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  • how do i ininitialize a float to it's max/min value?

    - by Faken
    How do i hard code an absolute maximum or minimum value for a float or double? I want to search out the max/min of an array by simply iterating through and catching the largest. There are also positive and negative infinity for floats, should i use those instead? if so, how do i denote that in my code?

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  • how do I initialize a float to its max/min value?

    - by Faken
    How do I hard code an absolute maximum or minimum value for a float or double? I want to search out the max/min of an array by simply iterating through and catching the largest. There are also positive and negative infinity for floats, should I use those instead? If so, how do I denote that in my code?

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  • Magento - How to select mysql rows by max value?

    - by Damodar Bashyal
    mysql> SELECT * FROM `log_customer` WHERE `customer_id` = 224 LIMIT 0, 30; +--------+------------+-------------+---------------------+-----------+----------+ | log_id | visitor_id | customer_id | login_at | logout_at | store_id | +--------+------------+-------------+---------------------+-----------+----------+ | 817 | 50139 | 224 | 2011-03-21 23:56:56 | NULL | 1 | | 830 | 52317 | 224 | 2011-03-27 23:43:54 | NULL | 1 | | 1371 | 136549 | 224 | 2011-11-16 04:33:51 | NULL | 1 | | 1495 | 164024 | 224 | 2012-02-08 01:05:48 | NULL | 1 | | 2130 | 281854 | 224 | 2012-11-13 23:44:13 | NULL | 1 | +--------+------------+-------------+---------------------+-----------+----------+ 5 rows in set (0.00 sec) mysql> SELECT * FROM `customer_entity` WHERE `entity_id` = 224; +-----------+----------------+---------------------------+----------+---------------------+---------------------+ | entity_id | entity_type_id | email | group_id | created_at | updated_at | +-----------+----------------+---------------------------+----------+---------------------+---------------------+ | 224 | 1 | [email protected] | 3 | 2011-03-21 04:59:17 | 2012-11-13 23:46:23 | +-----------+----------------+---------------------------+----------+--------------+----------+-----------------+ 1 row in set (0.00 sec) How can i search for customers who hasn't logged in for last 10 months and their account has not been updated for last 10 months. I tried below but failed. $collection = Mage::getModel('customer/customer')->getCollection(); $collection->getSelect()->joinRight(array('l'=>'log_customer'), "customer_id=entity_id AND MAX(l.login_at) <= '" . date('Y-m-d H:i:s', strtotime('10 months ago')) . "'")->group('e.entity_id'); $collection->addAttributeToSelect('*'); $collection->addFieldToFilter('updated_at', array( 'lt' => date('Y-m-d H:i:s', strtotime('10 months ago')), 'datetime'=>true, )); $collection->addAttributeToFilter('group_id', array( 'neq' => 5, )); Above tables have one customer for reference. I have no idea how to use MAX() on joins. Thanks UPDATE: This seems returning correct data, but I would like to do magento way using resource collection, so i don't need to do load customer again on for loop. $read = Mage::getSingleton('core/resource')->getConnection('core_read'); $sql = "select * from ( select e.*,l.login_at from customer_entity as e left join log_customer as l on l.customer_id=e.entity_id group by e.entity_id order by l.login_at desc ) as l where ( l.login_at <= '".date('Y-m-d H:i:s', strtotime('10 months ago'))."' or ( l.created_at <= '".date('Y-m-d H:i:s', strtotime('10 months ago'))."' and l.login_at is NULL ) ) and group_id != 5"; $result = $read->fetchAll($sql); I have loaded full shell script to github https://github.com/dbashyal/Magento-ecommerce-Shell-Scripts/blob/master/shell/suspendCustomers.php

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  • How to modify the attributes by putting dynamic node paths

    - by sam
    I have a code that selects all elements and their child nodes DECLARE @x XML DECLARE @node_no int DECLARE @count int DECLARE @max INT, @i INT EXECUTE return_xml '1', NULL, @x output Declare @temp Table ( id int not null identity(1,1), ParentNodeName varchar(max), NodeName varchar(max), NodeText varchar(max) ) INSERT INTO @temp SELECT t.c.value('local-name(..)', 'varchar(max)') AS ParentNodeName, t.c.value('local-name(.)', 'varchar(max)') AS NodeName, t.c.value('text()[1]', 'varchar(max)') AS NodeText FROM @x.nodes('/booking//*') AS t(c) select * from @temp Now I want to modify the attributs by putting dynamic node paths SET @x.modify (' insert attribute MyId {sql:variable("@i")} as first into (ParentNodeName/NodeName::*[position() = sql:variable("@i")])[1] ') where id = id of temp table any Idea how can I modify my whole xml this way as I am having a untyped xml and have to add an attribute in every node

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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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  • what is the best setting for using lighttpd on 8G ram?

    - by user39639
    I have running 8GB ram and 8 x Xeon 3361 system! What is the best setting for running simultaneous connection! What is the maximum? Is setting like this correct? server.max-keep-alive-requests = 0 server.max-keep-alive-idle = 10 server.max-read-idle = 60 server.max-write-idle = 60 server.event-handler = "linux-sysepoll" server.max-fds = 2048 fastcgi.server = ( ".php" = ( "localhost" = ( "socket" = "/tmp/php-fastcgi.socket", "bin-path" = "/usr/bin/php-cgi", "max-procs" = 20, "bin-environment" = ( "PHP_FCGI_CHILDREN" = "40", "PHP_FCGI_MAX_REQUESTS" = "800" ), "broken-scriptfilename" = "enable" ) ) ) please help me!

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  • Slow dvd burning/reading speeds: how to solve

    - by wouter205
    I have a problem on which I'm struggling since i started using linux a year ago on my desktop, but still haven't found a solution for it. When reading or burning a dvd, the speeds are very slow (mostly under 1x) whilst I did selected the fastest speed in k3b. As such, it takes up to 40-50 minutes to burn one dvd! I read about enabling dma this post but it didn't help. This is the output for dmesg | grep -i dma > [ 0.000000] DMA 0x00000010 -> 0x00001000 [ 0.000000] DMA32 0x00001000 -> 0x00100000 [ 0.000000] DMA zone: 56 pages used for memmap [ 0.000000] DMA zone: 5 pages reserved [ 0.000000] DMA zone: 3921 pages, LIFO batch:0 [ 0.000000] DMA32 zone: 3527 pages used for memmap [ 0.000000] DMA32 zone: 254441 pages, LIFO batch:31 [ 0.000000] Policy zone: DMA32 [ 0.120356] pnp 00:01: [dma 4] [ 0.120968] pnp 00:05: [dma 2] [ 0.121421] pnp 00:06: [dma 3] [ 0.122617] pnp 00:0b: [dma 0 disabled] [ 0.852321] ata1: SATA max UDMA/133 cmd 0xec00 ctl 0xe480 bmdma 0xe000 irq 19 [ 0.852325] ata2: SATA max UDMA/133 cmd 0xe400 ctl 0xe080 bmdma 0xe008 irq 19 [ 0.861633] ata3: PATA max UDMA/133 cmd 0x1f0 ctl 0x3f6 bmdma 0xff00 irq 14 [ 0.861636] ata4: PATA max UDMA/133 cmd 0x170 ctl 0x376 bmdma 0xff08 irq 15 [ 1.329411] ata1.00: ATA-7: Maxtor 6V250F0, VA111630, max UDMA/133 [ 1.345418] ata1.00: configured for UDMA/133 [ 1.820606] ata4.00: ATAPI: PHILIPS DVDR1660P1, P1.3, max UDMA/33 [ 1.820610] ata4.00: WARNING: ATAPI DMA disabled for reliability issues. It can be enabled [ 1.820613] ata4.00: WARNING: via pata_ali.atapi_dma modparam or corresponding sysfs node. [ 1.836681] ata4.00: configured for UDMA/33 [ 12.296600] parport0: PC-style at 0x378 (0x778), irq 7, dma 3 [PCSPP,TRISTATE,COMPAT,EPP,ECP,DMA] reading the third and fourth last line, I assume there is indeed a problem with dma? edit: this question still is not solved. Could anyone come up with an other solution please? Thanks

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  • Why is the remove function not working for hashmaps? [migrated]

    - by John Marston
    I am working on a simple project that obtains data from an input file, gets what it needs and prints it to a file. I am basically getting word frequency so each key is a string and the value is its frequency in the document. The problem however, is that I need to print out these values to a file in descending order of frequency. After making my hashmap, this is the part of my program that sorts it and writes it to a file. //Hashmap I create Map<String, Integer> map = new ConcurrentHashMap<String, Integer>(); //function to sort hashmap while (map.isEmpty() == false){ for (Entry<String, Integer> entry: map.entrySet()){ if (entry.getValue() > valueMax){ max = entry.getKey(); System.out.println("max: " + max); valueMax = entry.getValue(); System.out.println("value: " + valueMax); } } map.remove(max); out.write(max + "\t" + valueMax + "\n"); System.out.println(max + "\t" + valueMax); } When I run this i get: t 9 t 9 t 9 t 9 t 9 .... so it appears the remove function is not working as it keeps getting the same value. I'm thinking i have an issue with a scope rule or I just don't understand hashmaps very well. If anyone knows of a better way to sort a hashmap and print it, I would welcome a suggestion. thanks

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  • Code Contracts: Unit testing contracted code

    - by DigiMortal
    Code contracts and unit tests are not replacements for each other. They both have different purpose and different nature. It does not matter if you are using code contracts or not – you still have to write tests for your code. In this posting I will show you how to unit test code with contracts. In my previous posting about code contracts I showed how to avoid ContractExceptions that are defined in code contracts runtime and that are not accessible for us in design time. This was one step further to make my randomizer testable. In this posting I will complete the mission. Problems with current code This is my current code. public class Randomizer {     public static int GetRandomFromRangeContracted(int min, int max)     {         Contract.Requires<ArgumentOutOfRangeException>(             min < max,             "Min must be less than max"         );           Contract.Ensures(             Contract.Result<int>() >= min &&             Contract.Result<int>() <= max,             "Return value is out of range"         );           var rnd = new Random();         return rnd.Next(min, max);     } } As you can see this code has some problems: randomizer class is static and cannot be instantiated. We cannot move this class between components if we need to, GetRandomFromRangeContracted() is not fully testable because we cannot currently affect random number generator output and therefore we cannot test post-contract. Now let’s solve these problems. Making randomizer testable As a first thing I made Randomizer to be class that must be instantiated. This is simple thing to do. Now let’s solve the problem with Random class. To make Randomizer testable I define IRandomGenerator interface and RandomGenerator class. The public constructor of Randomizer accepts IRandomGenerator as argument. public interface IRandomGenerator {     int Next(int min, int max); }   public class RandomGenerator : IRandomGenerator {     private Random _random = new Random();       public int Next(int min, int max)     {         return _random.Next(min, max);     } } And here is our Randomizer after total make-over. public class Randomizer {     private IRandomGenerator _generator;       private Randomizer()     {         _generator = new RandomGenerator();     }       public Randomizer(IRandomGenerator generator)     {         _generator = generator;     }       public int GetRandomFromRangeContracted(int min, int max)     {         Contract.Requires<ArgumentOutOfRangeException>(             min < max,             "Min must be less than max"         );           Contract.Ensures(             Contract.Result<int>() >= min &&             Contract.Result<int>() <= max,             "Return value is out of range"         );           return _generator.Next(min, max);     } } It seems to be inconvenient to instantiate Randomizer now but you can always use DI/IoC containers and break compiled dependencies between the components of your system. Writing tests for randomizer IRandomGenerator solved problem with testing post-condition. Now it is time to write tests for Randomizer class. Writing tests for contracted code is not easy. The main problem is still ContractException that we are not able to access. Still it is the main exception we get as soon as contracts fail. Although pre-conditions are able to throw exceptions with type we want we cannot do much when post-conditions will fail. We have to use Contract.ContractFailed event and this event is called for every contract failure. This way we find ourselves in situation where supporting well input interface makes it impossible to support output interface well and vice versa. ContractFailed is nasty hack and it works pretty weird way. Although documentation sais that ContractFailed is good choice for testing contracts it is still pretty painful. As a last chance I got tests working almost normally when I wrapped them up. Can you remember similar solution from the times of Visual Studio 2008 unit tests? Cannot understand how Microsoft was able to mess up testing again. [TestClass] public class RandomizerTest {     private Mock<IRandomGenerator> _randomMock;     private Randomizer _randomizer;     private string _lastContractError;       public TestContext TestContext { get; set; }       public RandomizerTest()     {         Contract.ContractFailed += (sender, e) =>         {             e.SetHandled();             e.SetUnwind();               throw new Exception(e.FailureKind + ": " + e.Message);         };     }       [TestInitialize()]     public void RandomizerTestInitialize()     {         _randomMock = new Mock<IRandomGenerator>();         _randomizer = new Randomizer(_randomMock.Object);         _lastContractError = string.Empty;     }       #region InputInterfaceTests     [TestMethod]     [ExpectedException(typeof(Exception))]     public void GetRandomFromRangeContracted_should_throw_exception_when_min_is_not_less_than_max()     {         try         {             _randomizer.GetRandomFromRangeContracted(100, 10);         }         catch (Exception ex)         {             throw new Exception(string.Empty, ex);         }     }       [TestMethod]     [ExpectedException(typeof(Exception))]     public void GetRandomFromRangeContracted_should_throw_exception_when_min_is_equal_to_max()     {         try         {             _randomizer.GetRandomFromRangeContracted(10, 10);         }         catch (Exception ex)         {             throw new Exception(string.Empty, ex);         }     }       [TestMethod]     public void GetRandomFromRangeContracted_should_work_when_min_is_less_than_max()     {         int minValue = 10;         int maxValue = 100;         int returnValue = 50;           _randomMock.Setup(r => r.Next(minValue, maxValue))             .Returns(returnValue)             .Verifiable();           var result = _randomizer.GetRandomFromRangeContracted(minValue, maxValue);           _randomMock.Verify();         Assert.AreEqual<int>(returnValue, result);     }     #endregion       #region OutputInterfaceTests     [TestMethod]     [ExpectedException(typeof(Exception))]     public void GetRandomFromRangeContracted_should_throw_exception_when_return_value_is_less_than_min()     {         int minValue = 10;         int maxValue = 100;         int returnValue = 7;           _randomMock.Setup(r => r.Next(10, 100))             .Returns(returnValue)             .Verifiable();           try         {             _randomizer.GetRandomFromRangeContracted(minValue, maxValue);         }         catch (Exception ex)         {             throw new Exception(string.Empty, ex);         }           _randomMock.Verify();     }       [TestMethod]     [ExpectedException(typeof(Exception))]     public void GetRandomFromRangeContracted_should_throw_exception_when_return_value_is_more_than_max()     {         int minValue = 10;         int maxValue = 100;         int returnValue = 102;           _randomMock.Setup(r => r.Next(10, 100))             .Returns(returnValue)             .Verifiable();           try         {             _randomizer.GetRandomFromRangeContracted(minValue, maxValue);         }         catch (Exception ex)         {             throw new Exception(string.Empty, ex);         }           _randomMock.Verify();     }     #endregion        } Although these tests are pretty awful and contain hacks we are at least able now to make sure that our code works as expected. Here is the test list after running these tests. Conclusion Code contracts are very new stuff in Visual Studio world and as young technology it has some problems – like all other new bits and bytes in the world. As you saw then making our contracted code testable is easy only to the point when pre-conditions are considered. When we start dealing with post-conditions we will end up with hacked tests. I hope that future versions of code contracts will solve error handling issues the way that testing of contracted code will be easier than it is right now.

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  • Getting around the Max String size in a vba function?

    - by Ommit
    The max number of characters you can use in string in a vba function is 255. I am trying to run this function Var1= 1 Var2= 2 . . . Var256 =256 RunMacros= "'Tims_pet_Robot """ & Var1 & """ , """ & Var2 & """ , """ ... """ & Var256 """ '" Runat=TimeValue("15:00:00") Application.OnTime EarliestTime:=Runat, Procedure:=RunMacros & RunMacros2 ', schedule:=True It runs a procedure at a certain time and passes a bunch of variables to it. but the string is too long.

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  • How To Get A Field Value Based On The Max Of Another Field In VFP v8.0

    - by DaveB
    So, I have a table and I want to get the value from one field in the record with the greatest DateTime() value in another field and where still another field is equal to a certain value. Example data: Balance Created MeterNumber 7924.252 02/02/2010 10:31:48 AM 2743800 7924.243 02/02/2010 11:01:37 AM 2743876 7924.227 02/02/2010 03:55:50 PM 2743876 I want to get the balance for a record with the greatest created datetime for a specific meter number. In VFP 7 I can use: SELECT a.balance ,MAX(a.created) FROM MyTable a WHERE a.meternumber = '2743876' But, in the VFP v8.0 OleDb driver I am using in my ASP.NET page I must conform to VFP 8 which says you must have a GROUP BY listing each non aggregate field listed in the SELECT. This would return a record for each balance if I added GROUP BY a.balance to my query. Yes, I could issue a SET ENGINEBEHAVIOR 70 but I wanted to know if this could be done without having to revert to a previous version?

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  • Is there a faster method then StringBuilder for a max 9-10 step string concatenation?

    - by Pentium10
    I have this code to concate some array elements: StringBuilder sb = new StringBuilder(); private RatedMessage joinMessage(int step, boolean isresult) { sb.delete(0, sb.length()); for (int i = 0; i <= step; i++) { if (mStack[i] == null) continue; rm = mStack[i].getCurrentMsg(); if (rm == null || rm.msg.length() == 0) continue; if (sb.length() != 0) { sb.append(", "); } sb.append(rm.msg); } return sb.toString(); } Important the array holds max 10 items, so it's not quite much. My trace output tells me this method is called 18864 times, 16% of the runtime was spent in this method. Can I optimize more?

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  • CSS or JS max. character <h2> and replace end with "..."

    - by cr0z3r
    Hey I assume my title basically summed it all up. I have a <h2> title, and I want it to have a max character property, be it CSS or javascript, so that whenever this maximum limit is passed, the title's end is replaced by ... (three dots). Thank you very much in advance. An example can be viewed here: http://themeforest.net/forums/thread/now-accepting-bargain-submissions/23205 (see the title) P.S. Any idea why I had to create a new user? the login-feature through google doesn't recognize my previous user :(

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  • Why isn't this smbmount attempt working?

    - by Max Williams
    I can successfully access one of our local samba shares, which is on a windows pc (called marina) as follows: $ sudo /usr/bin/smbclient \\\\marina\\resource_library <my password> Domain=[MARINA] OS=[Windows 5.1] Server=[Windows 2000 LAN Manager] smb: \> So, that works. I'm now trying to mount the above location (the resource_library folder on marina) to /mnt/resource_library (as a read only folder), but it keeps failing - i've tried a few variations of specifying the location: $ sudo smbmount \\\\marina\\resource_library /mnt/resource_library -o username=max,password=<my password>,r mount error: could not resolve address for marina: No address associated with hostname No ip address specified and hostname not found and $ sudo smbmount //marina/resource_library /mnt/resource_library -o username=max,password=<my password>,r mount error: could not resolve address for marina: No address associated with hostname No ip address specified and hostname not found and both of the above with MARINA instead of marina. It's bound to be some dumb mistake i'm making, can anyone see it? cheers, max

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