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XAML with inline JavaScript

- by quddusaliquddus

Hi :), Is it possible to insert Javascript code into XAML? Thanks Q

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ID cannot be null (Auto Increment)

- by THeK

I'm using an INSERT ON DUPLICATE KEY statement for my website. It's for creating news items, so I figured I could use the same MySQL command for both creating and updating news items. However, when I use the following: INSERT INTO table (id,title,content) VALUES(NULL,"Test","Test"); Instead of creating a new auto increment value it throws an error. However, the command works on my main development server. But not on my laptop. Both versions of MySQL are the same, the only difference being MySQL was installed manually on my server, and with WAMP on my laptop. Are there any MySQL Variables that could be causing this?

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It says command.ExecuteNonQuery() is not initialized

- by Alfrezo

My code: // Get Connection String string conn = WebConfigurationManager.ConnectionStrings["GraduatesConnectionString"].ToString(); // Create connection object SqlConnection connection = new SqlConnection(conn); SqlCommand command = connection.CreateCommand(); try { // Open the connection. connection.Open(); // Execute the insert command. command.CommandText = ("INSERT INTO PersonalInfo(Id,Name,LastName,ContactNumber, Address,Gender, Date_Of_Birth) VALUES(\'" + (this.txtID.Text + ("\',\'" + (this.txtName.Text + ("\',\'" + (this.txtLastName.Text + ("\',\'" + (this.txtContactNumber.Text + ("\',\'" + (this.txtAddress.Text + ("\',\'" + (this.gender + ("\',\'" + (this.txtDateofBirth.Text + ("\',\'" ))))); command.ExecuteNonQuery(); } finally { // Close the connection. connection.Close(); }

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Improving performance for WRITE operation on Oracle DB in Java

- by Lucky

I've a typical scenario & need to understand best possible way to handle this, so here it goes - I'm developing a solution that will retrieve data from a remote SOAP based web service & will then push this data to an Oracle database on network. Also, this will be a scheduled task that will execute every 15 minutes. I've event queues on remote service that contains the INSERT/UPDATE/DELETE operations that have been done since last retrieval, & once I retrieve the events for last 15 minutes, it again add events for next retrieval. Now, its just pushing data to Oracle so all my interactions are INSERT & UPDATE statements. There are around 60 tables on Oracle with some of them having 100+ columns. Moreover, for every 15 minutes cycle there would be around 60-70 Inserts, 100+ Updates & 10-20 Deletes. This will be an executable jar file that will terminate after operation & will again start on next 15 minutes cycle. So, I need to understand how should I handle WRITE operations (best practices) to improve performance for this application as whole ? Current Test Code (on every cycle) - Connects to remote service to get events. Creates a connection with DB (single connection object). Identifies the type of operation (INSERT/UPDATE/DELETE) & table on which it is done. After above, calls the respective method based on type of operation & table. Uses Preparedstatement with positional parameters, & retrieves each column value from remote service & assigns that to statement parameters. Commits the statement & returns to get event class to process next event. Above is repeated till all the retrieved events are processed after which program closes & then starts on next cycle & everything repeats again. Thanks for help !

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Encryption By Certificate

- by user1817240

I am encrypting customer name in database at database level. While saving in database only first letter of customer name is saved and hence while decrypting only first letter is retrieved. The following code shows the test sp. ALTER PROCEDURE [dbo].[spc_test_insert] ( @sFIRST_NAME typ_encryptedtext, ) AS BEGIN DECLARE @sSENCRYPTION_KEY char(15) DECLARE @sCERTIFICATE char(22) SET @sSENCRYPTION_KEY='SymmetricKey1' SET @sCERTIFICATE='CustomerCertificate' OPEN SYMMETRIC KEY SymmetricKey1 DECRYPTION BY CERTIFICATE CustomerCertificate; INSERT INTO test_table ( FIRST_NAME, ) Values ( -- Add the Params to be Added... EncryptByKey(Key_GUID(@sSENCRYPTION_KEY),@sFIRST_NAME), ) CLOSE SYMMETRIC KEY SymmetricKey1 END encryption decryption working fine in normal insert but its not working in stored procedure.

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setting up linked list Java

- by erp

I'm working on some basic linked list stuff, like insert, delete, go to the front or end of the list, and basically i understand the concept of all of that stuff once i have the list i guess but im having trouble setting up the list. I was wondering of you guys could tell me if im going in the right direction. (mostly just the setup) this is what i have so far: public class List { private int size; private List linkedList; List head; List cur; List next; /** * Creates an empty list. * @pre * @post */ public List(){ linkedList = new List(); this.head = null; cur = head; } /** * Delete the current element from this list. The element after the deleted element becomes the new current. * If that's not possible, then the element before the deleted element becomes the new current. * If that is also not possible, then you need to recognize what state the list is in and define current accordingly. * Nothing should be done if a delete is not possible. * @pre * @post */ public void delete(){ // delete size--; } /** * Get the value of the current element. If this is not possible, throw an IllegalArgumentException. * @pre the list is not empty * @post * @return value of the current element. */ public char get(){ return getItem(cur); } /** * Go to the last element of the list. If this is not possible, don't change the cursor. * @pre * @post */ public void goLast(){ while (cur.next != null){ cur = cur.next; } } /** * Advance the cursor to the next element. If this is not possible, don't change the cursor. * @pre * @post */ public void goNext(){ if(cur.next != null){ cur = cur.next;} //else do nothing } /** * Retreat the cursor to the previous element. If this is not possible, don't change the cursor. * @pre * @post */ public void goPrev(){ } /** * Go to top of the list. This is the position before the first element. * @pre * @post */ public void goTop(){ } /** * Go to first element of the list. If this is not possible, don't change the cursor. * @pre * @post */ public void goFirst(){ } /** * Insert the given parameter after the current element. The newly inserted element becomes the current element. * @pre * @post * @param newVal : value to insert after the current element. */ public void insert(char newVal){ cur.setItem(newVal); size++; } /** * Determines if this list is empty. Empty means this list has no elements. * @pre * @post * @return true if the list is empty. */ public boolean isEmpty(){ return head == null; } /** * Determines the size of the list. The size of the list is the number of elements in the list. * @pre * @post * @return size which is the number of elements in the list. */ public int size(){ return size; } public class Node { private char item; private Node next; public Node() { } public Node(char item) { this.item = item; } public Node(char item, Node next) { this.item = item; this.next = next; } public char getItem() { return this.item; } public void setItem(char item) { this.item = item; } public Node getNext() { return this.next; } public void setNext(Node next) { this.next = next; } } } I got the node class alright (well i think it works alright), but is it necessary to even have that class? or can i go about it without even using it (just curious). And for example on the method get() in the list class can i not call that getItem() method from the node class because it's getting an error even though i thought that was the whole point for the node class. bottom line i just wanna make sure im setting up the list right. Thanks for any help guys, im new to linked list's so bear with me!

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MySQL Database || Tables Issue

- by user1780103

I'm trying to write up a script where the user is able to purchase an amount of points for dollars. I want the transaction to be inserted into MySQL. I keep facing a: "Column count doesn't match value count at row 1" error. And I have no idea what I'm doing wrong. I have written up this: mysql_query("INSERT INTO paypal_donations VALUES (NULL, ".$account_id.", ".$char_id.", ".$price.", ".$dp.", NOW(), NOW(), 'Started', 0, 0, '', '');") or die(mysql_error()); But I don't know what to execute in MySQL, since I've never worked with it before. Could anyone write up a quick script that I can insert into MySQL for it to work.

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Getting id of row just inserted into MySQL database

- by James P

I have my table columns set like this: likes(id, like_message, timestamp) id is the primary key that is auto incrementing. This is the SQL that I use to add a row: $sql = "INSERT INTO `likes` (like_message, timestamp) VALUES ('$likeMsg', $timeStamp)"; Everything works, but now I need to throw back the id attribute of the newly inserted row. For example, if I insert a row and the id of that row is 13, I need to echo out 13 so my AJAX request can pick that up and use it. Any help would be appreciated, as well as related code samples. Thanks :)

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Inserting timestamp value in SQL Server

- by JPro

I am trying to copy data from my MYSQL table to SQL Server using PHP. I have a TimeStamp value that needs to be copied. While I am trying to copy the fields, it gave an error that timestamp value cannot be inserted. Is there any way to insert the timestamp value? Is it is not possible, then declaring the column as nvarchar will insert the timestamp, but will I be able to search the data in a date range? Can anyone please clarify my doubt? Thanks.

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Outer select column value in joined subquery?

- by Michael DePetrillo

Is it possible to use a column value from an outer select within a joined subquery? SELECT table1.id, table2.cnt FROM table1 LEFT JOIN (SELECT COUNT(*) as `cnt` FROM table2 where table2.lt > table1.lt and table2.rt < table1.rt) as table2 ON 1; This results in "Unknown column 'table1.lt' in 'where clause'". Here is the db dump. CREATE TABLE IF NOT EXISTS `table1` ( `id` int(1) NOT NULL, `lt` int(1) NOT NULL, `rt` int(4) NOT NULL) ENGINE=MyISAM DEFAULT CHARSET=latin1; CREATE TABLE IF NOT EXISTS `table2` ( `id` int(1) NOT NULL, `lt` int(1) NOT NULL, `rt` int(4) NOT NULL) ENGINE=MyISAM DEFAULT CHARSET=latin1; INSERT INTO `table1` (`id`, `lt`, `rt`) VALUES (1, 1, 4); INSERT INTO `table2` (`id`, `lt`, `rt`) VALUES (2, 2, 3);

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TinyMce plugin, how to copy 'Link' functionality.

- by Tom

I'm creating a new plugin for TinyMce. However I cannot find any examples to see some of the functionality I've seen in other plugins. I've read their source code but I cannot find where it is done: When you click on an 'A' element, the link/unlink buttons in the taskbar become enabled. When you right click on an 'A' element, then click on the "Insert/edit link" icon that is shown in the popup menu, the "Insert/edit link" window is setup (has all the attributes for that particular link) prefilled. Could you suggest somewhere where I could learn how to do this? A file and line number is fine. Thanks in advance.

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Do i need a hashtag in Javascript to pass as a Div

- by Mike

How do i insert this php DivSomething into Javascript? Since Javascript needs a hashtag to recognize that as a div. Is there a way to tell JS that this is a Div or there's other better way to do it? Any help would be very much appreciated. <script> /*How do i insert a var DivSomething into JS with a hashtag */ /* DivSomething is php dynamic. It returns a Div. It can be #Div1, #Div2, #Div3... */ var DivSomething = '<?php echo $Highlight; ?>' $(function() { $('#MouseHere').hover(function() { $('#' + DivSomething).css('background-color', '#ffffff'); }, function() { // on mouseout, reset the background colour $('#' + DivSomething).css('background-color', ''); </script>

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I have a tab delimeted file that I want to convert into a mysql table

- by user320835

I have a tab delimeted file that I want to convert into a mysql table. there are 25 tab delimeted fields in the text file. I can get the values in when I construct the SQL statement word by word and get each value individually stated in the VALUES part but when I try to get the list as a whole it does not work. Here is the code. I couldn't figure it out. Any ideas? lines=open(path, "r").readlines() for line in lines[1:]: linex=line.strip().split("\t") linex.insert(0,'sometextindex') try: cursor.execute('INSERT INTO variants VALUES(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)',linex) except: print 'line number=',a,linex

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Query to select from two different tables

- by ryan

I would like to select from two tables and display my result using this query: CREATE TABLE Buy_Table ( buy_id int identity primary key, user_id int, amount decimal (18,2) ); go INSERT INTO Buy_Table (user_id, amount) VALUES ('1', 10), ('1', 8), ('1', 20), ('3', 1), ('2', 2); go CREATE TABLE Sell_Table ( sell_id int identity primary key, user_id int, amount decimal (18,2) ); go INSERT INTO Sell_Table (user_id, amount) VALUES ('1', 10), ('1', 8), ('1', 20), ('3', 3), ('2', 3); go select [user_id], 'Buy' as [Type], buy_id as [ID], amount from Buy_Table union all select [user_id], 'Sell', sell_id, amount from Sell_Table order by [user_id], [ID], [Type] However the above query will return each row of the user_id like this I want to display my result to something like this in a grid: Can this be done in query itself rather manipulating the grid? Thx

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MYSQL accentuated characters é display as %E9

- by Jk_

Hi guys, I'm pushing data from as3 to MSQL through a little php script! My problem is that all my accentuated characters are displayed as weird iso characters. Example : é is displayed %E9 Obvisously the collation of my field is set to utf8_general_ci Even when I try to INSERT the data from a simple php script without as3, I get the same mistake. <?php mysql_connect("***", "***", "***") or die("Error :" .mysql_error()); mysql_select_db("***"); $query ="INSERT INTO test (message) values ('éèàïû')"; mysql_query($query) or die("Error updating DB"); ?> Any idea on what am I doing wrong and how I could fix that? Thanks in advance. Jk_

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Apache-Mina FTPServer Issue — unable to login into apache ftp server while using database user manager

- by piyush

I am unable to login into apache ftp server while using database user manager: while entering username and password,I am getting following error in log file: [ INFO] 2013-02-07 20:51:07,779 [] [0:0:0:0:0:0:0:1] RECEIVED: USER piyush [ INFO] 2013-02-07 20:51:07,781 [piyush] [0:0:0:0:0:0:0:1] SENT: 331 User name okay, need password for piyush. [ INFO] 2013-02-07 20:51:07,784 [piyush] [0:0:0:0:0:0:0:1] RECEIVED: PASS ***** [ WARN] 2013-02-07 20:51:07,785 [piyush] [0:0:0:0:0:0:0:1] User failed to log in [ WARN] 2013-02-07 20:51:08,285 [piyush] [0:0:0:0:0:0:0:1] Login failure - piyush [ INFO] 2013-02-07 20:51:08,286 [piyush] [0:0:0:0:0:0:0:1] SENT: 530 Authentication failed. [ INFO] 2013-02-07 20:51:08,286 [piyush] [0:0:0:0:0:0:0:1] RECEIVED: QUIT [ INFO] 2013-02-07 20:51:08,290 [piyush] [0:0:0:0:0:0:0:1] SENT: 221 Goodbye. [ INFO] 2013-02-07 20:51:08,291 [piyush] [0:0:0:0:0:0:0:1] CLOSED here is my xml file ftpd-typical.xml: <?xml version="1.0" encoding="UTF-8"?>  <server xmlns="http://mina.apache.org/ftpserver/spring/v1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:beans="http://www.springframework.org/schema/beans" xsi:schemaLocation=" http://mina.apache.org/ftpserver/spring/v1 http://mina.apache.org/ftpserver/ftpserver-1.0.xsd " id="Prometheus"> <listeners> <nio-listener name="default" port="2121" /> </listeners> <db-user-manager encrypt-passwords="salted"> <data-source> <beans:bean class="org.apache.commons.dbcp.BasicDataSource" > <beans:property name="driverClassName" value="com.mysql.jdbc.Driver" /> <beans:property name="url" value="jdbc:mysql://localhost/apache_test" /> <beans:property name="username" value="amy" /> <beans:property name="password" value="piyush" /> </beans:bean> </data-source> <insert-user>INSERT INTO FTP_USER (userid, userpassword, homedirectory, enableflag, writepermission, idletime, uploadrate, downloadrate) VALUES ('{userid}', '{userpassword}', '{homedirectory}', {enableflag}, {writepermission}, {idletime}, {uploadrate}, {downloadrate}) </insert-user> <update-user>UPDATE FTP_USER SET userpassword='{userpassword}',homedirectory='{homedirectory}',enableflag={enableflag},writepermission={writepermission},idletime={idletime},uploadrate={uploadrate},downloadrate={downloadrate} WHERE userid='{userid}' </update-user> <delete-user>DELETE FROM FTP_USER WHERE userid = '{userid}' </delete-user> <select-user>SELECT userid, userpassword, homedirectory, enableflag, writepermission, idletime, uploadrate, downloadrate, maxloginnumber, maxloginperip FROM FTP_USER WHERE userid = '{userid}' </select-user> <select-all-users>SELECT userid FROM FTP_USER ORDER BY userid </select-all-users> <is-admin>SELECT userid FROM FTP_USER WHERE userid='{userid}' AND userid='admin' </is-admin> <authenticate>SELECT userpassword from FTP_USER WHERE userid='{userid}'</authenticate> </db-user-manager> </server>

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How To Start Your Own Professional Blog with WordPress

- by Matthew Guay

Would you like to start your own blog or website? With a free WordPress account, it’s free and easy to get started creating your own professional quality blog site. This is the first part in a series on how to create your own professional quality blog site. No, we’re not talking about some cheapo looking blog from Blogger or something on Facebook, but creating a quality blog you can be proud of and present to millions of readers online. WordPress is one of the most popular blogging platforms, powering hundreds of high-profile websites and blogs around the world. It’s both powerful and easy to use, which makes it great whether you’re just starting out or are a blogging pro. To start out with your blogging project WordPress is completely free, and you can use the online interface or install the WordPress software on your own server and blog from there. Getting Started You can start a blog in just a few minutes. Head over to WordPress.com and click Sign up now on the right-hand side of the main page. Enter a username and password, check that you agree with the legal terms, select the “Gimme a blog” bullet, and click Next. WordPress may inform you that your username is already taken, simply choose a new one and try again. Next, choose a domain for your blog. This will be the address for your site, and cannot be changed, so be sure to choose exactly what you want. If you’d prefer your address to be yourname.com instead of yourname.wordpress.com, you can add your own domain for a fee after your blog is setup…but we’ll cover that later. Once you click signup, you will be sent a confirmation email. While you wait for the email to arrive you can go ahead and enter in your name and a short bio about yourself. When you receive your confirmation email, click the link. Congratulations; you now have your own blog! You can view your new blog immediately, though the default theme isn’t very interesting without your content and pictures. Back on the page you opened from the email, click Login to access your blog’s administration page and to start adding stuff to your blog. You can also access your blog’s admin page anytime by from yourname.wordpress.com/admin, substituting your own blog name for yourname. Enter your username and password, then click Log in to get started. Adding Content to your WordPress.com Blog When you sign in to your WordPress blog, you’ll first see the WordPress Admin page. Here you can see recent posts and comments, and you can see stats of how many people have visited your site. You can also access all of your blog tools and settings right from this page. To add a new post to your blog, click the Posts link on the left, then click “Add New” either on the left menu or on the top of the Edit Posts page. Or, if you want to edit the default first post, hover over it and select Edit. Or click the New Posts button on the top of the page. This menu bar is always visible whenever you’re logged in, so it’s an easy way to add a post. The editor lets you easily write anything you want in a Microsoft Word-style editor. You can format your text, add lists, links, quotes, and more. When you’re ready to share your content with the world, click Publish on the right side. To add pictures or other files, click the picture icon beside “Upload/Insert”. Your free blog account can store up to 3Gb of pictures and documents which will definitely give you a good start. Click Select Files, and then choose the pictures or documents you want to add to your post. When the pictures have uploaded, you can add a caption and choose how to position the picture. When you’re finished, select “Insert into Post”. Or, if you want to add a video, click the video button. You have to add a paid upgrade to upload videos directly, but you can add YouTube and other online videos for free. Click the “From URL” tab, and then paste the link to the YouTube video and click Insert into post. If you’re a code geek, click the HTML tab in the editor and edit the HTML of your blog post the geeky way. Once you’ve added all your content and edited it the way you want, click the Publish button on the right of the editor. Or, you can click Preview to make sure it looks right, and then click Publish. Here’s our blog with the new blog post containing a picture and video. While you’re getting to know you’re way around the controls in WordPress, the Preview feature will be your best friend while you try to organize the content to your liking. Conclusion It only takes a couple minutes to get started blogging at WordPress.com. Whether you want to write about your daily life, share pictures of your children, or review the latest books and gadgets, WordPress.com is a great place to get started for free. But we’ve only covered a small portion of the WordPress features…but this should get you started. Check back for more WordPress and blogging coverage coming up soon! Links Signup for a free WordPress.com account Similar Articles Productive Geek Tips Add Social Bookmarking (Digg This!) 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Add keyboard languages to XP, Vista, and Windows 7

- by Matthew Guay

Do you regularly need to type in multiple languages in Windows? Here we’ll show you the easy way to add and change input languages to your keyboard in XP, Vista, and Windows 7. Windows Vista and 7 come preinstalled with support for viewing a wide variety of languages, so adding an input language is fairly simply. Adding an input language is slightly more difficult in XP, and requires installing additional files if you need an Asian or Complex script language. First we show how to add an input language in Windows Vista and 7; it’s basically the same in both versions. Then, we show how to add a language to XP, and also how to add Complex Script support. Please note that this is only for adding an input language, which will allow you to type in the language you select. This does not change your user interface language. Change keyboard language in Windows 7 and Vista It is fairly simple to add or change a keyboard language in Windows 7 or Vista. In Windows 7, enter “keyboard language” in the Start menu search box, and select “Change keyboards or other input methods”. In Windows Vista, open Control Panel and enter “input language” in the search box and select “Change keyboards or other input methods”. This also works in Windows 7. Now, click Change Keyboards to add another keyboard language or change your default one. Our default input language is US English, and our default keyboard is the US keyboard layout. Click Add to insert another input language while still leaving your default input language installed. Here we selected the standard Thai keyboard language (Thai Kedmanee), but you can select any language you want. Windows offers almost any language you can imagine, so just look for the language you want, select it, and click Ok. Alternately, if you want, you can click Preview to see your layout choice before accepting it. This is only the default characters, not ones that will be activated with Shift or other keys (many Asian languages use many more characters than English, and require the use of Shift and other keys to access them all). Once your finished previewing, click close and then press Ok on the previous dialog. Now you will see both of your keyboard languages in the Installed services box. You can click Add to go back and get more, or move your selected language up or down (to change its priority), or simply click Apply to add the new language. Also, you can now change the default input language from the top menu. This is the language that your keyboard will start with when you boot your computer. So, if you mainly use English but also use another language, usually it is best to leave English as your default input language. Once you’ve pressed Apply or Ok, you will see a new icon beside your system tray with the initials of your default input language. If you click it, you can switch between input languages. Alternately you can switch input languages by pressing Alt+Shift on your keyboard. Some complex languages, such as Chinese, may have extra buttons to change input modes to accommodate their large alphabet. If you would like to change the keyboard shortcut for changing languages, go back to the Input Languages dialog, and select the “Advanced Key Settings” tab. Here you can change settings for Caps Lock and change or add key sequences to change between languages. Also, the On-Screen keyboard will display the correct keyboard language (here the keyboard is displaying Thai), which can be a helpful reference if your physical keyboard doesn’t have your preferred input language printed on it. To open this, simply enter “On-Screen keyboard” in the start menu search, or click All Programs>Accessories>On-Screen keyboard. Change keyboard language in Windows XP The process for changing the keyboard language in Windows XP is slightly different. Open Control Panel, and select “Date, Time, Language, and Regional Options”. Select “Add other languages”. Now, click Details to add another language. XP does not include support for Asian and complex languages by default, so if you need to add one of those languages we have details for that below. Click Add to add an input language. Select your desired language from the list, and choose your desired keyboard layout if your language offers multiple layouts. Here we selected Canadian French with the default layout. Now you will see both of your keyboard languages in the Installed services box. You can click Add to go back and add more, or move your selected language up or down (to change its priority), or simply click Apply to add the new language. Once you’ve pressed Apply or Ok, you will see a new icon beside your system tray with the initials of your default input language. If you click it, you can switch between input languages. Alternately you can switch input languages by pressing Alt+Shift on your keyboard. If you would like to change the keyboard shortcut for changing languages, go back to the Input Languages dialog, and click the “Key Settings” button on the bottom of the dialog. Here you can change settings for Caps Lock and change or add key sequences to change between languages. Add support to XP for Asian and Complex script languages Windows XP does not include support for Asian and Complex script languages by default, but you can easily add them to your computer. This is useful if you wish to type in one of these languages, or simply want to read text written in these languages, since XP will not display these languages correctly if they are not installed. If you wish to install Chinese, Japanese, and/or Korean, check the “Install files for East Asian languages” box. Or, if you need to install a complex script language (including Arabic, Armenian, Georgian, Hebrew, the Indic languages, Thai, and Vietnamese), check the “Install files for complex script and right-to-left languages” box. Choosing either of these options will open a prompt reminding you that this option will take up more disk space. Support for complex languages will require around 10Mb of hard drive space, but East Asian language support may require 230 Mb or more free disk space. Click Ok, and click apply to install your language files. You may have to insert your XP CD into your CD drive to install these files. Insert the disk, and then click Ok. Windows will automatically copy the files, including fonts for these languages… …and then will ask you to reboot your computer to finalize the settings. Click Yes, and then reopen the “Add other languages” dialog when your computer is rebooted, and add a language as before. Now you can add Complex and/or Asian languages to XP, just as above. Here is the XP taskbar language selector with Thai installed. Conclusion Unfortunately we haven’t found a way to add Asian and complex languages in XP without having an XP disc. If you know of a way, let us know in the comments. (No downloading the XP disc from torrent site answers please) Adding an input language is very important for bilingual individuals, and can also be useful if you simply need to occasionally view Asian or Complex languages in XP. And by following the correct instructions for your version of Windows, it should be very easy to add, change, and remove input languages. Similar Articles Productive Geek Tips Show Keyboard Shortcut Access Keys in Windows VistaKeyboard Ninja: 21 Keyboard Shortcut ArticlesAnother Desktop Cube for Windows XP/VistaThe "Up" Keyboard Shortcut for Windows 7 or Vista ExplorerWhat is ctfmon.exe And Why Is It Running? TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 PCmover Professional Make your Joomla & Drupal Sites Mobile with OSMOBI Integrate Twitter and Delicious and Make Life Easier Design Your Web Pages Using the Golden Ratio Worldwide Growth of the Internet How to Find Your Mac Address Use My TextTools to Edit and Organize Text

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XNA Notes 007

- by George Clingerman

Every week I keep wondering if there’s going to be enough activity in the community to keep doing these notes on a weekly basis and every week I’m reminded of just how awesome and active the XNA community is. There’s engines being made, tutorials being created, games being crafted. There’s information being shared, questions being answered and then there’s another whole community around the Xbox LIVE Indie Games themselves. It’s really incredibly to just watch all that’s going on and I’m glad I’m playing a small part in all of this. So here’s what I noticed happening in the XNA community last week. If there’s things I’m missing, always feel free to let me know. I love learning about new corners of the XNA community that I wasn’t aware of or just have been missing! XNA Developers: Uditha Bandara held an XNA Game Development Workshops at Singapore Universities http://uditha.wordpress.com/2011/02/18/xna-game-development-workshops-at-singapore-universities-event-update/ Binary Tweed gives his talks about Indie City and gives his opinion on the false promise of digital distribution http://www.develop-online.net/news/37053/OPINION-The-false-promise-of-digital-distribution Kris Steele posts his Trivia or Die postmortem http://www.krissteele.net/blogdetails.aspx?id=246 @MadNinjaSkills (James Johnston) posts his feelings on testing for XBLIG http://www.ezmuze.co.uk/101 Simon (@DDReaper) posts hints and tips for XNA developers to help get the size of their projects down http://twitter.com/#!/DDReaper/status/38279440924545024 http://xna-uk.net/blogs/darkgenesis/archive/2011/02/17/look-at-the-size-of-that-thing.aspx Michael B. McLaughlin proving why he should be an XNA MVP posts the list of commonly used value types in XNA games http://geekswithblogs.net/mikebmcl/archive/2011/02/17/list-of-commonly-used-value-types-in-xna-games.aspx http://twitter.com/#!/mikebmcl/status/38166541354811392 Paul Powell (@ITSligoPaul) posts about a common sprite batch as a game service http://itspaulsblog.blogspot.com/2011/02/xna-common-sprite-batch-as-game-service.html @SigilXNA (John Defenbaugh) posts his new level editor video for the sequel to Opac’s Journey http://twitter.com/SigilXNA/statuses/36548174373982209 http://twitter.com/#!/SigilXNA/status/36548174373982209 http://youtu.be/QHbmxB_2AW8 @jwatte updates kW Animation for XNA 4.0 http://www.enchantedage.com/xna-animation @DSebJ posts Blender to SunBurn http://twitter.com/#!/DSebJ/status/36564920224976896 http://dsebj.evolvingsoftware.com/?p=187 Ads and WP7 Games - @mechaghost shares his revenue data for his ad based games http://www.occasionalgamer.com/2011/02/09/ads-and-wp7-games/ Xbox LIVE Indie Games (XBLIG): Steven Hurdle posts day 100 of his quest to find a fantastic XBLIG purchase every day http://writingsofmassdeduction.com/2011/02/17/day-100-radiangames-ballistic/ Xbox 360 Indie Game Buying Guide - 12 games for $60 including several Xbox LIVE Indie games! (although if the XNA community was asked we could have recommended 60 games for $60...) http://www.indiegamemag.com/xbox360-indie-games-buying-guide/ The best selling Xbox LIVE Indie games of 2010 http://www.1up.com/news/xbox-live-most-popular-games I’d buy that for a dollar! - the California Literary Review points out a few gems on the XBLIG marketplace (and other places) where you can game on the cheap. http://calitreview.com/14125 Armless Octopus Episode 39 - The Indie Gem Octocast http://www.armlessoctopus.com/2011/02/17/armless-octocast-episode-39-the-indie-gem-octocast/ Ska Studios posts a plethora of updates http://www.ska-studios.com/2011/02/11/good-morning-gato-49/ http://www.ska-studios.com/2011/02/14/vampire-smile-valentines/ http://www.ska-studios.com/2011/02/16/the-dishwasher-vs-finds-a-home/ Kotaku posts about the Xbox LIVE Indie Game that makes you go Pew Pew Pew Pew Pew Pew http://kotaku.com/#!5760632/the-game-that-makes-you-go-pew-pew-pew-pew-pew-pew-pew GameMarx continues to be active and doing a ton for the XBLIG community reviews and Top 5 indie games of the week 2/4-2/10 http://www.gamemarx.com/video/the-show/22/ep-9-february-11-2010.aspx a new podcast Xbox Indie New Releases http://twitter.com/#!/gamemarx/status/36888849107910656 http://www.gamemarx.com/news/2011/02/13/a-new-podcast-xbox-indie-new-releases.aspx @MasterBlud uploads Indocalypse XBLIG Collections #2 http://www.youtube.com/watch?v=uzCZSv075mc&feature=youtu.be&a http://twitter.com/#!/MasterBlud/status/37100029697064960 Just Press Start interviews Michael Hicks from MichaelArts, 18 year old creator of Honor in Vengeance http://justpressstart.net/?p=465 Achievement Locked interviews Kris Steele of FunInfused Games http://xboxindies.wordpress.com/2011/02/11/interview-fun-infused-games/ XNA Game Development: XNA -UK launches their XAP test service to help the XNA community http://xna-uk.net/blogs/news/archive/2011/02/18/xna-uk-xap-test-service-now-live.aspx Transmute shows off a video of the standard character editor http://www.youtube.com/watch?v=qqH6gErG948&feature=youtu.be Microsoft Tech Student introduces their first tech student of the month. Meet Daniel Van Tassel from the University of Utah and learn how he created an Xbox LIVE Indie Game using XNA Studio http://blogs.msdn.com/b/techstudent/archive/2010/12/22/introducing-our-first-tech-student-of-the-month-daniel-van-tassel.aspx XNA for Silverlight Developers Part 3 - Animation (transforms) http://www.silverlightshow.net/items/XNA-for-Silverlight-developers-Part-3-Animation-transforms.aspx XNA for Silverlight Developers Part 4 - Animation (frame based) http://www.silverlightshow.net/items/XNA-for-Silverlight-developers-Part-4-Animation-frame-based.aspx @suhinini tweets about an XNA Sprite Font generation tool http://twitter.com/#!/suhinini/status/36841370131890176 http://www.nubik.com/SpriteFont/ XNATouch 1.5 is out and in it’s words is faster, simpler, more reliable and has the XNA 4.0 API http://monogame.codeplex.com/releases/view/60815 IndieCity is hosting marketing workshops for Indie Developers (UK and US) http://forums.create.msdn.com/forums/p/75197/457654.aspx#457654 New York Students - Learn XNA and Silverlight for Xbox 360 and Windows Phone 7 http://forums.create.msdn.com/forums/p/72753/456964.aspx#456964 http://blogs.msdn.com/b/andrewparsons/archive/2011/01/13/learn-to-build-your-own-games-for-xbox-360-and-windows-phone-7.aspx http://blogs.msdn.com/b/andrewparsons/archive/2011/01/13/build-a-game-in-48-hours-win-a-kinect-or-windows-phone-7.aspx Extra Credits: Videogame Music http://www.escapistmagazine.com/videos/view/extra-credits/2019-Videogame-Music Steve Pavlina posts an article with useful information for all XNA/XBLIG developers http://www.stevepavlina.com/blog/2011/02/completion-vs-perfection/

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SQL SERVER – Difference Between DATETIME and DATETIME2

- by pinaldave

Yesterday I have written a very quick blog post on SQL SERVER – Difference Between GETDATE and SYSDATETIME and I got tremendous response for the same. I suggest you read that blog post before continuing this blog post today. I had asked people to honestly take part and share their view about above two system function. There are few emails as well few comments on the blog post asking question how did I come to know the difference between the same. The answer is real world issues. I was called in for performance tuning consultancy where I was asked very strange question by one developer. Here is the situation he was facing. System had a single table with two different column of datetime. One column was datelastmodified and second column was datefirstmodified. One of the column was DATETIME and another was DATETIME2. Developer was populating them with SYSDATETIME respectively. He was always thinking that the value inserted in the table will be the same. This table was only accessed by INSERT statement and there was no updates done over it in application.One fine day he ran distinct on both of this column and was in for surprise. He always thought that both of the table will have same data, but in fact they had very different data. He presented this scenario to me. I said this can not be possible but when looked at the resultset, I had to agree with him. Here is the simple script generated to demonstrate the problem he was facing. This is just a sample of original table. DECLARE @Intveral INT SET @Intveral = 10000 CREATE TABLE #TimeTable (FirstDate DATETIME, LastDate DATETIME2) WHILE (@Intveral > 0) BEGIN INSERT #TimeTable (FirstDate, LastDate) VALUES (SYSDATETIME(), SYSDATETIME()) SET @Intveral = @Intveral - 1 END GO SELECT COUNT(DISTINCT FirstDate) D_GETDATE, COUNT(DISTINCT LastDate) D_SYSGETDATE FROM #TimeTable GO SELECT DISTINCT a.FirstDate, b.LastDate FROM #TimeTable a INNER JOIN #TimeTable b ON a.FirstDate = b.LastDate GO SELECT * FROM #TimeTable GO DROP TABLE #TimeTable GO Let us see the resultset. You can clearly see from result that SYSDATETIME() does not populate the same value in the both of the field. In fact the value is either rounded down or rounded up in the field which is DATETIME. Event though we are populating the same value, the values are totally different in both the column resulting the SELF JOIN fail and display different DISTINCT values. The best policy is if you are using DATETIME use GETDATE() and if you are suing DATETIME2 use SYSDATETIME() to populate them with current date and time to accurately address the precision. As DATETIME2 is introduced in SQL Server 2008, above script will only work with SQL SErver 2008 and later versions. I hope I have answered few questions asked yesterday. Reference: Pinal Dave (http://www.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL DateTime, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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Improving Partitioned Table Join Performance

- by Paul White

The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x, CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) ); CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x, CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY); WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME(); SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID; SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50); -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE); -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory: Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME(); CREATE TABLE #P ( partition_number integer PRIMARY KEY); INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1; SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; DROP TABLE #P; SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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Connecting to DB2 from SSIS

- by Christopher House

The project I'm currently working on involves moving various pieces of data from a legacy DB2 environment to some SQL Server and flat file locations. Most of the data flows are real time, so they were a natural fit for the client's MQSeries on their iSeries servers and BizTalk to handle the messaging. Some of the data flows, however, are daily batch type transmissions. For the daily batch transmissions, it was decided that we'd use SSIS to pull the data direct from DB2 to either a SQL Server or flat file. I'm not at all an SSIS guy, I've done a bit here and there, but mainly for situations were we needed to move data from a dev environment to QA, mostly informal stuff like that. And, as much as I'm not an SSIS guy, I'm even less a DB2/iSeries guy. Prior to this engagement, my knowledge of DB2 was limited to the fact that it's an IBM product and that it was probably a DBMS flatform (that's what the DB in DB2 means, right?). One of my first goals when I came onto this project was to develop of POC SSIS package to pull some data from DB2 and dump it to a flat file. It sounded like a pretty straight forward task. As always, the devil is in the details. Configuring the DB2 connection manager took a bit of trial and error. As such, I thought I'd post my experiences here in hopes that they might save someone the efforts I went through. That being said, please keep in mind, as I pointed out, I'm not at all a DB2 guy, so my terminology and explanations may not be 100% spot on. Before you get started, you need to figure out how you're going to connect to DB2. From the research I did, it looks like there are a few options. IBM has both an OLE DB and .Net data provider which can be found here. I installed their client access tools and tried to use both the .Net and OLE DB providers but I received an error message from both when attempting to connect to the iSeries that indicated I needed a license for a product called DB2 Connect. I inquired with one of my client's iSeries resources about a license for this product and it appears they didn't have one, so that meant the IBM drivers were out. The other option that I found quite a bit of discussion around was Microsoft's OLE DB Provider for DB2. This driver is part of the feature pack for SQL Server 2008 Enterprise Edition and can be downloaded here. As it turns out, I already had Microsoft's driver installed on my dev VM, which stuck me as odd since I hadn't installed it. I discovered that the driver is installed with the BizTalk adapter pack for host systems, which was also installed on my VM. However, it looks like the version used by the adapter pack is newer than the version provided in the SQL Server feature pack. Once you get the driver installed, create a connection manager in your package just like you normally would and select the Microsoft OLE DB Provider for DB2 from the list of available drivers. After you select the driver, you'll need to enter in your host name, login credentials and initial catalog. A couple of things to note here. First, the Initial catalog needs to be the same as your host name. Not sure why that is, but trust me, it just does. Second, for credentials, in my environment, we're using what the client's iSeries people refer to as "profiles". I guess this is similar to SQL auth in the SQL Server world. In other words, they've given me a username and password for connecting to DB, so I've entered it here. Next, click the Data Links button. On the Data Links screen, enter your package collection on the first tab. Package collection is one of those DB2 concepts I'm still trying to figure out. From the little bit I've read, packages are used to control SQL compilation and each DB2 connection needs one. The package collection, I believe, controls where your package is created. One of the iSeries folks I've been working with told me that I should always use QGPL for my package collection, as QGPL is "general purpose" and doesn't require any additional authority. Next click the ellipsis next to the Network drop-down. Here you'll want to enter your host name again. Again, not sure why you need to do this, but trust me, my connection wouldn't work until I entered my hostname here. Finally, go to the Advanced tab, select your DBMS platform and check Process binary as character. My environment is DB2 on the iSeries and iSeries is the replacement for AS/400, so I selected DB2/AS400 for my platform. Process binary as character was necessary to handle some of the DB2 data types. I had a few columns that showed all their data as "System.Byte[]". Checking Process binary as character resolved this. At this point, you should be good to go. You can go back to the Connection tab on the Data Links dialog to perform a couple of tests to validate your configuration. The Test Connection button is obvious, this just verifies you can connect to the host using the configuration data you've entered. The Packages button will attempt to connect to the host and create the packages required to execute queries. This isn't meant to be a comprehensive look SSIS and DB2, these are just some of the notes I've come up with since I've started working with DB2 and SSIS. I'm sure as I continue developing my packages, I'll find more quirks and will post them here.

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SQL SERVER – Introduction to Rollup Clause

- by pinaldave

In this article we will go over basic understanding of Rollup clause in SQL Server. ROLLUP clause is used to do aggregate operation on multiple levels in hierarchy. Let us understand how it works by using an example. Consider a table with the following structure and data: CREATE TABLE tblPopulation ( Country VARCHAR(100), [State] VARCHAR(100), City VARCHAR(100), [Population (in Millions)] INT ) GO INSERT INTO tblPopulation VALUES('India', 'Delhi','East Delhi',9 [...]

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Enhanced REST Support in Oracle Service Bus 11gR1

- by jeff.x.davies

In a previous entry on REST and Oracle Service Bus (see http://blogs.oracle.com/jeffdavies/2009/06/restful_services_with_oracle_s_1.html) I encoded the REST query string really as part of the relative URL. For example, consider the following URI: http://localhost:7001/SimpleREST/Products/id=1234 Now, technically there is nothing wrong with this approach. However, it is generally more common to encode the search parameters into the query string. Take a look at the following URI that shows this principle http://localhost:7001/SimpleREST/Products?id=1234 At first blush this appears to be a trivial change. However, this approach is more intuitive, especially if you are passing in multiple parameters. For example: http://localhost:7001/SimpleREST/Products?cat=electronics&subcat=television&mfg=sony The above URI is obviously used to retrieve a list of televisions made by Sony. In prior versions of OSB (before 11gR1PS3), parsing the query string of a URI was more difficult than in the current release. In 11gR1PS3 it is now much easier to parse the query strings, which in turn makes developing REST services in OSB even easier. In this blog entry, we will re-implement the REST-ful Products services using query strings for passing parameter information. Lets begin with the implementation of the Products REST service. This service is implemented in the Products.proxy file of the project. Lets begin with the overall structure of the service, as shown in the following screenshot. This is a common pattern for REST services in the Oracle Service Bus. You implement different flows for each of the HTTP verbs that you want your service to support. Lets take a look at how the GET verb is implemented. This is the path that is taken of you were to point your browser to: http://localhost:7001/SimpleREST/Products/id=1234 There is an Assign action in the request pipeline that shows how to extract a query parameter. Here is the expression that is used to extract the id parameter: $inbound/ctx:transport/ctx:request/http:query-parameters/http:parameter[@name="id"]/@value The Assign action that stores the value into an OSB variable named id. Using this type of XPath statement you can query for any variables by name, without regard to their order in the parameter list. The Log statement is there simply to provided some debugging info in the OSB server console. The response pipeline contains a Replace action that constructs the response document for our rest service. Most of the response data is static, but the ID field that is returned is set based upon the query-parameter that was passed into the REST proxy. Testing the REST service with a browser is very simple. Just point it to the URL I showed you earlier. However, the browser is really only good for testing simple GET services. The OSB Test Console provides a much more robust environment for testing REST services, no matter which HTTP verb is used. Lets see how to use the Test Console to test this GET service. Open the OSB we console (http://localhost:7001/sbconsole) and log in as the administrator. Click on the Test Console icon (the little "bug") next to the Products proxy service in the SimpleREST project. This will bring up the Test Console browser window. Unlike SOAP services, we don't need to do much work in the request document because all of our request information will be encoded into the URI of the service itself. Belore the Request Document section of the Test Console is the Transport section. Expand that section and modify the query-parameters and http-method fields as shown in the next screenshot. By default, the query-parameters field will have the tags already defined. You just need to add a tag for each parameter you want to pass into the service. For out purposes with this particular call, you'd set the quer-parameters field as follows: <tp:parameter name="id" value="1234" /> </tp:query-parameters> Now you are ready to push the Execute button to see the results of the call. That covers the process for parsing query parameters using OSB. However, what if you have an OSB proxy service that needs to consume a REST-ful service? How do you tell OSB to pass the query parameters to the external service? In the sample code you will see a 2nd proxy service called CallREST. It invokes the Products proxy service in exactly the same way it would invoke any REST service. Our CallREST proxy service is defined as a SOAP service. This help to demonstrate OSBs ability to mediate between service consumers and service providers, decreasing the level of coupling between them. If you examine the message flow for the CallREST proxy service, you'll see that it uses an Operational branch to isolate processing logic for each operation that is defined by the SOAP service. We will focus on the getProductDetail branch, that calls the Products REST service using the HTTP GET verb. Expand the getProduct pipeline and the stage node that it contains. There is a single Assign statement that simply extracts the productID from the SOA request and stores it in a local OSB variable. Nothing suprising here. The real work (and the real learning) occurs in the Route node below the pipeline. The first thing to learn is that you need to use a route node when calling REST services, not a Service Callout or a Publish action. That's because only the Routing action has access to the $oubound variable, especially when invoking a business service. The Routing action contains 3 Insert actions. The first Insert action shows how to specify the HTTP verb as a GET. The second insert action simply inserts the XML node into the request. This element does not exist in the request by default, so we need to add it manually. Now that we have the element defined in our outbound request, we can fill it with the parameters that we want to send to the REST service. In the following screenshot you can see how we define the id parameter based on the productID value we extracted earlier from the SOAP request document. That expression will look for the parameter that has the name id and extract its value. That's all there is to it. You now know how to take full advantage of the query parameter parsing capability of the Oracle Service Bus 11gR1PS2. Download the sample source code here: rest2_sbconfig.jar Ubuntu and the OSB Test Console You will get an error when you try to use the Test Console with the Oracle Service Bus, using Ubuntu (or likely a number of other Linux distros also). The error (shown below) will state that the Test Console service is not running. The fix for this problem is quite simple. Open up the WebLogic Server administrator console (usually running at http://localhost:7001/console). In the Domain Structure window on the left side of the console, select the Servers entry under the Environment heading. The select the Admin Server entry in the main window of the console. By default, you should be viewing the Configuration tabe and the General sub tab in the main window. Look for the Listen Address field. By default it is blank, which means it is listening on all interfaces. For some reason Ubuntu doesn't like this. So enter a value like localhost or the specific IP address or DNS name for your server (usually its just localhost in development envirionments). Save your changes and restart the server. Your Test Console will now work correctly.

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Using a "white list" for extracting terms for Text Mining

- by [email protected]

In Part 1 of my post on "Generating cluster names from a document clustering model" (part 1, part 2, part 3), I showed how to build a clustering model from text documents using Oracle Data Miner, which automates preparing data for text mining. In this process we specified a custom stoplist and lexer and relied on Oracle Text to identify important terms. However, there is an alternative approach, the white list, which uses a thesaurus object with the Oracle Text CTXRULE index to allow you to specify the important terms. INTRODUCTIONA stoplist is used to exclude, i.e., black list, specific words in your documents from being indexed. For example, words like a, if, and, or, and but normally add no value when text mining. Other words can also be excluded if they do not help to differentiate documents, e.g., the word Oracle is ubiquitous in the Oracle product literature. One problem with stoplists is determining which words to specify. This usually requires inspecting the terms that are extracted, manually identifying which ones you don't want, and then re-indexing the documents to determine if you missed any. Since a corpus of documents could contain thousands of words, this could be a tedious exercise. Moreover, since every word is considered as an individual token, a term excluded in one context may be needed to help identify a term in another context. For example, in our Oracle product literature example, the words "Oracle Data Mining" taken individually are not particular helpful. The term "Oracle" may be found in nearly all documents, as with the term "Data." The term "Mining" is more unique, but could also refer to the Mining industry. If we exclude "Oracle" and "Data" by specifying them in the stoplist, we lose valuable information. But it we include them, they may introduce too much noise. Still, when you have a broad vocabulary or don't have a list of specific terms of interest, you rely on the text engine to identify important terms, often by computing the term frequency - inverse document frequency metric. (This is effectively a weight associated with each term indicating its relative importance in a document within a collection of documents. We'll revisit this later.) The results using this technique is often quite valuable. As noted above, an alternative to the subtractive nature of the stoplist is to specify a white list, or a list of terms--perhaps multi-word--that we want to extract and use for data mining. The obvious downside to this approach is the need to specify the set of terms of interest. However, this may not be as daunting a task as it seems. For example, in a given domain (Oracle product literature), there is often a recognized glossary, or a list of keywords and phrases (Oracle product names, industry names, product categories, etc.). Being able to identify multi-word terms, e.g., "Oracle Data Mining" or "Customer Relationship Management" as a single token can greatly increase the quality of the data mining results. The remainder of this post and subsequent posts will focus on how to produce a dataset that contains white list terms, suitable for mining. CREATING A WHITE LIST We'll leverage the thesaurus capability of Oracle Text. Using a thesaurus, we create a set of rules that are in effect our mapping from single and multi-word terms to the tokens used to represent those terms. For example, "Oracle Data Mining" becomes "ORACLEDATAMINING." First, we'll create and populate a mapping table called my_term_token_map. All text has been converted to upper case and values in the TERM column are intended to be mapped to the token in the TOKEN column. TERM TOKEN DATA MINING DATAMINING ORACLE DATA MINING ORACLEDATAMINING 11G ORACLE11G JAVA JAVA CRM CRM CUSTOMER RELATIONSHIP MANAGEMENT CRM ... Next, we'll create a thesaurus object my_thesaurus and a rules table my_thesaurus_rules: CTX_THES.CREATE_THESAURUS('my_thesaurus', FALSE); CREATE TABLE my_thesaurus_rules (main_term VARCHAR2(100), query_string VARCHAR2(400)); We next populate the thesaurus object and rules table using the term token map. A cursor is defined over my_term_token_map. As we iterate over the rows, we insert a synonym relationship 'SYN' into the thesaurus. We also insert into the table my_thesaurus_rules the main term, and the corresponding query string, which specifies synonyms for the token in the thesaurus. DECLARE cursor c2 is select token, term from my_term_token_map; BEGIN for r_c2 in c2 loop CTX_THES.CREATE_RELATION('my_thesaurus',r_c2.token,'SYN',r_c2.term); EXECUTE IMMEDIATE 'insert into my_thesaurus_rules values (:1,''SYN(' || r_c2.token || ', my_thesaurus)'')' using r_c2.token; end loop; END; We are effectively inserting the token to return and the corresponding query that will look up synonyms in our thesaurus into the my_thesaurus_rules table, for example: 'ORACLEDATAMINING' SYN ('ORACLEDATAMINING', my_thesaurus)At this point, we create a CTXRULE index on the my_thesaurus_rules table: create index my_thesaurus_rules_idx on my_thesaurus_rules(query_string) indextype is ctxsys.ctxrule; In my next post, this index will be used to extract the tokens that match each of the rules specified. We'll then compute the tf-idf weights for each of the terms and create a nested table suitable for mining.

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