Friday, June 29, 2012

SQL 2005 Upgrade Exams Expire 31st July 2012

The SQL 2005 to 2008 upgrade exams expire on 31st July 2012. This includes:

  • Exam 70-453: Upgrade: Transition Your MCITP SQL Server 2005 DBA to MCITP SQL Server 2008 DBA
  • Exam 70-454: Upgrade: Transition Your MCITP SQL Server 2005 DBD to MCITP SQL Server 2008 DBD
  • Exam 70-455: Upgrade: Transition Your MCITP SQL Server 2005 BI Developer to MCITP SQL Server 2008 BI Developer

To be honest it’s probably worth starting again on the SQL Server 2012 exams if you haven’t upgraded to 2008 at this point.

More information can be found here:

Wednesday, June 27, 2012

Creating Database Snapshots Via SMO

The SMO (Server Management Objects) API is the best way to programmatically interact with SQL Server. On a recent project I had a requirement to create database snapshots on a regular basis using this technique. I’ve created a static C# wrapper class to look after the implementation, as some of the sample code I found online for this was pretty average.

There’s a few things to validate before the snapshot can be created:

  • Database name and snapshot name must be different
  • Database must exist
  • Snapshot must not exist
  • The SQL Server Edition must be Enterprise or Developer. (Standard doesn’t support snapshots)

Once those conditions are satisfied, snap away! Here's my validation code:

private static void ValidateSnapshotParameters(Server server, string databaseToSnap, string snapshotName)
    //Server Edition must be Developer or Enterprise
    if(server.EngineEdition != Edition.EnterpriseOrDeveloper)
        throw new SnapshotException("Snapshots are not supported in this edition of SQL Server. Enterprise or Developer edition is required.");

    //Database must exist
    Database db = server.Databases[databaseToSnap];
    if(db == null)
        throw new SnapshotException(string.Format("Specified Database does not exist: {0}", databaseToSnap));

    //Snapshot must not exist
    Database snapshot = server.Databases[snapshotName];
    if (snapshot != null)
        throw new SnapshotException(string.Format("A snapshot or database named {0} already exists", snapshotName));

    //Database and snapshot cannot be the same name
    if(databaseToSnap == snapshotName)
        throw new SnapshotException("Snapshot name must be different from Database name");

Below is the code to perform the actual snapshot. I recommend putting the validation method and the TakeSnapshot() method in a static class. Note that the snapshot must have the same filegroups and data files as the database being snapped. The implementation below looks after this. I've used the .ss file extension here, but it's an arbitrary choice according to MSDN. The most important line of code is:

snapshot.DatabaseSnapshotBaseName = databaseToSnap;

If you don't specify the DatabaseSnapshotBaseName property, then really all you are doing is creating a blank database!

public static void TakeSnapshot(Server server, string databaseToSnap, string snapshotName)
        ValidateSnapshotParameters(server, databaseToSnap, snapshotName);

        Database sourceDatabase = server.Databases[databaseToSnap];
        Database snapshot = new Database(server, snapshotName);
        snapshot.DatabaseSnapshotBaseName = databaseToSnap;

        //Create the same filegroups on the snapshot
        foreach (FileGroup fg in sourceDatabase.FileGroups)
            snapshot.FileGroups.Add(new FileGroup(snapshot, fg.Name));

            //Add all of the files to the new filegroup
            foreach (DataFile file in fg.Files)
                snapshot.FileGroups[fg.Name].Files.Add(new DataFile(snapshot.FileGroups[fg.Name], file.Name, Path.Combine(sourceDatabase.PrimaryFilePath, string.Format("{0}_{1}.ss", snapshot.Name, file.Name))));

        //Create the snapshot
    catch (FailedOperationException ex)
        //TODO: Logging

The snapshot operation completes in O(1) time, that is to say the time to complete the operation is not related to the size of the database. Finally, my implementation of a SnapshotException, which is a simple derivation of ApplicationException.

public class SnapshotException : ApplicationException
    public SnapshotException(string message) : base(message){}

Friday, June 22, 2012

Using the ADO.NET SqlBulkCopy Class

Recently I had an interview where I was asked about the ADO.NET Bulk Copy class. Frustratingly, I had used it about 12 months prior and couldn’t remember much about it. So this post serves the dual purpose of providing a tutorial for the class and reinforcing my general knowledge.


The SqlBulkCopy class can be found in the System.Data.SqlClient namespace, and it was introduced in .NET 2.0. As the name suggests, it allows for the bulk insert of data into a SQL Server table. The benefit of this over a traditional insert is that the operation is minimally logged and therefore much faster at inserting a large number of rows.


Transactions management is applicable to the SqlBulkCopy class, and consequently a SqlTransaction can be passed to the constructor if required. Rolling back will cause all rows that have been inserted by the SqlBulkCopy object to be reversed out. So the operation is atomic and reliable.

Testing SqlBulkCopy

I set up the following table to test the SqlBulkCopy class. My target platform for this series of tests was SQL Server 2012 Developer Edition 11.0.2100.60.

 FirstName VARCHAR(50)   NOT NULL,
 LastName VARCHAR(100)  NOT NULL,
 Phone  VARCHAR(20)   NULL,
 City  VARCHAR(50)   NULL,

This should be sufficient to test a few things that I am curious about – non-nullable columns, an identity column and a basic primary key.

Here is the C# code I am using to run the test:

public static void BulkCopyExample(string connectionString, DataTable rowsToInsert, int batchSize)
        using (SqlBulkCopy bulkCopy = new SqlBulkCopy(connectionString))
            //Batch Size
            bulkCopy.BatchSize = batchSize;

            //Destination Table Name
            bulkCopy.DestinationTableName = "Customer";

            //Write the rows to the Table

    catch (Exception ex)

Column Mappings

The code above is pretty simple, but there’s one key thing missing. There are no column mappings, so the SqlBulkCopy compoment doesn’t know how to map the provided DataTable to the underlying SQL Table.

Non-Nullable Columns

When the mappings aren’t done properly (or at all), you may receive an exception similar to the following:

The given value of type String from the data source cannot be converted to type datetime of the specified target column.

This particular exception is related to the DOB column, which needs to have a valid DateTime provided.

Identity Column

Simply omit the identity column from the ColumnMappings collection on the SqlBulkCopy object, and SQL Server will allocate the next available identity value for that column.

Here is the revised code, showing all of the columns neatly mapped. Note that nullable columns in the underlying table do not need to be mapped. I’ve omitted the City mapping to prove this.

//Column Mappings
bulkCopy.ColumnMappings.Add("FirstName", "FirstName");
bulkCopy.ColumnMappings.Add("LastName", "LastName");
bulkCopy.ColumnMappings.Add("DOB", "DOB");
bulkCopy.ColumnMappings.Add("Phone", "Phone");


The sample row goes into the table. Note the City column is null because the mapping was omitted.


Keeping Track of Progress

The NotifyAfter property of the SqlBulkCopy object determines how frequently the SqlRowsCopied event is fired. For example:

//Notify After
bulkCopy.NotifyAfter = 1000;

//Listen for the Event
bulkCopy.SqlRowsCopied += new SqlRowsCopiedEventHandler(bulkCopy_SqlRowsCopied);

This will call the SQLRowsCopiedEventHandler after every 1000 rows. Note that there is a performance overhead associated with this call. In the event handler, a SqlRowsCopiedEventArgs is received and this can be used to get the current rowcount.

Experimenting with Batch Size

The BatchSize property determines how many rows will be sent to SQL Server in each round trip. Smaller batch sizes will result in more trips to SQL Server, but larger batch sizes will take longer to commit. The optimal batch size will depend on a number of factors including the length of each row, and the total of number of rows being inserted.

To test the effect of different batch sizes on performance, I inserted 1,000,000 identical rows using varying batch sizes and measured the total time taken to complete the task. The table was truncated after each test to guarantee a level playing field.


The results are pretty interesting – a small batch number results in lousy performance, whereas a batch size of around 70,000 seems to be optimal for my table and the sample row I was working with. It would be interesting to re-run this test for rows of differing lengths.