I’m happy to announce that I’ll be presenting at SQLSaturday #275 in Copenhagen on March 29th!
In this post I want to walk through a number of SQL Server corruption recovery techniques for when you’re out of luck, have no backups, and the usual methods don’t work. I’ll be using the AdventureWorksLT2008R2 sample database as my victim.
Sometimes you must first do evil, to do good. Such is the case when you want to hone your skills in corruption recovery of SQL Server databases.
When I initially started working on OrcaMDF I had just one goal, to gain a deeper knowledge of MDF file internals than I could through most books available.
At the moment I’m working on extending OrcaMDF Studio to not only list base tables, DMVs and tables, but also stored procedures. That’s easy enough, we just need to query sys.procedures – or that is, the sys.sysschobjs base table, since the sys.procedures DMV isn’t available when SQL Server isn’t running.
I’m really lagging behind on my blogging – life is busy as the moment! Just a couple of weeks ago I presented my Revealing the Magic session at the Norwegian Developers Conference in Oslo. I was quite excited to give my SQL Server oriented session to a crowd of developers – a 500 level session, at SQL Server events that is.
After two months of on and off work, I finally merged the OrcaMDF compression branch into master. This means OrcaMDF now officially supports data row compression!
In this post I’ll do a deep dive into how vardecimals are stored on disk. For a general introduction to what they are and how/when to use them, see this post.
Since I released OrcaMDF Studio, I’ve gotten aware of some base table differences between SQL Server 2008 and 2005. These differences causes OrcaMDF to fail since it’s coded against 2008 R2 and expect that format.
Just about two and a half months have passed since I last posted an OrcaMDF feature recap. Since then I’ve been busy attending three of the top SQL Server conferences – SQLBits, PASS and SQL Rally. It’s been excellent chatting about OrcaMDF and getting some feedback on where to take it, thanks to all of you!
I’m sitting here on the train in Denmark, on the final leg home from SQLRally Nordic. During my presentation based on my OrcaMDF work, I implicitly announced that OrcaMDF now exposes metadata – thougt I might as well share here as well. Other than expanding the core engine support in OrcaMDF, one of the main features I’ve wanted to implement was a way for OrcaMDF to expose metadata about your database. How do you list the tables, indexes, columns, etc. from your database?
One of the latest features I’ve added to OrcaMDF is support of databases with multiple data files. This required relatively little parsing changes, actually it was mostly bug fixing code that wasn’t hit previously, due to only working with single file databases. It did however require some major refactoring to move away from MdfFile being the primary entrypoint, to now using the Database class, encapsulating a variable number of DataFiles.
Time flies – it’s been about four months since I originally introduced my pet project, OrcaMDF. Since then, quite a lot has happened and OrcaMDF is somewhat more capable than when it started out. As a result I thought I’d provide a recap of what OrcaMDF is currently capable of, as well as what my plans are for the future.
As I continue to add new features & support for new data structures in OrcaMDF, the risk of regressions increase. Especially so as I’m developing in a largely unknown field, given that I can’t plan for structures and relations that I do not yet know about. To reduce the risk of regressions, testing is an obvious need.
Bits are stored very differently from other fixed length data types in SQL Server. Usually all fixed length columns will be present, one after the other, in the fixed data part of a record. As the smallest unit of data we can write to disk is a byte, the naïve approach to storing bits would be to use a whole bit for each bit. It would be very simple to parse as it would follow the usual scheme, but it would also waste quite some space.
There are several different date related data types in SQL Server. Currently OrcaMDF supports the three most common types: date, datetime & smalldatetime.
Implementing parsing support for SQL Server data types in OrcaMDF is a simple matter of implementing the ISqlType interface:
I’ve been spamming Twitter the last couple of days with progress on my pet project, OrcaMDF. But what is OrcaMDF really?
Miracle Open World 2011
I was invited to speak at MOW2011 for the SQL Server track. Last year I got good reviews for my presentation on Dissecting PDF Documents, a deep dive into the file format of PDF files. Wanting to stay in the same grove, I decided to take a look at the MDF format as it’s somewhat closer to SQL Server DBA’s than PDF files. Having almost worn my SQL Server 2008 Internals book down from reading, I’ve always been interested in the internals, though I still felt like I was lacking a lot of knowledge.
A parser is born
For my demos at MOW I wanted to at least read the records from a data page, just like the output from DBCC Page. The basic page format is well documented, and it’s not the first time I’ve taken a deeper look at pages. Surprisingly quickly, I had record parsing from data pages functioning using a hardcoded schema. Parsing a single page is fun, but really, I’d like to get all the data from a table. Restricting myself to just consider clustered tables made it simpler as it’d just be a matter of following the linked list of pages from start to end. However, that meant I’d have to parse the header as well. There’s some good information out there on the anatomy of pages, but everything I could find had a distinct lack of information on the actual header structure and field types.