On August 10th 2010 I attended and presented at the PGH.NET User Group meeting named “5 Guys with Code.”  According to one of the PGH.NET leaders tweet it looks like the headcount was 60+

The following are some thoughts and highlights from the presentations.

Presentations

•  
  • John Sterrett (Blog | Twitter) – Table Value Parameters with SQL Server 2008 and Microsoft .NET  
  •  
    • Download sample code and presentation here.
    • Download SQL Server 2008 R2 Developer Toolkit
    • Download SQL Server 2008 Developer Toolkit here
    • Table Value Parameter links

I presented a feature that is included in SQL Server 2008 and underused by many developers.  This presentation shows developers how to pass a  DataTable, DataReaders and Lists to SQL Server database objects with only two extra lines of C# or VB.NET code. 

As promised below are some reference links

• David Hoerster (Blog | Twitter) – jQuery Code Snippets in Visual Studio 2010

Time is money and David’s fifteen minute tip might just save you a lot of time and money.    He covered several tools that will help you generate some awesome JavaScript. 

I  really liked the jsFiddle.NET tool.  It looks like a great tool to mockup some a user interface (more on user interfaces later).

• Rich Dudley (Blog  | Twitter ) – A Quick Look at the New SQL CE Engine

Being addicted to databases I very happy to see that I wasn’t the only one presenting a topic based on databases.  Rich did a great job explaining what SQL CE can do and what it cannot do. 

Rich blogged about his experience (post includes photos, slides and more)

• John Hidey (Blog | Twitter) – Layout Controls for XAML

I have to admit that XAML and I don’t get along well.  We had a fling a few years ago.  XAML cheated on me and I haven’t been the same since.

Ok seriously, I tried XAML a few times and found it very hard to understand.  John did a great job going over the common things that are hard to understand when you get started with XAML.   John started with some very basic controls and then built a final example that included all the basic controls.

• Eric Kepes (Blog | Twitter) – Bowling for TDD

At this summers PGH.NET Code Camp we had a speakers session where one of the presenters said, “Code is considered legacy code when TDD is not applied.”  Eric bowling for TDD example showed how anyone can start developing TDD.

I cannot speak for the whole legal industry but where I work a lot of people love some SharePoint.  It’s like 50 Cent says, “We love SharePoint like a fat kid loves cake.”  And trust me we love some cake.  With this mad love of SharePoint comes great collaboration and with this great collaboration comes tons of binary files stored in a database.  What does this mean to the DBA? SharePoint now consists of VLDB’s. 

Hmm… How do we move the VLDB’s across the USA and keep them in sync?

With the built in features of Log Shipping, database Mirroring, Transactional Replication with SQL Server I knew it was possible to migrate the databases and keep them in-sync.   At the time I wasn’t exactly sure of the best way to do this so I used the bat phone.

While some people love SharePoint I love Twitter. Twitter allows me to communicate with several great DBA’s.  For example, I used #sqlhelp which is the equivalent of getting Batman on the bat phone.  This time it was Brent Ozar ( Twitter | Blog) who confirmed my gut feeling that Log Shipping was the way to go.

So…. How do you do it?

The complete process I used is documented at mssqltips #2073.  This tip walks you though the process of 22 steps to get the job done.  I hope this tip helps out other DBA’s that need to migrate VLDB’s from one location to another location without using third party tools.

If you have any comments or suggestions please forward them along.

Today using profiler to trace database calls from third-party applications was published on www.mssqltips.com.  Hopefully, this tip will help some people understand why profiler is bacon.  In this example I trace two queries with Management Studio.  Speaking of Management Studio, have you ever wondered what queries are executed by your favorite features of Management Studio?  You can follow the steps in this tip to do that too.

This is my fist tip published at www.mssqltips.com.  I look forward to publishing tips on a monthly basis.

Today, I am jumping into Adam Machanic T-SQL Tuesday challenge with the following post.

Recently, I created a build request to have a new server to move SQL Server databases.  I put together an estimate for the space needed for data, logs and backups and included this information in the build document.  This request was put in the queue and all was well.  Once this request popped to the top of the queue I reviewed the size of database files using Idera’s Space Analyzer and noticed unexpected data growth in a few of the data files.  Thankfully, the data collector and Management Data Warehouse (MDW) was enabled which helped us track the unexpected data growth.

Introduction

SQL Server 2008 introduces the data collector and the management data warehouse (MDW) into SQL Server Management Studio (SSMS). The Management Data Warehouse exists by leveraging the data collector and a MDW database and custom reports. This allows administrators and developers the opportunity to do some proactive monitoring. If you are familiar with the Performance Dashboard then you will be impressed with the new Management Data Warehouse.

How does the data collector help you?

Out of the box, the data collector provides you with the tools to monitor disk usage, server activity and query statistics.  Therefore, when you are asked the following questions.  How much space do we need for database xyz? Why did database xyz grow from size 123 to size 456? you can use the data collector report to help answer these questions.  For example, below is a screen shot of some sample databases.

You can see that the third, forth and fifth databases had their current size changed.  I want to focus on this fact because it doesn’t represent the data inside the database files.  This means the actual data files (mdf, ndf, ldf) are growing which can cause disk fragmentation. You want to avoid this when possible.  Ideally, you want your database graph to be a straight line like the sixth database.  Next we will click on the graph for the fourth database and drill deeper to the analysis.

Looking at the two image above you can see that the data size multiplied during a six hour between noon and 6pm on November 30th.  We were then able to use this information to determine the cause for the unexpected growth of data.

Conclusion

I think this is a great tool to troubleshoot unexpected data growth.  I look forward to using this tool as part of the process to estimate future database growth.

A few days ago I wrote a post that gave an introduction to dimensions.  Today, we are going to continue covering the basic concepts included in dimensional modeling by covering an introduction to fact tables and measures.  These posts are all part of the introduction to building a data warehouse with sql server series.

What is a Fact Table?

A fact table is a table that joins dimension tables with measures.  For example, Lets say you wanted to know the time worked by employees, by location, by project and by task.  If you had a dimension for employees, location, project and task you would create a composite primary key using these foreign keys and add an additional column for the time worked measure. (more on measures in a little bit)

Keep in mind that fact tables are huge unlike dimension tables.  Fact tables are usually built to contain a hundred thousand records on the low side up to billions of records on the high side.  Therefore, these tables must be normalized to be efficient.

A fact table is normalized when it consists of the following two things:

1. 1. A composite primary key using the foreign keys to the dimension tables.
   2. Measure(s) used for numerical analysis.

What is a measure?

A measure is normally an additive numerical value that represents a business metric.  You are also not limited to a single measure.  You can have multiple measures within a fact table.  For example, if your fact table is used to track purchases internationally you might have measures for each type of currency.  If you are building a fact table for the retail industry you might also have the following measures cost, list price, average sale price.

Next we will conclude or session on dimensional modeling and start to build our first cube.

Today, we are going to quickly cover one of the basic concepts included in dimensional modeling.  We are going over the basics of dimensions, attributes and hierarchies.  We will review how they are related and how they work within Data Warehouses.  If you are looking for an introduction to building a data warehouse click here.

What is a Dimension Table?

A dimension table provides the description behind the analytic numbers.  It describes the who, what, when, where and why behind the facts. Dimensions are normally broken down into groups (tables) and they contain several attributes (columns).   Unlike a fact table the dimension table is not normalized.  Generally, dimension tables have many columns but a limited amount of rows. Dimension tables normally provide two purposes in a data warehouse, it can be used to filter queries and to select data.

Several data warehouses include the following dimension tables products, employees, customers, time, and location.  Lets say your business requirement is to provide an  time tracking data warehouse.  You would to want to implement a employee dimension table that included at least the following attributes (columns) first name, last name, status, start date, hire date, end date, department name title, salary etc….   we could actually go on and on and this is okay as long as the attributes support your business requirements.

What are dimension hierarchies?

Dimension hierarchies provide a way to define a relationship between multiple attributes within a dimension. They are commonly defined as a structure to provide drill up and drill down capabilities.  You can have multiple hierarchies within a dimension. For example, in a time dimension you might want to have two separate hierarchies, one for fiscal year and another for calendar year.  These two dimension could contain the following attributes year, quarter, month, day.

Best Practices for designing a Dimension table

• Use a unique identifier integer column that is auto incremental as your primary key.  This is commonly known as a surrogate key.
• Use the source’s primary key as an alternating key.
• Any additional attributes (columns) that describe the business entity

Slowly Changing Dimensions

Now that we know how to build a dimension we need to consider how the data is stored.  Yes, occasionally the attribute data changes.  For example, lets pretend you are a die hard Pirates fan and built a Data Warehouse to do analysis on your favorite players.  How would you handle promotions like Andrew McCutchen getting called up from AAA Indianapolis to the Pirates?

The following are options to handle slowly changing dimensions:

1. Do nothing (type 0).  This approach is highly not recommended.  This cannot guarantee history preservation and includes the least control over managing changed attributes.
2. Overwrite old data with new data (type 1)
   This completely overwrites the previous attribute value.  This could be ideal if you had a spelling error or the historical value of this column is not crucial. This is the easiest method to implement but it can be hard to manage.
3. Create multiple records with different key values (type 2)
   This provides you with the ability to have an unlimited amount of history.  It is usually implemented by adding a start and end date column.  If you have to make changes to past records this could require you to also update fact records.
4. Create a new column for previous values (type 3)
   This allows only a fixed amount of history to be retained.  If you create two extra columns for the team attribute you can only store three team values (the current value and last two previous values)

I hope you enjoyed this post.  Next we will cover an introduction to facts and measures.

Question:
How do I obtain statistics for the utilization of SSRS reports?

Solution:

With a little research I found a great sample application on codeplex that provides statistics for SSRS.  The Server Management Sample Reports are available for both SQL Server 2005 & 2008.

The following solution provides answers to the following questions.  What are the top 10 most executed reports? What reports have the longest average execution time?  Who is accessing the reports?

To implement this solution all you have to is download the sample solution and follow the installation guide.  If you have any questions post them here and I will do my best to help you out.

I recently attended a Pittsburgh SQL Server user group meeting where Brent Ozar gave a presentation on the silent performance killer.  This motivated me to create a stored procedure that could leverage the DMVs in SQL 2005/2008 to gather index fragmentation statistics for all databases on a given server.

Goal

The goal is very simple.  Build a query that could be scheduled to grab statistics that are helpful towards determining if an index needs to be defragged or reorganized.  I would like to throw these results into a table so I could analyze them at a later date.  I would also like to monitor the fill factor and padding to determine if I need to make changes and to analyze if the changes are really helpful.

Download Scripts

The following script uses the following DMV’s sys.dm_db_index_physical_stats, sys.objects and sys.indexes and this script is provided as is.

Table Definition

The following is an explanation of the columns.  The following descriptions come from MSDN.

Script

   1:  ALTER PROCEDURE [dbo].[GetStatsForIndexes]

   2:      @PageCount INT = 100

   3:  

   4:  AS

   5:  BEGIN

   6:      -- SET NOCOUNT ON added to prevent extra result sets from

   7:      -- interfering with SELECT statements.

   8:      SET NOCOUNT ON;

   9:  

  10:      -- Declare varables

  11:      DECLARE @dbID INT, @dbName VARCHAR(128), @SQL NVARCHAR(MAX)

  12:  

  13:      -- Create a temp table to store all active databases

  14:      CREATE TABLE #databaseList

  15:      (

  16:            databaseID        INT

  17:          , databaseName      VARCHAR(128)

  18:      );

  19:  

  20:      -- we only want non-system databases who are currenlty online

  21:      INSERT INTO #databaseList (databaseID, databaseName)

  22:      SELECT d.database_id, d.name FROM sys.databases d where d.[state] = 0 and d.database_id > 4

  23:  

  24:  

  25:      -- Loop through all databases 

  26:         WHILE (SELECT COUNT(*) FROM #databaseList) > 0  BEGIN

  27:  

  28:             -- get a database id

  29:          SELECT TOP 1 @dbID = databaseID, @dbName = databaseName

  30:          FROM #databaseList;

  31:  

  32:              SET @SQL = 'INSERT INTO DBA_Tools.dbo.IDX_FRAG (databaseName, ObjectName, indexName, partitionNumber, fragmentation, fill_factor, is_padded, type_desc, page_count, [date])

  33:                  SELECT

  34:                    db.name AS databaseName

  35:                  , obj.name AS ObjectName

  36:                  , idx.name AS indexName

  37:                  , ps.partition_number AS partitionNumber

  38:                  , ps.avg_fragmentation_in_percent AS fragmentation

  39:                  ,idx.fill_factor

  40:                  ,idx.is_padded

  41:                  ,idx.type_desc

  42:                  , ps.page_count

  43:                  , GETDATE() as [date]

  44:              FROM sys.databases db

  45:                INNER JOIN sys.dm_db_index_physical_stats ('+CAST(@dbID AS VARCHAR(10))+', NULL, NULL , NULL, N''Limited'') ps

  46:                    ON db.database_id = ps.database_id

  47:                INNER JOIN '+ @dbName+'.sys.objects obj ON obj.object_id = ps.object_id

  48:                INNER JOIN '+ @dbName+'.sys.indexes idx ON idx.index_id = ps.index_id AND idx.object_id = ps.object_id

  49:              WHERE ps.index_id > 0

  50:                 AND ps.page_count > 100

  51:              ORDER BY page_count desc

  52:              OPTION (MaxDop 1);'

  53:  

  54:          EXECUTE sp_executesql @SQL

  55:          -- remove the database from the databases table

  56:          DELETE FROM #databaseList WHERE databaseID = @dbID

  57:  

  58:          -- get the next database in the databases table

  59:          SELECT TOP 1 @dbID = databaseID, @dbName = databaseName

  60:          FROM #databaseList;

  61:  

  62:      END

  63:      -- temp table is no longer needed, so we will kill it.

  64:      DROP TABLE #databaseList;

  65:  END

I noticed a great event that is occurring down south.  Its called SQLSaturday and one of my short term goals is to see if it’s possible to bring this great event to Wheeling, WV. 

What is SQLSaturday?

SQLSaturday is a platform for free one day training events for SQL Server professionals. This event focuses on speakers, providing a good variety of topics, and making it all happen through the efforts of volunteers. Whether you’re attending one or thinking about hosting your own(this would be me), we think you’ll find it’s a great way to spend a Saturday.

Initial Goals:

1. Bring technology professionals from Pittsburgh, Columbus and Morgantown to Wheeling.
2. Have 50 to100 attendees attend this initial event.
3. Provide great speakers to present topics about SQL Server and .NET
4. Utilize sponsors to make the event 100% free to all who attend.
5. Provide the opportunity for IT Professionals to network with their peers.
6. Provide exposure for AITP and the Greater Wheeling Chapter of AITP 

Conclusion:

Will this event happen?  I sure hope so, but  I am still planning.  I hope to have an answer soon.  If we do go live I am targeting early 2010.

I will post my future action items and the decisions I make soon.  I hope that this series of posts are helpful for people who are contemplating if they should start a similar event in their area.

If you have any comments, thoughts or suggestions please share them.