Database

Databases grow over time, and sometimes it’s necessary to add disk space to a server to accommodate that growth. Fortunately, moving your database is a fairly simple process. The following is tested on Ubuntu 12.04LTS, but, by locating directories and files, it should work on other flavors of Linux.

The first step is to stop any incoming data to your database. This might involve editing the crontab to stop scheduled processes that touch your database or stopping programs that are inserting or modifying data, such as a web server or Syslog software. This is the trickiest part, and will probably be the most time-consuming part of the process.

It’s time to fix some common errors in your blog. In this blog post, we are going to discuss common structured data errors. You can use Google webmaster tools to detect them. Google already added Structured Data in blogger templates but there’s a common error in Structured Data markup like missing the required field, not part of the schema, etc… This common error affects your search appearance and affects your site crawling. This format has a common problem such as missing required field updated. This affects search appearance. To correct these errors, I’m sharing this article with you. Many people’s use Google webmaster structured data testing tool for determining the structure of the web page. While using this tool many people’s get an error regarding their structure page Contains Property “image_url” Which Is Not Part of The Schema Error can be easily fixed

Recently we faced a situation where the server hosting our Analysis Services ran out of the space on the primary C drive. After looking at the files stored on C drive, we noticed that the Data folder of Analysis service %Installation folder%\OLAP\Data was occupying max disk space. This is because by default when you deploy the Analysis Service Project, the cube data (dimensions and Facts data) is stored in the above default directory.

We as database developers, many times have to export data into csv files and send them across to the Business users. The data the needs to be exported can be a retrieved by executing an adhoc-query or a stored procedure based on the users requirements. In this article we will look at a SQL CLR Stored procedure which can be used to export data into CSV from within the Database

Many times when we normalize our database, we end up storing multi-values attributes as separate rows in table. For eg. Consider we are storing Photos and a set of tags associated with the photos.

Assume the following table structure

Photo_ID   Tag
  1	   Beach
  1	   Sand
  2	   Mountain
  2	   Waterfall
  3	   Island
  3	   White Sand
  3	   Blue waters

Now while retrieving the tags for photos we need only one record per photo with all the tags as comma separated in the output.