The Checksum Transformation computes a hash value, the checksum, across one or more columns, returning the result in the Checksum output column. The transformation provides functionality similar to the T-SQL CHECKSUM function, but is encapsulated within SQL Server Integration Services, for use within the pipeline without code or a SQL Server connection. As featured in The Microsoft Data Warehouse Toolkit by Joy Mundy and Warren Thornthwaite from the Kimbal Group. Have a look at the book samples especially Sample package for custom SCD handling. All input columns are passed through the transf... [More]

This component needs little explanation. It generates random integer (DT_I4) and string (DT_WSTR) data and places them in the pipeline. You specify how many columns of each you would like and for any string columns you pass a fixed length value. You then need to specify how many rows in total you require to be generated. This component is used by us to do testing of the pipeline and components downstream. Previously we would have used a script component (as a source) to generate the rows but found ourselves rewriting the code too often so created this component. Screenshots ... [More]

Use the power of regular expressions to cleanse your data right there inside the Data Flow. This transformation includes a full user interface for simple configuration, as well as advanced features such as error output configuration. Two regular expressions are used, a match expression and a replace expression. The transformation is designed around the named capture groups or match groups, and even supports multiple expressions. This allows for rich and complex expressions to be built, all through an easy to reuse transformation where a bespoke Script Component was previously the only alterna... [More]

As the name suggests we have taken the current Row Count Transform that is provided by Microsoft in the Integration Services toolbox and we have recreated the functionality and extended upon it. There are two things about the current version that we thought could do with cleaning up Lack of a custom UI You have to type the variable name yourself In the Row Count Plus Transformation we solve these issues for you. Another thing we thought was missing is the ability to calculate the time taken between components in the pipeline. An example usage would be that you want to know how many r... [More]

The Row Number Transformation calculates a row number for each row, and adds this as a new output column to the data flow. The column number is a sequential number, based on a seed value. Each row receives the next number in the sequence, based on the defined increment value. The final row number can be stored in a variable for later analysis, and can be used as part of a process to validate the integrity of the data movement. The Row Number transform has a variety of uses, such as generating surrogate keys, or as the basis for a data partitioning scheme when combined with the Conditional Sp... [More]

The Trace File Source adapter is a useful addition to your SSIS toolbox.  It allows you to read profiler traces stored as .trc files and read them into the Data Flow.  From there you can perform filtering and analysis using the power of SSIS. There is no need for a SQL Server connection this just uses the trace file. Example Usages Cache warming for SQL Server Analysis Services Reading the flight recorder Find out the longest running queries on a server Analyze statements for CPU, memory by user or some other criteria you choose Properties The Trace File Source adapt... [More]

The Trash Destination and this article came from early experiences of using SSIS and community feedback at the time. When developing a package it is very useful to have a destination adapter that does nothing but consume rows with no setup requirement. You often want run a package part way through development, or just add a path so you can set a Data Viewer. There are stock tasks that can be used, but with the Trash Destination all columns are treated as selected automatically (usage type of read-only), so the pipeline knows they are required. It is also obvious that this is for development or... [More]

The regular expression transformation exposes the power of regular expression matching within the pipeline. One or more columns can be selected, and for each column an individual expression can be applied. The way multiple columns are handled can be set on the options page. The AND option means all columns must match, whilst the OR option means only one column has to match. If rows pass their tests then rows are passed down the successful match output. Rows that fail are directed down the alternate output. This transformation is ideal for validating data through the use of regular expressions... [More]

Every now and then I've come across scenarios where I need to update a lot of packages all in the same way. The usual scenario revolves around a group of packages all having been built off the same package template, and something needs to updated to keep up with new requirements, a new logging standard for example.You'd probably start by updating your template package, but then you need to address all your existing packages. Often this can run into the hundreds of packages and clearly that's not a job anyone wants to do by hand. I normally solve the problem by writing a simple console applicat... [More]

This code sample programmatically creates a package that imports a text file into SQL Server, with a Flat File Source and the OLE-DB Destination. This shows how you can leverage the SSIS engine to write your own data import tool for example, but beware importing files is not as simple as it may seem. When you build a similar package in the designer and and select your file, you make some choices about the file format. It seems quite simple, but there is actually some quite complex thinking behind the scenes to parse the file and make suggestions on the file format for columns and their data ... [More]

If you are building SSIS 2008 packages programmatically and adding data flow components, you will probably need to know the creation name of the component to add. I can never find a handy reference when I need one, hence this rather mundane post. See also CreationName for SSS 2005. We start with a very simple snippet for adding a component: // Add the Data Flow Task package.Executables.Add("STOCK:PipelineTask"); // Get the task host wrapper, and the Data Flow task TaskHost taskHost = package.Executables[0] as TaskHost; MainPipe dataFlowTask = (MainPipe)taskHost.InnerObject... [More]

This code sample programmatically creates a package with an OLE-DB Source and a Flat File Destination, and the resulting package exports data from SQL Server to a CSV file. The finished package just has the one Data Flow Task shown below.   The code creates the package, configures the task, and components, then saves the package to disk, useful for checking the package and testing, before finally executing. namespace Konesans.Dts.Samples { using System; using Microsoft.SqlServer.Dts.Runtime; using Microsoft.SqlServer.Dts.Pipeline.Wrapper; using RuntimeWrapper ... [More]

This code sample programmatically creates a package with an OLE-DB Source and a Raw File Destination, and the resulting package exports data from SQL Server to a raw file. The finished package just has the one Data Flow Task shown below.   The code creates the package, configures the task, and components, then saves the package to disk, useful for checking the package and testing, before finally executing. namespace Konesans.Dts.Samples { using System; using Microsoft.SqlServer.Dts.Runtime; using Microsoft.SqlServer.Dts.Pipeline.Wrapper; internal class SqlTo... [More]

If you are building SSIS 2005 packages programmatically and adding data flow components, you will probably need to know the creation name of the component to add. I can never find a handy reference when I need one, hence this rather mundane post. See also CreationName for SSS 2008. We start with a very simple snippet for adding a component: // Add the Data Flow Task package.Executables.Add("STOCK:PipelineTask"); // Get the task host wrapper, and the Data Flow task TaskHost taskHost = package.Executables[0] as TaskHost; MainPipe dataFlowTask = (MainPipe)taskHost.InnerObject... [More]

When building our own custom pipeline components two methods in particular are very important and it may become a little confusing as to which one is used in which situation. The two methods are: ProcessInput PrimeOutput Depending on the type of component you are building will depend on whether you need to use one or both of these methods. Let's take a look now and identify how to use them correctly. All components need to have the DtsPipelineComponent attribute, and in particular the ComponentType property. As we detail each type of component we will tell you w... [More]

When developing your own custom components for that more professional, and also practical, finish you may want to use your own icon rather than relying on the default system icon. You set this through the IconResource property of the appropriate component attribute; DtsTask for a control flow component or task, DtsPipelineComponent for a data flow component, and DtsConnection for your own connection manager. The DtsConnection IconResource functionality is not fully implemented, and you will always get the default icon. To set an icon for your component the first thing you need to do is to pr... [More]