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  • Confusion about TCP packet analysis terms

    - by Berkay
    I'm analyzing our network and have some confusion about the terms: this is the 2-packet output from source to destination. from these i have to get some features as describe, pls make me clear... packets with at least a bytes of TCP data payload: it seems tcp.len0; The minimum segment size (confusion is headers are included or or not) The average segment size observed during the lifetime of the connection, the definition: is calculated as the value reported in the actual data bytes divided by the actual data pkts reported. Total bytes in IP packets, should be ip_len value. Total bytes in (Ethernet) The total number of bytes sent probably related to frame.len and frame.cap_len these two terms are describes as, also make me clear about these two terms. frame.cap_len: Frame length stored into the capture file frame.len: Frame length on the wire

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  • How do I change the format of group by data in Excel 2003 pivot tables

    - by Bernard
    I have a data that lists the value of a contract per contract number. So I've created a pivot table that counts the number of contracts valued at 0 - 10, 11 - 20, etc. I want to be able to format the group, e.g. $0 - $10, $11 - $20 I've tried formatting the underlying data as currency and formatting the column in the pivot table, but it still shows as 0 - 10, 11 - 20 Also I have a column in the pivot table that says Total which is the Count of the number of contracts in that range, i.e. Value Total 0 - 10 1 11 - 20 1 Its an autogenerated column heading that Excel put in. How do I change this to say Number of contracts. I want it changed because when I chart the pivot table, the series is called called Total :(

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  • how do i search from php file ?

    - by Tum Bin
    Dear Friends, im totally new in php. Just learning. I got 2 Assingment with php and html. Assignment 01: I have to mansion some pplz name and all of them some friends name. and I have to print common friend if there have common friend. Bt there have a prob that I got also msg which dnt have any common friend like “Rana has 0 friends in common with Roni.” I want to stop this and how can i? Assignment 02: I made a html form to search a person from that php file. Like: when I will search for Rana php form will b open and and print : Rana have 4 friends and he has a common friend with Nandini and Mamun. when I will search for Tanmoy the page will be open and print: Tonmoy is Rana’s friend who have 4 friend and common friends with Nandini and Mamun. for this I have to use the function “post/get/request” Plz plz plzzzzzzzzzz help me! Here im posting my codes; <?php # Function: finfCommon function findCommon($current, $arr) { $cUser = $arr[$current]; unset($arr[$current]); foreach ($arr As $user => $friends) { $common = array(); $total = array(); foreach ($friends As $friend) { if (in_array($friend, $cUser)) { $common[] = $friend; } } $total = count($common); $add = ($total != 1) ? 's' : ''; $final[] = "<i>{$current} has {$total} friend{$add} in common with {$user}.</i>"; } return implode('<br />', $final); } # Array of users and friends $Friends = array( "Rana" => array("Pothik", "Zaman", "Tanmoy", "Ishita"), "Nandini" => array("Bonna", "Shakib", "Kamal", "Minhaj", "Ishita"), "Roni" => array("Akbar", "Anwar", "Khakan", "Pavel"), "Liton" => array("Mahadi", "Pavel"), "Mamun" => array("Meheli", "Tarek", "Zaman") ); # Creating the output value $output = "<ul>"; foreach ($Friends As $user => $friends) { $total = count($friends); $common = findCommon($user, $Friends); $output .= "<li><u>{$user} has {$total} friends.</u><br /><strong>Friends:</strong>"; if (is_array($friends) && !empty($friends[0])) { $output .= "<ul>"; foreach ($friends As $friend) { $output .= "<li>{$friend}</li>"; } $output .= "</ul>"; } $output .= "{$common}<br /><br /></li>"; } $output .= "</ul>"; # Printing the output value print $output; ?>

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  • TCP Tweaking options and Results: Any suggestions?

    - by krishnakumar
    I first tried with the default windows XP TCP option(It doesn't have TCPWindowSize option and TCP1323 in its Registry setting). I dynamically set those options using TCP optimizer. Here I list out the result with and without TCP Tweaking option. I see no major improvements in TCP after increasing window size optimally too. What value should I set to increase the performance? Results: Without any window size and MTU setting from server to client (receiving) TCPWindowSize : MTU : TTL: Size:586 MB total duration : 03:47 With window size extension from server to client (receiving) Bandwidth :100 Mbps Latency: 100ms BDP :1250000 TCPWindowSize : 1250000 MTU :1500 TTL:128 Size:586MB total duration : 03:44 With window size extension from server to client (receiving) TCPWindowSize :64240 MTU :1500 TTL :112 Size: 586MB total duration : 03:49

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  • php server settings for restrict post queries

    - by Korjavin Ivan
    I have php script on hosting, which receive big data with ajax/post. Just now, after some works on hosting, I see that script is broken. I checked with curl: file temp1: user_avatar=&user_baner=&user_sig=.... 237 chars total, and curl -H "X-Requested-With: XMLHttpRequest" -X POST --data @temp1 'http://host/mypage.php' works perfect. But with file temp2: name=%D0%9C%D0%B5%D0%B1%%B5%D0%BB%D1%8C%D0%A4%%B0%D0%B1%D1%80%D0%B8%D0%BA%D1%8A&user_payed=0000-00-00&...positions%5B5231%5D=on total chars: 65563 curl -H "X-Requested-With: XMLHttpRequest" -X POST --data @temp2 'http://host/mypage.php' curl return nothing. Looks like a problem with apache/php/php.ini or something like that. I check .htaccess php_value post_max_size 20M Which other parameters I should check? Is it possible that %BO encode kill php/apache? Or total number of parameters (about 2800) ?

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  • Bypass cache for mobile user agents, VARNISH+NGINX+W3CACHE

    - by Mike McGhee
    Right now I'm running Wordpress w/ W3 Cache on nginx with varnish front end. I'm trying to use the WP Touch Pro plugin for wordpress to display mobile sites, but it is not working. Shows the desktop theme still. I've put the mobile user agents in the rejected user agents box in w3 cache. Here is the nginx config w3 cache spit out: BEGIN W3TC Page Cache cache location ~ /wp-content/w3tc/pgcache.*html$ { expires modified 3600s; add_header X-Powered-By "W3 Total Cache/0.9.2.4"; add_header Vary "Accept-Encoding, Cookie"; } location ~ /wp-content/w3tc/pgcache.*gzip$ { gzip off; types {} default_type text/html; expires modified 3600s; add_header X-Powered-By "W3 Total Cache/0.9.2.4"; add_header Vary "Accept-Encoding, Cookie"; add_header Content-Encoding gzip; } # END W3TC Page Cache cache # BEGIN W3TC Browser Cache gzip on; gzip_types text/css application/x-javascript text/x-component text/richtext image/svg+xml text/plain text/xsd text/xsl text/xml image/x-icon; location ~ \.(css|js|htc)$ { expires 31536000s; add_header X-Powered-By "W3 Total Cache/0.9.2.4"; } location ~ \.(html|htm|rtf|rtx|svg|svgz|txt|xsd|xsl|xml)$ { expires 3600s; add_header X-Powered-By "W3 Total Cache/0.9.2.4"; } location ~ \.(asf|asx|wax|wmv|wmx|avi|bmp|class|divx|doc|docx|eot|exe|gif|gz|gzip|ico|jpg|jpeg|jpe|mdb|mid|midi|mov|qt|mp3|m4a|mp4|m4v|mpeg|mpg|mpe|mpp|otf|odb|odc|odf|odg|odp|ods|odt|ogg|pdf|png|pot|pps|ppt|pptx|ra|ram|svg|svgz|swf|tar|tif|tiff|ttf|ttc|wav|wma|wri|xla|xls|xlsx|xlt|xlw|zip)$ { expires 31536000s; add_header X-Powered-By "W3 Total Cache/0.9.2.4"; } # END W3TC Browser Cache # BEGIN W3TC Minify core rewrite ^/wp-content/w3tc/min/w3tc_rewrite_test$ /wp-content/w3tc/min/index.php?w3tc_rewrite_test=1 last; rewrite ^/wp-content/w3tc/min/(.+\.(css|js))$ /wp-content/w3tc/min/index.php?file=$1 last; # END W3TC Minify core # BEGIN W3TC Page Cache core rewrite ^(.*\/)?w3tc_rewrite_test$ $1?w3tc_rewrite_test=1 last; set $w3tc_rewrite 1; if ($request_method = POST) { set $w3tc_rewrite 0; } if ($query_string != "") { set $w3tc_rewrite 0; } if ($http_host != "mysite.com") { set $w3tc_rewrite 0; } set $w3tc_rewrite2 1; if ($request_uri !~ \/$) { set $w3tc_rewrite2 0; } if ($request_uri ~* "(sitemap(_index)?\.xml(\.gz)?|[a-z0-9_\-]+-sitemap([0-9]+)?\.xml(\.gz)?)") { set $w3tc_rewrite2 1; } if ($w3tc_rewrite2 != 1) { set $w3tc_rewrite 0; } set $w3tc_rewrite3 1; if ($request_uri ~* "(\/wp-admin\/|\/xmlrpc.php|\/wp-(app|cron|login|register|mail)\.php|\/feed\/|wp-.*\.php|index\.php)") { set $w3tc_rewrite3 0; } if ($request_uri ~* "(wp\-comments\-popup\.php|wp\-links\-opml\.php|wp\-locations\.php)") { set $w3tc_rewrite3 1; } if ($w3tc_rewrite3 != 1) { set $w3tc_rewrite 0; } if ($http_cookie ~* "(comment_author|wp\-postpass|wordpress_\[a\-f0\-9\]\+|wordpress_logged_in)") { set $w3tc_rewrite 0; } if ($http_user_agent ~* "(W3\ Total\ Cache/0\.9\.2\.4|iphone|ipod|ipad|aspen|incognito|webmate|android|dream|cupcake|froyo|blackberry9500|blackberry9520|blackberry9530|blackberry9550|blackberry\ 9800|blackberry\ 9780|webos|s8000|bada)") { set $w3tc_rewrite 0; } set $w3tc_ua ""; if ($http_user_agent ~* "(acer\ s100|android|archos5|blackberry9500|blackberry9530|blackberry9550|blackberry\ 9800|cupcake|docomo\ ht\-03a|dream|htc\ hero|htc\ magic|htc_dream|htc_magic|incognito|ipad|iphone|ipod|kindle|lg\-gw620|liquid\ build|maemo|mot\-mb200|mot\-mb300|nexus\ one|opera\ mini|samsung\-s8000|series60.*webkit|series60/5\.0|sonyericssone10|sonyericssonu20|sonyericssonx10|t\-mobile\ mytouch\ 3g|t\-mobile\ opal|tattoo|webmate|webos)") { set $w3tc_ua _high; } set $w3tc_ref ""; set $w3tc_ssl ""; set $w3tc_enc ""; if ($http_accept_encoding ~ gzip) { set $w3tc_enc _gzip; } set $w3tc_ext ""; if (-f "$document_root/wp-content/w3tc/pgcache/$request_uri/_index$w3tc_ua$w3tc_ref$w3tc_ssl.html$w3tc_enc") { set $w3tc_ext .html; } if ($w3tc_ext = "") { set $w3tc_rewrite 0; } if ($w3tc_rewrite = 1) { rewrite .* "/wp- content/w3tc/pgcache/$request_uri/_index$w3tc_ua$w3tc_ref$w3tc_ssl$w3tc_ext$w3tc_enc" last; } # END W3TC Page Cache core And here is what I have in my varnish vcl.. sub vcl_recv { # Add a unique header containing the client address remove req.http.X-Forwarded-For; set req.http.X-Forwarded-For = client.ip; # Device detection set req.http.X-Device = "desktop"; if ( req.http.User-Agent ~ "iP(hone|od|ad)" || req.http.User-Agent ~ "Android" ) { set req.http.X-Device = "smart"; } elseif ( req.http.User-Agent ~ "(SymbianOS|BlackBerry|SonyEricsson|Nokia|SAMSUNG|^LG)" ) { set req.http.X-Device = "cell"; } Any help is greatly appreciated, I've been banging my head against this for 2 days..

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  • How many hours of use before I need to clean a tape drive?

    - by codeape
    I do backups to a HP Ultrium 2 tape drive (HP StorageWorks Ultrium 448). The drive has a 'Clean' LED that supposedly will light up or blink when the drive needs to be cleaned. The drive has been in use since october 2005, and still the 'Clean' light has never been lit. The drive statistics are: Total hours in use: 1603 Total bytes written: 19.7 TB Total bytes read: 19.3 TB My question is: How many hours of use can I expect before I need to clean the drive? Edit: I have not encountered any errors using the drive. I do restore tests every two months, and every backup is verified. Edit 2: The user manual says: "HP StorageWorks Ultrium tape drives do not require regular cleaning. An Ultrium universal cleaning cartridge should only be used when the orange Clean LED is flashing." Update: It is now May 2010 (4.5 years of use), and the LED is still off, I have not cleaned, backups verify and regular restore tests are done.

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  • High Load - Low IO - Low CPU usage

    - by devup
    I have a system whose load is rather high. As you can see from the top output below, CPU usage and I/O is negligible: top - 17:31:59 up 4 days, 2:34, 2 users, load average: 1.00, 0.99, 1.00 Tasks: 71 total, 1 running, 70 sleeping, 0 stopped, 0 zombie Cpu(s): 2.0%us, 2.0%sy, 0.0%ni, 95.9%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 960720k total, 707288k used, 253432k free, 67328k buffers Swap: 2811896k total, 2644k used, 2809252k free, 528928k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 15310 root 20 0 2512 1128 888 R 2.1 0.1 0:00.05 top I would appreciate any assistance with isolating the cause(s) of high load for when I/O and CPU are not factors.

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  • OpenOffice Calc - Highlighting the higest value in a column

    - by cornjuliox
    So I've got this spreadsheet open using OpenOffice Calc (ver 3.3.0) and its set up a little like this: A B C D 1.name quantity price total 2.foo 10 10 100 3.bar 20 6 120 4.red 30 7 210 Each cell in the "total" column is obtained by multiplying the two cells to the left of it, and what I'm trying to do is to get it so that Calc highlights the highest value in the total column (even better if it could highlight the entire row). I've tried using MAX(D1:D4) in the Conditional Formatting section, but it highlights multiple values. How do I get it to highlight just the highest value?

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  • httpd service keep restarting. after 15-20 mins

    - by niraj
    I have recently purchased Dedicated Server which has 16bg ram and 1TB Harddisk. It has Cpanel and for firewall CSF Installd. I am mainly going to install it for File hosting service. Now the day i moved my httpd service keep restarting every 15-20 mins. It becomes unresponsive after that so have to manually restart it. My httpd settings are Start Servers = 5 Minimum Spare Servers = 5 Maximum Spare Servers = 10 Server Limit = 20000 Max Clients = 10000 Max Requests Per Child = 10000 Keep-Alive = On Keep-Alive Timeout = 5 Max Keep-Alive Requests = Unlimited Timeout 300 TOP is top - 14:53:41 up 1 day, 23:39, 2 users, load average: 0.10, 0.14, 0.09 Tasks: 1563 total, 1 running, 1562 sleeping, 0 stopped, 0 zombie Cpu(s): 0.7%us, 0.6%sy, 0.0%ni, 98.1%id, 0.2%wa, 0.0%hi, 0.5%si, 0.0%st Mem: 16303780k total, 16142048k used, 161732k free, 135264k buffers Swap: 8224760k total, 868k used, 8223892k free, 14136616k cached Please help me in this its keep happning.

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  • linux migration/N high cpu consumption

    - by Alexander
    on my linux appliance based on 3.0.0-14 kernel I got: RPN:/tmp# ps axuf | grep migration root 6 92.9 0.0 0 0 ? S Apr23 2788:33 \_ [migration/0] root 7 99.7 0.0 0 0 ? S Apr23 2993:20 \_ [migration/1] my top is RPN:/tmp# top -b -n1 top - 12:03:41 up 2 days, 2:18, 5 users, load average: 25.76, 25.26, 24.73 Tasks: 171 total, 1 running, 168 sleeping, 0 stopped, 2 zombie Cpu(s): 14.0%us, 12.6%sy, 0.8%ni, 72.0%id, 0.3%wa, 0.0%hi, 0.3%si, 0.0%st Mem: 1543032k total, 1264728k used, 278304k free, 25308k buffers Swap: 0k total, 0k used, 0k free, 183168k cached My question: why processes "migration/N" take so much CPU?

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  • Maximum memory allocation for 32bit linux kernel

    - by LedZeppelin
    I was reading this article that talks about how maximum amount of ram dedicated for kernel usage in 32 bit windows is 2GB even when the total amount of ram is 4GB. http://www.brianmadden.com/blogs/brianmadden/archive/2004/02/19/the-4gb-windows-memory-limit-what-does-it-really-mean.aspx\ Is this the same for 32bit linux environments like 32-bit ubuntu 10.04? IE is the max kernel allocation 2GB ram even if the total main memory 4GB? If you increase the total amount of memory to 64GB of ram by recompiling the kernel with the PAE option enabled, what is the maximum amount of ram you can dedicate for kernel usage? Is it still 2GB? Or can you increase it?

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  • Adding view cart function

    - by user228390
    Hey guys need some help in adding a view cart button but I'm stuck not sure how to code it. any help? The way I have coded it is that when a user clicks 'add item' they will get a alert box with info about the total price but I want that to appear in the HTML file but only once I have clicked on 'view cart' and I need it to be in a table format with info about the name, sum, price of the items and total. any ideas how I can do this? here is my javascript var f,d,str,items,qnts,price,bag,total; function cart(){ f=document.forms[0]; d=f.getElementsByTagName('div'); var items=[];var qnts=[];price=[];bag=[] for(i=0,e=0;i<d.length;i++){ items[i]=d[i].getElementsByTagName('b')[0].innerHTML; qnts[i]=d[i].getElementsByTagName('select')[0].value; str=d[i].getElementsByTagName('p')[1].innerHTML; priceStart(str,i); if(qnts[i]!=0){bag.push(new Array()); ib=bag[bag.length-1]; ib.push(items[i]);ib.push(qnts[i]);ib.push(price[i]);ib.push(qnts[i]*price[i]);} } if(bag.length>0){ total=bag[0][3]; if(bag.length>1){for(t=1;t<bag.length;t++){total+=bag[t][3]}} alert(bag.join('\n')+'\n----------------\ntotal='+total) } } function priceStart(str,inx){for(j=0;j<str.length;j++){if(str.charAt(j)!=' ' && !isNaN(str.charAt(j))){priceEnd(j,str,inx);return }}} function priceEnd(j,str,inx){for(k=str.length;k>j;k--){if(str.charAt(k)!=' ' && !isNaN(str.charAt(k))){price[inx]=str.substring(j,k);return }}} and my HTML <script type="text/javascript" src="cart.js" /> </script> <link rel="stylesheet" type="text/css" href="shopping_cart.css" /> <title> A title </title> </head> <body> <form name="form1" method="post" action="data.php" > <div id="product1"> <p id="title1"><b>Star Wars Tie Interceptor</b></p> <img src="images/DS.jpg" /> <p id="price1">Price £39.99</p> <p><b>Qty</b></p> <select name="qty"> <option value="0">0</option> <option value="1">1</option> <option value="2">2</option> <option value="3">3</option> <option value="4">4</option> <option value="5">5</option> </select> <input type="button" value="Add to cart" onclick="cart()" /> </div>

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  • I hyperlinked a cell in excel 2003, formula issues?

    - by joseinsomniac
    I have a budget spreadsheet using excel 2003. I have My deposit, then all of my bills, the total, then a cell that has the difference(between the amount of deposit and the total of the bills). The difference cell numbers turn red when I dont have enough money (deposit vs bill total). I hyperlinked the difference cell to a checkbook register spreadsheet so I can track where all my extra money went(reconsile receipts daily). When hyperlinked the numbers are blue. I need the numbers to stay black(when above 0.00) and stay red (when the numbers are below 0.00) and not change after the link has been clicked on. Also if the link has not been clicked on, and the numbers are red, the font is smaller, even though the toolbar shows the font size hasnt changed. After I click on it and go back to the budget sheet, its the size it should be. Any Ideas? Thanks!

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  • Installing Ubuntu next to Windows XP

    - by jess
    I have iso image for Ubuntu 11.0.4 on a CD. My OS is windows XP. I have 3 partions c, E and F. Windows is installed on C, and F has data. E is empty drive. Now, after I start installation , I choose the third option. Then click forward and I am shown three figures -- /dev/sda1 52427(total)/50931(used) /dev/sda5 52427(total)/3221(used) -- surprised, since it should be empty. I had used wubi to install earlier but have uninstalled. /dev/sda5 215206(total)/37545(used) Now, it means I need to choose sda5. Now how should I go about creating 3 partions for /(root), /home and /swap. Click edit partion and give size for each of them?

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  • PowerShell script halts execution when Windows XP PC is locked

    - by jshin47
    I have the following script that does a continuous ping and reports failures. It works fine, except the loop apparently "suspends" when the computer is locked. I have confirmed this by starting the script, immediately locking the PC, waiting 10 minutes, and seeing how many pings have occurred. It is nowhere near the expected number. What could be the culprit? Write-Host "Entering monitoring loop..." -Background DarkRed $ping = new-object System.Net.NetworkInformation.Ping $count_up = 0 $count_dn = 0 $count_dd = 0 while ($true) { $result = $ping.send("10.1.1.1") if ($result.Status -eq "Success") { $count_up++ $count_dd = 0 } else { $count_dn++ $count_dd++ $this_date = Get-Date Write-Host "VPN ping failed at time " $this_date -Background Magenta if ($count_dd -gt 3) { Write-Host "***VPN is Down***" `a send_mail_notification("VPN is Down", "") } } if ($Host.UI.RawUI.KeyAvailable -and ("q" -eq $Host.UI.RawUI.ReadKey("IncludeKeyUp,NoEcho").Character)) { Write-Host "Exiting monitoring loop..." -Background DarkRed break; } Start-Sleep -m 250 } $total = $count_up + $count_dn $uptime = 100 * $count_up / $total Write-Host $count_up " out of " $total " pings for a " $uptime "% uptime."

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  • Swap 95%+ , but a lot of free ram memory

    - by Paolo_NL_FR
    I am running centos 5.8 with cpanel. Lately I am getting reports that my swap is full , but there is a lot of free memory to use. top - 10:33:43 up 133 days, 17:00, 1 user, load average: 0.05, 0.03, 0.05 Tasks: 170 total, 1 running, 169 sleeping, 0 stopped, 0 zombie Cpu(s): 2.1%us, 0.5%sy, 0.0%ni, 97.2%id, 0.0%wa, 0.0%hi, 0.2%si, 0.0%st Mem: 24726100k total, 8255368k used, 16470732k free, 599560k buffers Swap: 1046520k total, 984740k used, 61780k free, 3641828k cached How do I solve this? The unused ram memory should be used instead of the swap. Or should I increase the swap ( and how do I do that ? ). Thanks

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  • large RAID 10 vs small RAID1

    - by user116399
    The machine will store and serve millions of small files (<15Kb each), and all those files require a total storage space of 400G Considering the exact same SATA hard drives maker and models, on the exact same environment (OS, cpu, ram, raid controller, etc...) which one of the setups bellow would be faster? A) RAID 1 with 2 drives of 2T each, making up total storage of 2T B) RAID 10 with 4 drives of 2T each, making up total storage of 4T [EDIT]: I'm aware RAID10 is faster than RAID1. The larger the disk, at least in theory, the longer will take to do seeks/writes. So, will the performance gain of RAID10 will be outweighed by the "drag" caused the larger disk area when seek/write operations happened?

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  • check two conditions in two different columns in excel and count the matches

    - by user1727103
    I've trying to create a Error Log to help me analyse my mistakes. So for simplicity, lets assume I have two columns "Type of Question" - with values SC,RC,CR and another column that indicates whether I got this question "right/wrong".Let's assume this is my table: Question No. | Right/Wrong | Question Type | Right | SC | Right | RC | Wrong | SC | Wrong | CR | Right | RC (Pardon my formatting skills). And I want an output table like this Type of Question | Right | Wrong | Total SC | 1 | 1 | 2 RC | 2 | 0 | 2 CR | 0 | 1 | 1 So basically what I want to do is check Column3 for SC using =COUNTIF(C1:C5,"SC"), and return the total number of SC questions, and then outta the SC , I need to find out which are Right.If I know the right and the total I can get the wrong. I have never written a macro so a formula based answer would suffice.

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  • Load on Ubuntu 8.04 LTS high

    - by Paddington
    My Ubuntu 8.04 LTS server periodically has a high load avg spike(once every 2 days) resulting in Apache timing out and virtualy everything even SSH to the server is not possible. When I am on the console and run TOP is see that The load avg increases from less than 1 to above 60 in 15 mins. How can I isolate the cause? top - 09:21:51 up 37 days, 20:18, 6 users, load average: 5.41, 5.53, 5.36 Tasks: 160 total, 2 running, 156 sleeping, 0 stopped, 2 zombie Cpu(s): 65.0%us, 8.8%sy, 0.0%ni, 1.0%id,24.6%wa, 0.3%hi, 0.3%si, 0.0%st Mem: 3989468k total, 3444984k used, 544484k free, 360460k buffers Swap: 11687248k total, 178168k used, 11509080k free, 881772k cached

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  • How many hours of use before I need to clean a tape drive?

    - by codeape
    I do backups to a HP Ultrium 2 tape drive (HP StorageWorks Ultrium 448). The drive has a 'Clean' LED that supposedly will light up or blink when the drive needs to be cleaned. The drive has been in use since october 2005, and still the 'Clean' light has never been lit. The drive statistics are: Total hours in use: 1603 Total bytes written: 19.7 TB Total bytes read: 19.3 TB My question is: How many hours of use can I expect before I need to clean the drive? Edit: I have not encountered any errors using the drive. I do restore tests every two months, and every backup is verified. Edit 2: The user manual says: "HP StorageWorks Ultrium tape drives do not require regular cleaning. An Ultrium universal cleaning cartridge should only be used when the orange Clean LED is flashing." Update: It is now May 2010 (4.5 years of use), and the LED is still off, I have not cleaned, backups verify and regular restore tests are done.

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  • July, the 31 Days of SQL Server DMO’s – Day 27 (sys.dm_db_file_space_usage)

    - by Tamarick Hill
    The sys.dm_db_file_space usage DMV returns information about database file space usage.  This DMV was enhanced for the 2012 version to include 3 additional columns. Let’s query this DMV against our AdventureWorks2012 database and view the results. SELECT * FROM sys.dm_db_file_space_usage The column returned from this DMV are really self-explanatory, but I will give you a description, paraphrased from books online, below. The first three columns returned from this DMV represent the Database, File, and Filegroup for the current database context that executed the DMV query. The next column is the total_page_count which represents the total number of pages in the file. The allocated_extent_page_count represents the total number of pages in all extents that have been allocated. The unallocated_extent_page_count represents the number of pages in the unallocated extents within the file. The version_store_reserved_page_count column represents the number of pages that are allocated to the version store. The user_object_reserved_page_count represents the number of pages allocated for user objects. The internal_object_reserved_page_count represents the number of pages allocated for internal objects.  Lastly is the mixed_extent_page_count which represents the total number of pages that are part of mixed extents. This is a great DMV for retrieving usage space information from your database files. For more information about this DMV, please see the below Books Online link: http://msdn.microsoft.com/en-us/library/ms174412.aspx Follow me on Twitter @PrimeTimeDBA

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  • How should I work out VAT (UK tax) in my eCommerce site?

    - by Leonard Challis
    We have an ecommerce system in place. The sales actually go through Sage, so we have an export script from our system that uses a third-party Sage Importer program. With a new version of this importer, values are checked more thoroughly. We are getting 1 pence discrepancies because of the way rounding works - our system has always held prices and worked to 4 decimal places. In the checkout the totals would be worked out first, then the rounding to 2 decimal places. The importer does rounding first, though. So, for instance: Our way: Product 1: £13.4561 Qty: 2 Total inc VAT = £32.29 (to 2dp) Importer way: Our way: Product 1: £13.4561 Qty: 2 Total inc VAT = £32.30 (to 2dp) Management are reluctant to lose the 4dp but the developers of the Sage importer have said that this is correct and makes sense -- you woudn't sell a product for £13.4561 in a shop, nor would you charge someone tax at 4 decimal places. I contacted the HMRC and the operator didn't really give me much to go on, telling me a technician would phone back, to which they haven't and I'm still waiting after almost a week and numerous follow-up calls. I did find a PDF on the HMRC's web site, but this did about us much to confuse me as it did to answer my questions. I see that they're happy for people to round up or down, as long it is consistent, but I can't tell whether it should be done on a line by line basis or on the end total of the order. We are now in the position where we need to decide whether it's worth us doing one of the following, or something completely different. Please advise with any experience or information I can read. Change all products on the site to use 2dp Keep 4dp but round each line in the order to 2dp before working out tax Keep it as it is and "fudge" the values at the export script (i.e. make that values correct by adding or subtracting 1p and changing the shipping cost to make the totals still work out) Any thoughts?

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  • Convert ddply {plyr} to Oracle R Enterprise, or use with Embedded R Execution

    - by Mark Hornick
    The plyr package contains a set of tools for partitioning a problem into smaller sub-problems that can be more easily processed. One function within {plyr} is ddply, which allows you to specify subsets of a data.frame and then apply a function to each subset. The result is gathered into a single data.frame. Such a capability is very convenient. The function ddply also has a parallel option that if TRUE, will apply the function in parallel, using the backend provided by foreach. This type of functionality is available through Oracle R Enterprise using the ore.groupApply function. In this blog post, we show a few examples from Sean Anderson's "A quick introduction to plyr" to illustrate the correpsonding functionality using ore.groupApply. To get started, we'll create a demo data set and load the plyr package. set.seed(1) d <- data.frame(year = rep(2000:2014, each = 3),         count = round(runif(45, 0, 20))) dim(d) library(plyr) This first example takes the data frame, partitions it by year, and calculates the coefficient of variation of the count, returning a data frame. # Example 1 res <- ddply(d, "year", function(x) {   mean.count <- mean(x$count)   sd.count <- sd(x$count)   cv <- sd.count/mean.count   data.frame(cv.count = cv)   }) To illustrate the equivalent functionality in Oracle R Enterprise, using embedded R execution, we use the ore.groupApply function on the same data, but pushed to the database, creating an ore.frame. The function ore.push creates a temporary table in the database, returning a proxy object, the ore.frame. D <- ore.push(d) res <- ore.groupApply (D, D$year, function(x) {   mean.count <- mean(x$count)   sd.count <- sd(x$count)   cv <- sd.count/mean.count   data.frame(year=x$year[1], cv.count = cv)   }, FUN.VALUE=data.frame(year=1, cv.count=1)) You'll notice the similarities in the first three arguments. With ore.groupApply, we augment the function to return the specific data.frame we want. We also specify the argument FUN.VALUE, which describes the resulting data.frame. From our previous blog posts, you may recall that by default, ore.groupApply returns an ore.list containing the results of each function invocation. To get a data.frame, we specify the structure of the result. The results in both cases are the same, however the ore.groupApply result is an ore.frame. In this case the data stays in the database until it's actually required. This can result in significant memory and time savings whe data is large. R> class(res) [1] "ore.frame" attr(,"package") [1] "OREbase" R> head(res)    year cv.count 1 2000 0.3984848 2 2001 0.6062178 3 2002 0.2309401 4 2003 0.5773503 5 2004 0.3069680 6 2005 0.3431743 To make the ore.groupApply execute in parallel, you can specify the argument parallel with either TRUE, to use default database parallelism, or to a specific number, which serves as a hint to the database as to how many parallel R engines should be used. The next ddply example uses the summarise function, which creates a new data.frame. In ore.groupApply, the year column is passed in with the data. Since no automatic creation of columns takes place, we explicitly set the year column in the data.frame result to the value of the first row, since all rows received by the function have the same year. # Example 2 ddply(d, "year", summarise, mean.count = mean(count)) res <- ore.groupApply (D, D$year, function(x) {   mean.count <- mean(x$count)   data.frame(year=x$year[1], mean.count = mean.count)   }, FUN.VALUE=data.frame(year=1, mean.count=1)) R> head(res)    year mean.count 1 2000 7.666667 2 2001 13.333333 3 2002 15.000000 4 2003 3.000000 5 2004 12.333333 6 2005 14.666667 Example 3 uses the transform function with ddply, which modifies the existing data.frame. With ore.groupApply, we again construct the data.frame explicilty, which is returned as an ore.frame. # Example 3 ddply(d, "year", transform, total.count = sum(count)) res <- ore.groupApply (D, D$year, function(x) {   total.count <- sum(x$count)   data.frame(year=x$year[1], count=x$count, total.count = total.count)   }, FUN.VALUE=data.frame(year=1, count=1, total.count=1)) > head(res)    year count total.count 1 2000 5 23 2 2000 7 23 3 2000 11 23 4 2001 18 40 5 2001 4 40 6 2001 18 40 In Example 4, the mutate function with ddply enables you to define new columns that build on columns just defined. Since the construction of the data.frame using ore.groupApply is explicit, you always have complete control over when and how to use columns. # Example 4 ddply(d, "year", mutate, mu = mean(count), sigma = sd(count),       cv = sigma/mu) res <- ore.groupApply (D, D$year, function(x) {   mu <- mean(x$count)   sigma <- sd(x$count)   cv <- sigma/mu   data.frame(year=x$year[1], count=x$count, mu=mu, sigma=sigma, cv=cv)   }, FUN.VALUE=data.frame(year=1, count=1, mu=1,sigma=1,cv=1)) R> head(res)    year count mu sigma cv 1 2000 5 7.666667 3.055050 0.3984848 2 2000 7 7.666667 3.055050 0.3984848 3 2000 11 7.666667 3.055050 0.3984848 4 2001 18 13.333333 8.082904 0.6062178 5 2001 4 13.333333 8.082904 0.6062178 6 2001 18 13.333333 8.082904 0.6062178 In Example 5, ddply is used to partition data on multiple columns before constructing the result. Realizing this with ore.groupApply involves creating an index column out of the concatenation of the columns used for partitioning. This example also allows us to illustrate using the ORE transparency layer to subset the data. # Example 5 baseball.dat <- subset(baseball, year > 2000) # data from the plyr package x <- ddply(baseball.dat, c("year", "team"), summarize,            homeruns = sum(hr)) We first push the data set to the database to get an ore.frame. We then add the composite column and perform the subset, using the transparency layer. Since the results from database execution are unordered, we will explicitly sort these results and view the first 6 rows. BB.DAT <- ore.push(baseball) BB.DAT$index <- with(BB.DAT, paste(year, team, sep="+")) BB.DAT2 <- subset(BB.DAT, year > 2000) X <- ore.groupApply (BB.DAT2, BB.DAT2$index, function(x) {   data.frame(year=x$year[1], team=x$team[1], homeruns=sum(x$hr))   }, FUN.VALUE=data.frame(year=1, team="A", homeruns=1), parallel=FALSE) res <- ore.sort(X, by=c("year","team")) R> head(res)    year team homeruns 1 2001 ANA 4 2 2001 ARI 155 3 2001 ATL 63 4 2001 BAL 58 5 2001 BOS 77 6 2001 CHA 63 Our next example is derived from the ggplot function documentation. This illustrates the use of ddply within using the ggplot2 package. We first create a data.frame with demo data and use ddply to create some statistics for each group (gp). We then use ggplot to produce the graph. We can take this same code, push the data.frame df to the database and invoke this on the database server. The graph will be returned to the client window, as depicted below. # Example 6 with ggplot2 library(ggplot2) df <- data.frame(gp = factor(rep(letters[1:3], each = 10)),                  y = rnorm(30)) # Compute sample mean and standard deviation in each group library(plyr) ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y)) # Set up a skeleton ggplot object and add layers: ggplot() +   geom_point(data = df, aes(x = gp, y = y)) +   geom_point(data = ds, aes(x = gp, y = mean),              colour = 'red', size = 3) +   geom_errorbar(data = ds, aes(x = gp, y = mean,                                ymin = mean - sd, ymax = mean + sd),              colour = 'red', width = 0.4) DF <- ore.push(df) ore.tableApply(DF, function(df) {   library(ggplot2)   library(plyr)   ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))   ggplot() +     geom_point(data = df, aes(x = gp, y = y)) +     geom_point(data = ds, aes(x = gp, y = mean),                colour = 'red', size = 3) +     geom_errorbar(data = ds, aes(x = gp, y = mean,                                  ymin = mean - sd, ymax = mean + sd),                   colour = 'red', width = 0.4) }) But let's take this one step further. Suppose we wanted to produce multiple graphs, partitioned on some index column. We replicate the data three times and add some noise to the y values, just to make the graphs a little different. We also create an index column to form our three partitions. Note that we've also specified that this should be executed in parallel, allowing Oracle Database to control and manage the server-side R engines. The result of ore.groupApply is an ore.list that contains the three graphs. Each graph can be viewed by printing the list element. df2 <- rbind(df,df,df) df2$y <- df2$y + rnorm(nrow(df2)) df2$index <- c(rep(1,300), rep(2,300), rep(3,300)) DF2 <- ore.push(df2) res <- ore.groupApply(DF2, DF2$index, function(df) {   df <- df[,1:2]   library(ggplot2)   library(plyr)   ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))   ggplot() +     geom_point(data = df, aes(x = gp, y = y)) +     geom_point(data = ds, aes(x = gp, y = mean),                colour = 'red', size = 3) +     geom_errorbar(data = ds, aes(x = gp, y = mean,                                  ymin = mean - sd, ymax = mean + sd),                   colour = 'red', width = 0.4)   }, parallel=TRUE) res[[1]] res[[2]] res[[3]] To recap, we've illustrated how various uses of ddply from the plyr package can be realized in ore.groupApply, which affords the user explicit control over the contents of the data.frame result in a straightforward manner. We've also highlighted how ddply can be used within an ore.groupApply call.

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  • SQLAuthority News – 6th Anniversary and 50 Million Views and Over 2300 Blog Posts – Thank You Thank You

    - by pinaldave
    Six years ago, I started this SQLAuthority.com blog. There are so many things I want to say today – it is very very emotional. Instead of writing long I am including few images and cartoons. Last month we have also reached 50 Million Total Views on this blog. Here is the screen captured at that time. Click Image to Enlarge In 6 years there are total 2192 days (including 2 leap year day) and my total blog post count is 2300. That means I have been blogging more than 1 blog post every day. Here is the quick glance to all the numbers. Here you can find the list of all the 2300 blog posts. I am very glad to see my many of the friends stay in USA, India, United Kingdom, Canada and Australia in that order. You can see the geographic distribution of the support I receive on the blog from worldwide. On this day I would like to call out one 2 individuals who contribute equally or more in my success. When I started this blog 6 years ago, I was walking alone. After 2 years my wife Nupur joined my journey and 3 years later my daughter Shaivi joined the journey. Here is the example of the common conversation among us almost every day - Shaivi: Daddy, play catch-catch. Nupur: Shaivi, daddy will play with you once he finishes tomorrow’s blog. Shaivi: Daddy, Finish Blog. Okey. I play catch-catch (alone). SQLAuthority Family Well, thank you very much! We all love you! Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: About Me, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority News, SQLServer, T SQL, Technology

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