SSIS - Is there a Data Flow Source component that

Question

We have written a number of SSIS packages that import data from CSV files using the Flat File Source.

It now seems that after these packages are deployed into production, the providers of these files may deliver files where the column order of the files changes (Don't ask!). Currently if this happens, our packages will fail.

For example, an additional column is inserted at the beginning of each row. In this case, the flat file source continues to use the existing column order, which obviously has a detrimental effect on the transformation!

Eg. Using a trivial example, the original file has the following content :

OurReference,Client,Amount
235,MFI,20000.00
236,MS,30000.00

The output from the flat file source is :

OurReference   Client   Amount
235            ClientA  20000.00
236            ClientB  30000.00

Subsequently, the file delivered changes to :

OurReference,ClientReference,Client,Amount
235,A244,ClientA,20000.00
236,B222,ClientB,30000.00

When the existing unchanged package is run against this file, the output from the flat file source is :

OurReference   Client   Amount
235            A244     ClientA,20000.00
236            B222     ClientB,30000.00

Ideally, we would like to use a data source that will cope with this problem - ie which produces output based on the column names, instead of the column order.

Any suggestions would be welcomed!

Answer 1

Not that I know of.

A possibility to check for the problem in advance is to set up two different connection managers, one with a single flat row. This one can read the first row and tell if it's OK or not and abort.

If you want to do the work, you can take it a step further and make that flat one-field row the only connection manager, and use a script component in your flow to parse the row and assign to the columns you need later in the flow.

As far as I know, there is no way to dynamically add columns to the flow at runtime - so all the columns you need will need to be added to the script task output. Whether they can be found and get parsed from the each line is up to you. Any "new" (i.e. unanticipated) columns cannot be used. Columns which are missing you could default or throw an exception.

A final possibility is to use the SSIS object model to modify the package before running to alter the connection manager - or even to write the entire package dynamically using the object model based on an inspection of the input file. I have done quite a bit of package generation in C# using templates and then adding information based on metadata I obtained from master files describing the mainframe files.

Answer 2

Here is a rough approach. I will write down the limitations at the end. Create a flat file source. Put the entire row in one column. Do not check Column names in first data row. Create a Script Component Code:

public override void Input0_ProcessInputRow(Input0Buffer Row)
{
    string sRow = Row.Column0;

    string sManipulated = string.Empty;
    string temp = string.Empty;

    string[] columns = sRow.Split(',');

    foreach (string column in columns)
    {
       sManipulated = string.Format("{0}{1}", sManipulated, column.PadRight(15, ' '));
    }
    /* Note: For sake of demonstration I am padding to 15 chars.*/

    Row.Column0 = sManipulated; 
}

Create a flat file destination Map Column0 to Column0

Limitation: I have arbitrarily padded each field to 15 characters. Points to consider: 1. Do we need to have each field of same size? 2. If yes, what is that size?

A generic way to handle that would be to create a table to store the file name, fields, and field sizes. Use the file name to dynamically create the source and destination connection manager. Use the field name and corresponding field size to decide the padding. Not sure, if you need this much flexibility. If you have any question, please respond.

Answer 3

Best approach would be to run a check before the SSIS package imports the CSV data. This may have to be an external script/application, because I don't think you can manipulate data in the MS Business Intelligence Studio.