBs that are source-indexed to the appropriate CodePlex changeset. ...OpenIdPortableArea: 0.1.0.2 OpenIdPortableArea: OpenIdPortableArea.Release: DotNetOpenAuth.dll DotNetOpenAuth.xml MvcContrib.dll MvcContrib.xml OpenIdPortableArea.dll OpenIdPortableAre...PokeIn Comet Ajax Library: PokeIn Sample with Library v0.2: New version of PokeIn library with sample. v0.2 There are new features in this release and no bug detected yet.Project Tru Tiên: Elements-test V1-fix (v2): Là EL test được fix tiếp theo bản fix V1, tạm gọi đây là bản fix V2 của ELtest Trong bản fix này EL được fix thêm vụ Quest, Quest chỉnh sửa đúng t...Rule 18 - Love your clipboard: Rule 18: This is the third public beta for the first version of Rule 18. This version has been updated to support Visual Studio 2010 RTM and .NET 4.0 RTM. ...SevenZipSharp: SevenZipSharp 0.62: Added: Extraction from SFX archives. Now it is possible to unrar RAR self-extractors, unzip ZIP self-extractors, etc. Extraction from DOC, XLS, (...SharePoint Labs: SPLab3001A-FRA-Level200: SPLab3001A-FRA-Level200 This SharePoint Lab will teach the persistence object layer that SharePoint uses to centraly store configuration data and o...TTXPathNavigator: TTXPathNavigator for VS2010: Version for Visual Studio 2010turing machine simulator: SDS: SDS documentVecDraw: VecDraw_0.2.25: Alpha release for test purposesWinForm SharePoint Web Part Manager: Beta 1: First release of the WinForm SharePoitn web part manager toolXrns2XMod: Xrns2XMod 0.5.1: Mod and XM conversion format - No sample data conversion at momentZip Solution: ZipSolution 5.3: Features: 1. Added WaitMsec for visual studio support with getting access to files in post build event; 2. Added ShowTextInToolbars to app.config ...Most Popular ProjectsRawrWBFS ManagerAJAX Control ToolkitMicrosoft SQL Server Product Samples: DatabaseSilverlight ToolkitWindows Presentation Foundation (WPF)ASP.NETMicrosoft SQL Server Community & SamplesPHPExcelpatterns & practices – Enterprise LibraryMost Active ProjectsRawrpatterns & practices – Enterprise LibraryGMap.NET - Great Maps for Windows Forms & PresentationFarseer Physics EngineIonics Isapi Rewrite FilterNB_Store - Free DotNetNuke Ecommerce Catalog ModuleBlogEngine.NETjQuery Library for SharePoint Web ServicesDotRasFacebook Developer Toolkit

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• The blocking nature of aggregates

  - by Rob Farley

  I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

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• The blocking nature of aggregates

  - by Rob Farley

  I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

  Read the article

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