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  • Mount - Unable to find suitable address

    - by Benny
    I am trying to mount my Windows share through my Ubuntu box (no xwindow), but I continue to get Unable to find suitable address I have tried using the raw IP address, I have checked the credentials, I have disabled the Windows firewall, but I cannot find anything wrong. benny@backup:~$ sudo mount -t cifs //my-desk/j -o username=me,password=s)mePasss /mnt/sync Unable to find suitable address. benny@backup:~$ ping my-desk PING my-desk (10.10.10.43) 56(84) bytes of data. ? --- my-desk ping statistics --- 2 packets transmitted, 0 received, 100% packet loss, time 1008ms benny@backup:~$ sudo mount -t cifs //10.10.10.43/j -o username=me,password=s)mePasss /mnt/sync Unable to find suitable address. Any help would be greatly appreciated!

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  • Managing Multiple dedicated servers centrally using a Web GUI tools?

    - by Sampath
    Application Architecture I am having a single ruby on rails application code running with multiple instances (ie. each client having identical sub domains) running on a multiple dedicated server using phusion passenger + nginx. sub domains setup done using vhost option in nginx passenger module. For Example server 1 serving 1 - 100 client with identical sub domains www.client1.product.com upto www.client100.product.com server 2 serving 101 - 200 client with identical sub domains www.client101.product.com upto www.client200.product.com server 3 serving 201 - 300 client with identical sub domains www.client201.product.com upto www.client300.product.com What my question is i need to centrally manage all my N dedicated servers using an gui tool I am looking for Web GUI tool to manage tasks like 1) backup all mysql databases automatically from all dedicated servers and send it to an some FTP backup drive 2) back files and folders from all dedicated servers and send it to an some FTP backup drive 3) need to manage firewall (CSF http://configserver.com/cp/csf.html) centrally for all dedicated servers 4) look to see server load , bandwidth used in graphical manner for all N no of dedicated servers Note: I am prefer to looking for an open source solution

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  • Redehost Transforms Cloud & Hosting Services with MySQL Enterprise Edition

    - by Mat Keep
    RedeHost are one of Brazil's largest cloud computing and web hosting providers, with more than 60,000 customers and 52,000 web sites running on its infrastructure. As the company grew, Redehost needed to automate operations, such as system monitoring, making the operations team more proactive in solving problems. Redehost also sought to improve server uptime, robustness, and availability, especially during backup windows, when performance would often dip. To address the needs of the business, Redehost migrated from the community edition of MySQL to MySQL Enterprise Edition, which has delivered a host of benefits: - Pro-active database management and monitoring using MySQL Enterprise Monitor, enabling Redehost to fulfil customer SLAs. Using the Query Analyzer, Redehost were able to more rapidly identify slow queries, improving customer support - Quadrupled backup speed with MySQL Enterprise Backup, leading to faster data recovery and improved system availability - Reduced DBA overhead by 50% due to the improved support capabilities offered by MySQL Enterprise Edition. - Enabled infrastructure consolidation, avoiding unnecessary energy costs and premature hardware acquisition You can learn more from the full Redehost Case Study Also, take a look at the recently updated MySQL in the Cloud whitepaper for the latest developments that are making it even simpler and more efficient to develop and deploy new services with MySQL in the cloud

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  • SQL SERVER – Recover the Accidentally Renamed Table

    - by pinaldave
    I have no answer to following question. I saw a desperate email marked as urgent delivered in my mailbox. “I accidentally renamed table in my SSMS. I was scrolling very fast and I made mistakes. It was either because I double clicked or clicked on F2 (shortcut key for renaming). However, I have made the mistake and now I have no idea how to fix this. I am in big trouble. Help me get my original tablename.” I have seen many similar scenarios in my life and they give me a very good opportunity to preach wisdom but when the house is burning, we cannot talk about how we should have conserved the water earlier. The goal at that point is to put off the fire as fast as we can. I decided to answer this email with my best knowledge. If you have renamed the table, I think you pretty much is out of luck. Here are few things which you can do which can give you idea about what your tablename can be if you are lucky. Method 1: (Not Recommended but try your luck) Check your naming convention of your system. I have often seen that many organizations name their index as IX_TableName_Colms or name their keys as FK_TableName1_TableName2_Cols. If your organization is following the same you can get the name from your table, you may refer your keys. Again, note that this is quite possible that your tablename was already renamed and your keys were not updated. This can easily lead you to select incorrect name. I think follow this if you are confident or move to the next method. Method 2: (Not Recommended but try your luck) This method is also based on your orgs naming convention. If you use the name of the table in any columnname (some organizations use tablename in their incremental identity column name), you can get that name from there. Method 3: (Not Recommended but try your luck) If you know where your table was used in your stored procedures, you can script your stored procedure and find the name of the table back. Method 4: (Try your luck) All the best organizations first create a data model of the schema and there is good chance that this table is used there, you should take your chances and refer original document. If your organization is good at managing docs or source code, you will get the name of the table back for sure. Method 5: (It WORKS but try on a development server) There is no sure way to get you the name of the table which you accidentally renamed however, there is one way which will work for sure. You need to take your latest full backup and restore it on your development server (remember not on production or where you have renamed this column). Now restore latest differential file of the full backup. Now restore all the log files one by one making sure that you are restoring before the point of time of you renamed the tablename. Now go to explore and this will give you the name of the table which you have renamed. If you are confident that the same table existed with the same name when the last full backup was made, you do not have to go to all the steps. You can just get the name of the table directly from last backup’s restore. Read the article about Backup Timeline. Wisdom: How can I miss to preach wisdom when I get the opportunity to do so? Here are a few points to remember. Use a different account to explore production environment. Do not use the same account which have all the rights and permissions all the time. Use the account which has read only permissions if there are no modification required. Use policy based management to prevent changes which are accidental. If there was policy of valid names, the accidental change of the table was not possible unless it was intentional delibarate changes. Have a proper auditing of the system in place. You can use DDL triggers but be careful with its usage (get it reviewed properly first). (Add your suggestion here) I guess Method 5 will work all the time (using point in time restore). Everything else is chance of luck and if you are lucky are bad – you will get further incorrect name. Now go back and read the first line of this blog. Out of five method four methods are just lucky guesses. The method 5 will work but again it is a lengthy process if the size of the database is huge or if you do not have full backup. Did I miss anything obvious? Please leave a comment and I will publish your answer with due credit. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • How to Back Up Your Linux System With Back In Time

    - by Chris Hoffman
    Ubuntu includes Déjà Dup, an integrated backup tool, but some people prefer Back In Time instead. Back In Time has several advantages over Déjà Dup, including a less-opaque backup format, integrated backup file browser, and more configurability. Déjà Dup still has a few advantages, notably its optional encryption and simpler interface, but Back In Time gives Déjà Dup a run for its money. How to Sync Your Media Across Your Entire House with XBMC How to Own Your Own Website (Even If You Can’t Build One) Pt 2 How to Own Your Own Website (Even If You Can’t Build One) Pt 1

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  • Disable auto-mount for particular partitions on usb drives

    - by nealmcb
    I have a big USB disk with 3 partitions: one for backup and two other bootable ones for installing and testing new distros. I want the backup partition automounted on boot. But I don't want the two test partitions automounted. Despite my use of "noauto" in /etc/fstab, something (gnome?) seems to be mounting them when I plug the drive it. LABEL=mybook /srv/backup ext4 defaults 0 2 LABEL=mybook-root /media/mybook-root ext4 user,noauto 0 2 LABEL=mybook-spare /media/mybook-spare ext4 user,noauto 0 2 In previous Ubuntu distributions it seems that it was possible to configure gnome so it would avoid mounting particular partitions on removable drives like USB: gnome-mount --write-settings --mount-options noauto --device /dev/sda1 This is no longer available in Lucid (when did it go away?) Is there another way to do this now?

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  • Exalytics Disaster Recovery

    - by Saresh
    Q:Where can you find more information about Exalytics Disaster Recovery? Ans: Exalytics Disaster Recovery: http://docs.oracle.com/cd/E41246_01/bi.1/e39709/admin_dr.htm#BABCFGEC Note 1568360.1 -Oracle Exalytics Deployment Guide (Download the whitepaper attached to the Note) OBIEE http://docs.oracle.com/cd/E28280_01/bi.1111/e10541/backup.htm#CHDFEIGF Note 1316073.1 - OBIEE 11g: Recommended Strategies For Disaster Recovery or Backup Oracle Hyperion EPM http://docs.oracle.com/cd/E17236_01/epm.1112/epm_high_avail_11121.pdf (Though this is for Hyperion EPM 11.1.2.1, it is applicable to 11.1.2.2 as well) TimesTen: http://docs.oracle.com/cd/E21901_01/doc/timesten.1122/e21632/migrate.htmhttp://docs.oracle.com/cd/E21901_01/doc/timesten.1122/e21635/standbycache.htm#CBAJDJBD EPM Disaster Recovery : http://www.oracle.com/technetwork/middleware/bi-foundation/epm-dr-best-practice-130229.ppt Oracle® Enterprise Performance Management System Backup and Recovery Guide :http://docs.oracle.com/cd/E17236_01/epm.1112/epm_backup_recovery_1112200.pdf

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  • Deploying Data-Tier Applications of SQL Server 2008 R2

    SQL Server 2008 R2 Data-Tier Applications make database development, deployment and management much easier. When you create and build a Data Tier Application, it creates a single, self-contained unit of deployment called a DAC package. Arshad Ali shows you how to deploy the created DAC package and discusses the different methods of deployment. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • Writing a Data Access Layer (DAL) for SQL Server

    In this tip, I am going to show you how you can create a Data Access Layer (to store, retrieve and manage data in relational database) in ADO .NET. I will show how you can make it data provider independent, so that you don't have to re-write your data access layer if the data storage source changes and also you can reuse it in other applications that you develop. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • Is ignoring clients data during an automatic upgrading acceptable?

    - by A competent translator
    I recently faced a deletion of my calendar and notes data inside a third party application ( Horde ) on my online space. When I told the web hosting provider they replied that they were doing an upgrade to system software (!!) and client third party applications are not within their reach or backup policy. They don't even have a backup of my data. Is this practice acceptable from a web hosting provider, even for an individual clients ? I know that backing up my data is my responsibility but I anticipated that backup copies done by the host would be available when needed.

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  • Linqpad and Autocompletion

    I have mentioned before about doing development for StreamInsight in Linqpad. I have it installed on two separate PCs and I have enabled autocompletion on only one of them. Whilst both versions are an excellent tool, the one with autocompletion enabled is so much easier to use. After enabling autocompletion you can see I now get parameter listing Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • BIT of a Problem

    The BIT data type is an awkward fit for a SQL database. It doesn't have just two values, and it can do unexpected things in expressions. What is worse, it is a flag rather than a predicate, and so its overuse, along with bit masks, is a prime candidate for being listed as a 'SQL Code Smell'. Joe Celko makes the case. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • Contiguous Time Periods

    It is always more efficient to maintain referential integrity by using constraints rather than triggers. Sometimes it isn't obvious how to do this. Until a recent idea by Alex Kuznetsov, the history table presented problems for checking data that were difficult to solve with constraints. Joe Celko explains. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • Data Conversion in SQL Server

    Most of the time, you do not have to worry about implicit conversion in SQL expressions, or when assigning a value to a column. Just occasionally, though, you'll find that data gets truncated, queries run slowly, or comparisons just seem plain wrong. Robert Sheldon explains why you sometimes need to be very careful if you mix data types when manipulating values. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • Understanding and Using Parallelism in SQL Server

    SQL Server is able to make implicit use of parallelism to speed SQL queries. Quite how it does it, and how you can be sure that it is doing so, isn't entirely obvious to most of us. Paul White begins a series that makes it all seem simple, starting at the gentle level of counting Jelly Beans. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • Concatenating Rows

    Often in database design we store different values in rows to take advantage of a normalized design. However many times we need to combine multiple rows of data into one row for a report of some sort. New author Carl P. Anderson brings us some interesting T-SQL code to accomplish this. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • How do I update mysql database when posting form without using hidden inputs?

    - by user1322707
    I have a "members" table in mysql which has approximately 200 field names. Each user is given up to 7 website templates with 26 different values they can insert unique data into for each template. Each time they create a template, they post the form with the 26 associated values. These 26 field names are the same for each template, but are differentiated by an integer at the end, ie _1, _2, ... _7. In the form submitting the template, I have a variable called $pid_sum which is inserted at the end of each field name to identify which template they are creating. For instance: <form method='post' action='create.template.php'> <input type='hidden' name='address_1' value='address_1'> <input type='hidden' name='city_1' value='city_1'> <input type='hidden' name='state_1' value='state_1'> etc... <input type='hidden' name='address_1' value='address_2'> <input type='hidden' name='city_1' value='city_2'> <input type='hidden' name='state_1' value='state_2'> etc... <input type='hidden' name='address_2' value='address_3'> <input type='hidden' name='city_2' value='city_3'> <input type='hidden' name='state_2' value='state_3'> etc... <input type='hidden' name='address_2' value='address_4'> <input type='hidden' name='city_2' value='city_4'> <input type='hidden' name='state_2' value='state_4'> etc... <input type='hidden' name='address_2' value='address_5'> <input type='hidden' name='city_2' value='city_5'> <input type='hidden' name='state_2' value='state_5'> etc... <input type='hidden' name='address_2' value='address_6'> <input type='hidden' name='city_2' value='city_6'> <input type='hidden' name='state_2' value='state_6'> etc... <input type='hidden' name='address_2' value='address_7'> <input type='hidden' name='city_2' value='city_7'> <input type='hidden' name='state_2' value='state_7'> etc... // Visible form user fills out in creating their template ($pid_sum converts // into an integer 1-7, depending on what template they are filling out) <input type='' name='address_$pid_sum'> <input type='' name='city_$pid_sum'> <input type='' name='state_$pid_sum'> etc... <input type='submit' name='save_button' id='save_button' value='Save Settings'> <form> Each of these need updated in a hidden input tag with each form post, or the values in the database table (which aren't submitted with the form) get deleted. So I am forced to insert approximately 175 hidden input tags with every creation of 26 new values for one of the 7 templates. Is there a PHP function or command that would enable me to update all these values without inserting 175 hidden input tags within each form post? Here is the create.template.php file which the form action calls: <?php $q=new Cdb; $t->set_file("content", "create_template.html"); $q2=new CDB; $query="SELECT menu_category FROM menus WHERE link='create.template.ag.php'"; $q2->query($query); $toall=0; if ($q2->nf()<1) { $toall=1; } while ($q2->next_record()) { if ($q2->f('menu_category')=="main") { $toall=1; } } if ($toall==0) { get_logged_info(); $q2=new CDB; $query="SELECT id FROM menus WHERE link='create_template.php'"; $q2->query($query); $q2->next_record(); $query="SELECT membership_id FROM menu_permissions WHERE menu_item='".$q2->f("id")."'"; $q2->query($query); while ($q2->next_record()) { $permissions[]=$q2->f("membership_id"); } if (count($permissions)>0) { $error='<center><font color="red"><b>You do not have access to this area!<br><br>Upgrade your membership level!</b></font></center>'; foreach ($permissions as $value) { if ($value==$q->f("membership_id")) { $error=''; break; } } if ($error!="") { die("$error"); } } } $member_id=$q->f("id"); $pid=$q->f("pid"); $pid_sum = $pid +1; $first_name=$q->f("first_name"); $last_name=$q->f("last_name"); $email=$q->f("email"); echo " // THIS IS WHERE THE HTML FORM GOES "; replace_tags_t($q->f("id"), $t); ?>

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  • ?????? ??????????! ?Gold???? vol.4

    - by M.Morozumi
    ??????????????????????????????????????????????????????????????????? ???ORACLE MASTER Gold Oracle Database 11g??????????????????????? ------------------------------- ????: ???????????????????????????????????1????????? a. BACKUP DATABASE ???????????? b. LIKE ?????????? BACKUP ARCHIVELOG ???????????? c. ALL ?????????? BACKUP ARCHIVELOG ???????????? d. ?????????????????? 2 ?????? ???????????????

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  • ?????? ??????????! ?Gold???? vol.4 <??>

    - by M.Morozumi
    ???ORACLE MASTER Gold Oracle Database 11g?????????????? ?????????????????????? ------------------------------- ???????????????????????????????????1????????? a. BACKUP DATABASE ???????????? b. LIKE ?????????? BACKUP ARCHIVELOG ???????????? c. ALL ?????????? BACKUP ARCHIVELOG ???????????? d. ?????????????????? 2 ?????? ??????????????? ------------------------------- ??:d. ?????????????????? 2 ?????? ??: ?????????????????? 1???????????????????????????

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  • Can this Query be corrected or different table structure needed? (database dumps provided)

    - by sandeepan
    This is a bit lengthy but I have provided sufficient details and kept things very clear. Please see if you can help. (I will surely accept answer if it solves my problem) I am sure a person experienced with this can surely help or suggest me to decide the tables structure. About the system:- There are tutors who create classes A tags based search approach is being followed Tag relations are created/edited when new tutors registers/edits profile data and when tutors create classes (this makes tutors and classes searcheable).For simplicity, let us consider only tutor name and class name are the fields which are matched against search keywords. In this example, I am considering - tutor "Sandeepan Nath" has created a class called "first class" tutor "Bob Cratchit" has created a class called "new class" Desired search results- AND logic to be appied on the search keywords and match against class and tutor data(class name + tutor name), in other words, All those classes be shown such that all the search terms are present in the class name or its tutor name. Example to be clear - Searching "first class" returns class with id_wc = 1. Working Searching "Sandeepan class" should also return class with id_wc = 1. Not working in System 2. Problem with profile editing and searching To tell in one sentence, I am facing a conflict between the ease of profile edition (edition of tag relations when tutor profiles are edited) and the ease of search logic. In the beginning, we had one table structure and search was easy but tag edition logic was very clumsy and unmaintainable(Check System 1 in the section below) . So we created separate tag relations tables to make profile edition simpler but search has become difficult. Please dump the tables so that you can run the search query I have given below and see the results. System 1 (previous system - search easy - profile edition difficult):- Only one table called All_Tag_Relations table had the all the tag relations. The tags table below is common to both systems 1 and 2. CREATE TABLE IF NOT EXISTS `all_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, `id_wc` int(10) unsigned DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `All_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_wc` (`id_wc`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `all_tag_relations` (`id_tag_rel`, `id_tag`, `id_tutor`, `id_wc`) VALUES (1, 1, 1, NULL), (2, 2, 1, NULL), (3, 1, 1, 1), (4, 2, 1, 1), (5, 3, 1, 1), (6, 4, 1, 1), (7, 6, 2, NULL), (8, 7, 2, NULL), (9, 6, 2, 2), (10, 7, 2, 2), (11, 5, 2, 2), (12, 4, 2, 2); CREATE TABLE IF NOT EXISTS `tags` ( `id_tag` int(10) unsigned NOT NULL AUTO_INCREMENT, `tag` varchar(255) DEFAULT NULL, PRIMARY KEY (`id_tag`), UNIQUE KEY `tag` (`tag`), KEY `id_tag` (`id_tag`), KEY `tag_2` (`tag`), KEY `tag_3` (`tag`), KEY `tag_4` (`tag`), FULLTEXT KEY `tag_5` (`tag`) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 AUTO_INCREMENT=8 ; INSERT INTO `tags` (`id_tag`, `tag`) VALUES (1, 'Sandeepan'), (2, 'Nath'), (3, 'first'), (4, 'class'), (5, 'new'), (6, 'Bob'), (7, 'Cratchit'); Please note that for every class, the tag rels of its tutor have to be duplicated. Example, for class with id_wc=1, the tag rel records with id_tag_rel = 3 and 4 are actually extras if you compare with the tag rel records with id_tag_rel = 1 and 2. System 2 (present system - profile edition easy, search difficult) Two separate tables Tutors_Tag_Relations and Webclasses_Tag_Relations have the corresponding tag relations data (Please dump into a separate database)- CREATE TABLE IF NOT EXISTS `tutors_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `All_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `tutors_tag_relations` (`id_tag_rel`, `id_tag`, `id_tutor`) VALUES (1, 1, 1), (2, 2, 1), (3, 6, 2), (4, 7, 2); CREATE TABLE IF NOT EXISTS `webclasses_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, `id_wc` int(10) DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `webclasses_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_wc` (`id_wc`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `webclasses_tag_relations` (`id_tag_rel`, `id_tag`, `id_tutor`, `id_wc`) VALUES (1, 3, 1, 1), (2, 4, 1, 1), (3, 5, 2, 2), (4, 4, 2, 2); CREATE TABLE IF NOT EXISTS `tags` ( `id_tag` int(10) unsigned NOT NULL AUTO_INCREMENT, `tag` varchar(255) DEFAULT NULL, PRIMARY KEY (`id_tag`), UNIQUE KEY `tag` (`tag`), KEY `id_tag` (`id_tag`), KEY `tag_2` (`tag`), KEY `tag_3` (`tag`), KEY `tag_4` (`tag`), FULLTEXT KEY `tag_5` (`tag`) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 AUTO_INCREMENT=8 ; INSERT INTO `tags` (`id_tag`, `tag`) VALUES (1, 'Sandeepan'), (2, 'Nath'), (3, 'first'), (4, 'class'), (5, 'new'), (6, 'Bob'), (7, 'Cratchit'); CREATE TABLE IF NOT EXISTS `all_tag_relations` ( `id_tag_rel` int(10) NOT NULL AUTO_INCREMENT, `id_tag` int(10) unsigned NOT NULL DEFAULT '0', `id_tutor` int(10) DEFAULT NULL, `id_wc` int(10) unsigned DEFAULT NULL, PRIMARY KEY (`id_tag_rel`), KEY `All_Tag_Relations_FKIndex1` (`id_tag`), KEY `id_wc` (`id_wc`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; insert into All_Tag_Relations select NULL,id_tag,id_tutor,NULL from Tutors_Tag_Relations; insert into All_Tag_Relations select NULL,id_tag,id_tutor,id_wc from Webclasses_Tag_Relations; Here you can see how easily tutor first name can be edited only in one place. But search has become really difficult, so on being advised to use a Temporary table, I am creating one at every search request, then dumping all the necessary data and then searching from it, I am creating this All_Tag_Relations table at search run time. Here I am just dumping all the data from the two tables Tutors_Tag_Relations and Webclasses_Tag_Relations. But, I am still not able to get classes if I search with tutor name This is the query which searches "first class". Running them on both the systems shows correct results (returns the class with id_wc = 1). SELECT wtagrels.id_wc,SUM(DISTINCT( wtagrels.id_tag =3)) AS key_1_total_matches, SUM(DISTINCT( wtagrels.id_tag =4)) AS key_2_total_matches FROM all_tag_relations AS wtagrels WHERE ( wtagrels.id_tag =3 OR wtagrels.id_tag =4 ) GROUP BY wtagrels.id_wc HAVING key_1_total_matches = 1 AND key_2_total_matches = 1 LIMIT 0, 20 But, searching for "Sandeepan class" works only with the 1st system Here is the query which searches "Sandeepan class" SELECT wtagrels.id_wc,SUM(DISTINCT( wtagrels.id_tag =1)) AS key_1_total_matches, SUM(DISTINCT( wtagrels.id_tag =4)) AS key_2_total_matches FROM all_tag_relations AS wtagrels WHERE ( wtagrels.id_tag =1 OR wtagrels.id_tag =4 ) GROUP BY wtagrels.id_wc HAVING key_1_total_matches = 1 AND key_2_total_matches = 1 LIMIT 0, 20 Can anybody alter this query and somehow do a proper join or something to get correct results. That solves my problem in a nice way. As you can figure out, the reason why it does not work in system 2 is that in system 1, for every class, one additional tag relation linking class and tutor name is present. e.g. for class first class, (records with id_tag_rel 3 and 4) which returns the class on searching with tutor name. So, you see the trade-off between the search and profile edition difficulty with the two systems. How do I overcome both. I have to reach a conclusion soon. So far my reasoning is it is definitely not good from a code maintainability point of view to follow the single tag rel table structure of system one, because in a real system while editing a field like "tutor qualifications", there can be as many records in tag rels table as there are words in qualification of a tutor (one word in a field = one tag relation). Now suppose a tutor has 100 classes. When he edits his qualification, all the tag rel rows corresponding to him are deleted and then as many copies are to be created (as per the new qualification data) as there are classes. This becomes particularly difficult if later more searcheable fields are added. The code cannot be robust. Is the best solution to follow system 2 (edition has to be in one table - no extra work for each and every class) and somehow re-create the all_tag_relations table like system 1 (from the tables tutor_tag_relations and webclasses_tag_relations), creating the extra tutor tag rels for each and every class by a tutor (which is currently missing in system 2's temporary all_tag_relations table). That would be a time consuming logic script. I doubt that table can be recreated without resorting to PHP sript (mysql alone cannot do that). But the problem is that running all this at search time will make search definitely slow. So, how do such systems work? How are such situations handled? I thought about we can run a cron which initiates that PHP script, say every 1 minute and replaces the existing all_tag_relations table as per new tag rels from tutor_tag_relations and webclasses_tag_relations (replaces means creates a new table, deletes the original and renames the new one as all_tag_relations, otherwise search won't work during that period- or is there any better way to that?). Anyway, the result would be that any changes by tutors will reflect in search in the next 1 minute and not immediately. An alternateve would be to initate that PHP script every time a tutor edits his profile. But here again, since many users may edit their profiles concurrently, will the creation of so many tables be a burden and can mysql make the server slow? Any help would be appreciated and working solution will be accepted as answer. Thanks, Sandeepan

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  • Tutorial: Getting Started with the NoSQL JavaScript / Node.js API for MySQL Cluster

    - by Mat Keep
    Tutorial authored by Craig Russell and JD Duncan  The MySQL Cluster team are working on a new NoSQL JavaScript connector for MySQL. The objectives are simplicity and high performance for JavaScript users: - allows end-to-end JavaScript development, from the browser to the server and now to the world's most popular open source database - native "NoSQL" access to the storage layer without going first through SQL transformations and parsing. Node.js is a complete web platform built around JavaScript designed to deliver millions of client connections on commodity hardware. With the MySQL NoSQL Connector for JavaScript, Node.js users can easily add data access and persistence to their web, cloud, social and mobile applications. While the initial implementation is designed to plug and play with Node.js, the actual implementation doesn't depend heavily on Node, potentially enabling wider platform support in the future. Implementation The architecture and user interface of this connector are very different from other MySQL connectors in a major way: it is an asynchronous interface that follows the event model built into Node.js. To make it as easy as possible, we decided to use a domain object model to store the data. This allows for users to query data from the database and have a fully-instantiated object to work with, instead of having to deal with rows and columns of the database. The domain object model can have any user behavior that is desired, with the NoSQL connector providing the data from the database. To make it as fast as possible, we use a direct connection from the user's address space to the database. This approach means that no SQL (pun intended) is needed to get to the data, and no SQL server is between the user and the data. The connector is being developed to be extensible to multiple underlying database technologies, including direct, native access to both the MySQL Cluster "ndb" and InnoDB storage engines. The connector integrates the MySQL Cluster native API library directly within the Node.js platform itself, enabling developers to seamlessly couple their high performance, distributed applications with a high performance, distributed, persistence layer delivering 99.999% availability. The following sections take you through how to connect to MySQL, query the data and how to get started. Connecting to the database A Session is the main user access path to the database. You can get a Session object directly from the connector using the openSession function: var nosql = require("mysql-js"); var dbProperties = {     "implementation" : "ndb",     "database" : "test" }; nosql.openSession(dbProperties, null, onSession); The openSession function calls back into the application upon creating a Session. The Session is then used to create, delete, update, and read objects. Reading data The Session can read data from the database in a number of ways. If you simply want the data from the database, you provide a table name and the key of the row that you want. For example, consider this schema: create table employee (   id int not null primary key,   name varchar(32),   salary float ) ENGINE=ndbcluster; Since the primary key is a number, you can provide the key as a number to the find function. function onSession = function(err, session) {   if (err) {     console.log(err);     ... error handling   }   session.find('employee', 0, onData); }; function onData = function(err, data) {   if (err) {     console.log(err);     ... error handling   }   console.log('Found: ', JSON.stringify(data));   ... use data in application }; If you want to have the data stored in your own domain model, you tell the connector which table your domain model uses, by specifying an annotation, and pass your domain model to the find function. var annotations = new nosql.Annotations(); function Employee = function(id, name, salary) {   this.id = id;   this.name = name;   this.salary = salary;   this.giveRaise = function(percent) {     this.salary *= percent;   } }; annotations.mapClass(Employee, {'table' : 'employee'}); function onSession = function(err, session) {   if (err) {     console.log(err);     ... error handling   }   session.find(Employee, 0, onData); }; Updating data You can update the emp instance in memory, but to make the raise persistent, you need to write it back to the database, using the update function. function onData = function(err, emp) {   if (err) {     console.log(err);     ... error handling   }   console.log('Found: ', JSON.stringify(emp));   emp.giveRaise(0.12); // gee, thanks!   session.update(emp); // oops, session is out of scope here }; Using JavaScript can be tricky because it does not have the concept of block scope for variables. You can create a closure to handle these variables, or use a feature of the connector to remember your variables. The connector api takes a fixed number of parameters and returns a fixed number of result parameters to the callback function. But the connector will keep track of variables for you and return them to the callback. So in the above example, change the onSession function to remember the session variable, and you can refer to it in the onData function: function onSession = function(err, session) {   if (err) {     console.log(err);     ... error handling   }   session.find(Employee, 0, onData, session); }; function onData = function(err, emp, session) {   if (err) {     console.log(err);     ... error handling   }   console.log('Found: ', JSON.stringify(emp));   emp.giveRaise(0.12); // gee, thanks!   session.update(emp, onUpdate); // session is now in scope }; function onUpdate = function(err, emp) {   if (err) {     console.log(err);     ... error handling   } Inserting data Inserting data requires a mapped JavaScript user function (constructor) and a session. Create a variable and persist it: function onSession = function(err, session) {   var data = new Employee(999, 'Mat Keep', 20000000);   session.persist(data, onInsert);   } }; Deleting data To remove data from the database, use the session remove function. You use an instance of the domain object to identify the row you want to remove. Only the key field is relevant. function onSession = function(err, session) {   var key = new Employee(999);   session.remove(Employee, onDelete);   } }; More extensive queries We are working on the implementation of more extensive queries along the lines of the criteria query api. Stay tuned. How to evaluate The MySQL Connector for JavaScript is available for download from labs.mysql.com. Select the build: MySQL-Cluster-NoSQL-Connector-for-Node-js You can also clone the project on GitHub Since it is still early in development, feedback is especially valuable (so don't hesitate to leave comments on this blog, or head to the MySQL Cluster forum). Try it out and see how easy (and fast) it is to integrate MySQL Cluster into your Node.js platforms. You can learn more about other previewed functionality of MySQL Cluster 7.3 here

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  • I thought the new AUTO_SAMPLE_SIZE in Oracle Database 11g looked at all the rows in a table so why do I see a very small sample size on some tables?

    - by Maria Colgan
    I recently got asked this question and thought it was worth a quick blog post to explain in a little more detail what is going on with the new AUTO_SAMPLE_SIZE in Oracle Database 11g and what you should expect to see in the dictionary views. Let’s take the SH.CUSTOMERS table as an example.  There are 55,500 rows in the SH.CUSTOMERS tables. If we gather statistics on the SH.CUSTOMERS using the new AUTO_SAMPLE_SIZE but without collecting histogram we can check what sample size was used by looking in the USER_TABLES and USER_TAB_COL_STATISTICS dictionary views. The sample sized shown in the USER_TABLES is 55,500 rows or the entire table as expected. In USER_TAB_COL_STATISTICS most columns show 55,500 rows as the sample size except for four columns (CUST_SRC_ID, CUST_EFF_TO, CUST_MARTIAL_STATUS, CUST_INCOME_LEVEL ). The CUST_SRC_ID and CUST_EFF_TO columns have no sample size listed because there are only NULL values in these columns and the statistics gathering procedure skips NULL values. The CUST_MARTIAL_STATUS (38,072) and the CUST_INCOME_LEVEL (55,459) columns show less than 55,500 rows as their sample size because of the presence of NULL values in these columns. In the SH.CUSTOMERS table 17,428 rows have a NULL as the value for CUST_MARTIAL_STATUS column (17428+38072 = 55500), while 41 rows have a NULL values for the CUST_INCOME_LEVEL column (41+55459 = 55500). So we can confirm that the new AUTO_SAMPLE_SIZE algorithm will use all non-NULL values when gathering basic table and column level statistics. Now we have clear understanding of what sample size to expect lets include histogram creation as part of the statistics gathering. Again we can look in the USER_TABLES and USER_TAB_COL_STATISTICS dictionary views to find the sample size used. The sample size seen in USER_TABLES is 55,500 rows but if we look at the column statistics we see that it is same as in previous case except  for columns  CUST_POSTAL_CODE and  CUST_CITY_ID. You will also notice that these columns now have histograms created on them. The sample size shown for these columns is not the sample size used to gather the basic column statistics. AUTO_SAMPLE_SIZE still uses all the rows in the table - the NULL rows to gather the basic column statistics (55,500 rows in this case). The size shown is the sample size used to create the histogram on the column. When we create a histogram we try to build it on a sample that has approximately 5,500 non-null values for the column.  Typically all of the histograms required for a table are built from the same sample. In our example the histograms created on CUST_POSTAL_CODE and the CUST_CITY_ID were built on a single sample of ~5,500 (5,450 rows) as these columns contained only non-null values. However, if one or more of the columns that requires a histogram has null values then the sample size maybe increased in order to achieve a sample of 5,500 non-null values for those columns. n addition, if the difference between the number of nulls in the columns varies greatly, we may create multiple samples, one for the columns that have a low number of null values and one for the columns with a high number of null values.  This scheme enables us to get close to 5,500 non-null values for each column. +Maria Colgan

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  • SPARC T4-2 Produces World Record Oracle Essbase Aggregate Storage Benchmark Result

    - by Brian
    Significance of Results Oracle's SPARC T4-2 server configured with a Sun Storage F5100 Flash Array and running Oracle Solaris 10 with Oracle Database 11g has achieved exceptional performance for the Oracle Essbase Aggregate Storage Option benchmark. The benchmark has upwards of 1 billion records, 15 dimensions and millions of members. Oracle Essbase is a multi-dimensional online analytical processing (OLAP) server and is well-suited to work well with SPARC T4 servers. The SPARC T4-2 server (2 cpus) running Oracle Essbase 11.1.2.2.100 outperformed the previous published results on Oracle's SPARC Enterprise M5000 server (4 cpus) with Oracle Essbase 11.1.1.3 on Oracle Solaris 10 by 80%, 32% and 2x performance improvement on Data Loading, Default Aggregation and Usage Based Aggregation, respectively. The SPARC T4-2 server with Sun Storage F5100 Flash Array and Oracle Essbase running on Oracle Solaris 10 achieves sub-second query response times for 20,000 users in a 15 dimension database. The SPARC T4-2 server configured with Oracle Essbase was able to aggregate and store values in the database for a 15 dimension cube in 398 minutes with 16 threads and in 484 minutes with 8 threads. The Sun Storage F5100 Flash Array provides more than a 20% improvement out-of-the-box compared to a mid-size fiber channel disk array for default aggregation and user-based aggregation. The Sun Storage F5100 Flash Array with Oracle Essbase provides the best combination for large Oracle Essbase databases leveraging Oracle Solaris ZFS and taking advantage of high bandwidth for faster load and aggregation. Oracle Fusion Middleware provides a family of complete, integrated, hot pluggable and best-of-breed products known for enabling enterprise customers to create and run agile and intelligent business applications. Oracle Essbase's performance demonstrates why so many customers rely on Oracle Fusion Middleware as their foundation for innovation. Performance Landscape System Data Size(millions of items) Database Load(minutes) Default Aggregation(minutes) Usage Based Aggregation(minutes) SPARC T4-2, 2 x SPARC T4 2.85 GHz 1000 149 398* 55 Sun M5000, 4 x SPARC64 VII 2.53 GHz 1000 269 526 115 Sun M5000, 4 x SPARC64 VII 2.4 GHz 400 120 448 18 * – 398 mins with CALCPARALLEL set to 16; 484 mins with CALCPARALLEL threads set to 8 Configuration Summary Hardware Configuration: 1 x SPARC T4-2 2 x 2.85 GHz SPARC T4 processors 128 GB memory 2 x 300 GB 10000 RPM SAS internal disks Storage Configuration: 1 x Sun Storage F5100 Flash Array 40 x 24 GB flash modules SAS HBA with 2 SAS channels Data Storage Scheme Striped - RAID 0 Oracle Solaris ZFS Software Configuration: Oracle Solaris 10 8/11 Installer V 11.1.2.2.100 Oracle Essbase Client v 11.1.2.2.100 Oracle Essbase v 11.1.2.2.100 Oracle Essbase Administration services 64-bit Oracle Database 11g Release 2 (11.2.0.3) HP's Mercury Interactive QuickTest Professional 9.5.0 Benchmark Description The objective of the Oracle Essbase Aggregate Storage Option benchmark is to showcase the ability of Oracle Essbase to scale in terms of user population and data volume for large enterprise deployments. Typical administrative and end-user operations for OLAP applications were simulated to produce benchmark results. The benchmark test results include: Database Load: Time elapsed to build a database including outline and data load. Default Aggregation: Time elapsed to build aggregation. User Based Aggregation: Time elapsed of the aggregate views proposed as a result of tracked retrieval queries. Summary of the data used for this benchmark: 40 flat files, each of size 1.2 GB, 49.4 GB in total 10 million rows per file, 1 billion rows total 28 columns of data per row Database outline has 15 dimensions (five of them are attribute dimensions) Customer dimension has 13.3 million members 3 rule files Key Points and Best Practices The Sun Storage F5100 Flash Array has been used to accelerate the application performance. Setting data load threads (DLTHREADSPREPARE) to 64 and Load Buffer to 6 improved dataloading by about 9%. Factors influencing aggregation materialization performance are "Aggregate Storage Cache" and "Number of Threads" (CALCPARALLEL) for parallel view materialization. The optimal values for this workload on the SPARC T4-2 server were: Aggregate Storage Cache: 32 GB CALCPARALLEL: 16   See Also Oracle Essbase Aggregate Storage Option Benchmark on Oracle's SPARC T4-2 Server oracle.com Oracle Essbase oracle.com OTN SPARC T4-2 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 28 August 2012.

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  • Evaluating Oracle Data Mining Has Never Been Easier - Evaluation "Kit" Available

    - by chberger
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Now you can quickly and easily get set up to starting using Oracle Data Mining for evaluation purposes. Just go to the Oracle Technology Network (OTN) and follow these simple steps. Oracle Data Mining Evaluation "Kit" Instructions Step 1: Download and Install the Oracle Database 11g Release 2 Anyone can download and install the Oracle Database for free for evaluation purposes. Read OTN web site for details. 11.2.0.1.0 DB is the minimum, 11.2.0.2 is better and naturally 11.2.0.3 is best if you are a current customer and on active support. Either 32-bit or 64-bit is fine. 4GB of RAM or more works fine for SQL Developer and the Oracle Data Miner GUI extension. Downloading the database and installing it should take just about an hour or so, depending on your network and computer. For more instructions on setting up Oracle Data Mining see: http://www.oracle.com/technetwork/database/options/odm/dataminerworkflow-168677.html When you install the Oracle Database, the Sample Examples data should also be installed e.g.:Release 2 Examples win32_11gR2_examples.zip (565,154,740 bytes). Contains examples of how to use the Oracle Database. Download if you are new to Oracle and want to try some of the examples presented in the Documentation Step 2: Install SQL Developer 3.1 (the Oracle Data Mining Extension installs automatically) Step 3. Follow the four free step-by-step Oracle-by-Examples e-training lessons: Setting Up Oracle Data Miner 11g Release 2 This tutorial covers the process of setting up Oracle Data Miner 11g Release 2 for use within Oracle SQL Developer 3.0. Using Oracle Data Miner 11g Release 2 This tutorial covers the use of Oracle Data Miner to perform data mining against Oracle Database 11g Release 2. In this lesson, you examine and solve a data mining business problem by using the Oracle Data Miner graphical user interface (GUI). Star Schema Mining Using Oracle Data Miner This tutorial covers the use of Oracle Data Miner to perform star schema mining against Oracle Database 11g Release 2. Text Mining Using Oracle Data Miner This tutorial covers the use of Oracle Data Miner to perform text mining against Oracle Database 11g Release 2. That’s it! Easy, fun and the fastest way to get started evaluating Oracle Data Mining. Enjoy! Charlie

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  • SQL Azure: Notes on Building a Shard Technology

    - by Herve Roggero
    In Chapter 10 of the book on SQL Azure (http://www.apress.com/book/view/9781430229612) I am co-authoring, I am digging deeper in what it takes to write a Shard. It's actually a pretty cool exercise, and I wanted to share some thoughts on how I am designing the technology. A Shard is a technology that spreads the load of database requests over multiple databases, as transparently as possible. The type of shard I am building is called a Vertical Partition Shard  (VPS). A VPS is a mechanism by which the data is stored in one or more databases behind the scenes, but your code has no idea at design time which data is in which database. It's like having a mini cloud for records instead of services. Imagine you have three SQL Azure databases that have the same schema (DB1, DB2 and DB3), you would like to issue a SELECT * FROM Users on all three databases, concatenate the results into a single resultset, and order by last name. Imagine you want to ensure your code doesn't need to change if you add a new database to the shard (DB4). Now imagine that you want to make sure all three databases are queried at the same time, in a multi-threaded manner so your code doesn't have to wait for three database calls sequentially. Then, imagine you would like to obtain a breadcrumb (in the form of a new, virtual column) that gives you a hint as to which database a record came from, so that you could update it if needed. Now imagine all that is done through the standard SqlClient library... and you have the Shard I am currently building. Here are some lessons learned and techniques I am using with this shard: Parellel Processing: Querying databases in parallel is not too hard using the Task Parallel Library; all you need is to lock your resources when needed Deleting/Updating Data: That's not too bad either as long as you have a breadcrumb. However it becomes more difficult if you need to update a single record and you don't know in which database it is. Inserting Data: I am using a round-robin approach in which each new insert request is directed to the next database in the shard. Not sure how to deal with Bulk Loads just yet... Shard Databases:  I use a static collection of SqlConnection objects which needs to be loaded once; from there on all the Shard commands use this collection Extension Methods: In order to make it look like the Shard commands are part of the SqlClient class I use extension methods. For example I added ExecuteShardQuery and ExecuteShardNonQuery methods to SqlClient. Exceptions: Capturing exceptions in a multi-threaded code is interesting... but I kept it simple for now. I am using the ConcurrentQueue to store my exceptions. Database GUID: Every database in the shard is given a GUID, which is calculated based on the connection string's values. DataTable. The Shard methods return a DataTable object which can be bound to objects.  I will be sharing the code soon as an open-source project in CodePlex. Please stay tuned on twitter to know when it will be available (@hroggero). Or check www.bluesyntax.net for updates on the shard. Thanks!

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