Skip to main content

SSIS Script for handling bad dates

Oracle and SSIS both have the ability to handle dates which SQL server's DateTime type won't accept.
A reasonably simple solution is to leverage the script component to detect and repair the invalid dates... here's a step-by-step guide for doing exactly that...

  1. Add a script component to your data flow, in transform mode.
  2. Open the editor for the script component
  3. Under Input Columns, select all the date columns you want to repair, and set their usage type to READ/WRITE (this is vital, else the script will break).
  4. Under Script, click the edit script button
  5. Select and delete all text
  6. Paste the C# code from here
  7. Close the source code window, click OK to dismass the script editor.
  8. Run the data flow.
The script will efficiently detect date with bad years and attempt to correct them to something which SQL finds palettable.

Give it a whirl and let me know what you think!

Comments

Popular posts from this blog

Reading Zip files in PowerQuery / M

Being a fan of PowerBI, I recently looked for a way to read zip files directly into the Data Model, and found this blog which showed a usable technique. Inspired by the possibilities revealed in Ken's solution, but frustrated by slow performance, I set out to learn the M language and write a faster alternative. UnzipContents The result of these efforts is an M function - UnzipContents - that you can paste into any PowerBI / PowerQuery report. It takes the contents of a ZIP file, and returns a list of files contained therein, along with their decompressed data: If you're not sure how to make this function available in your document, simply: Open up PowerQuery (either in Excel or in PowerBI) Create a new Blank Query. Open up the Advanced Editor  (found on the View tab in PowerBI). Copy-Paste the above code into the editor, then close the editor. In the properties window, rename the the function to  UnzipContents Usage Using the function is fairly straight forw

Power Query: Transforming YYYYMM dates (the quick way)

Accountants. Their unit of work seems to be the month, as if individual days don't exists, or don't count somehow. Nowhere is this better seen than in the notion of the accounting period , which all too often follows the form YYYYMM.  Try converting this directly into a date and Power Query starts making excuses faster than a kid with his hand caught in the cookie jar. The quick solution to this is to understand what Power Query's Table.TransformColumns does, and then leverage this knowledge to transform your YYYYMM values into proper date type columns. Table.TransformColumns As it's name suggests, this handy function allows you to convert the contents of a column from one type to another. The basic syntax is: = Table.TransformColumns( #"Your Source Table", { A list of tuples, specifying the columns and what functions to apply to each value} ) Lists {denoted by curly braces} are something you need to get comfortable with if you

Easily Move SQL Tables between Filegroups

Recently during a Data Warehouse project, I had the need to move many tables to a new file group. I didn't like any of the solutions that I found on Google, so decided to create on of my own. The result? MoveTablesToFilegroup Click here for a nifty stored proc allows you to easily move tables, indexes, heaps and even LOB data to different filegroups without breaking a sweat. To get going, copy-paste the code below into Management Studio, and then run it to create the needed stored procedure. Hopefully the arguments are self explanatory, but here are some examples: 1. Move all tables, indexes and heaps, from all schemas into the filegroup named SECONDARY: EXEC dbo.sp_MoveTablesToFileGroup @SchemaFilter = '%', -- chooses schemas using the LIKE operator @TableFilter  = '%', -- chooses tables using the LIKE operator @DataFileGroup = 'SECONDARY', -- The name of the filegroup to move index and in-row data to. @ClusteredIndexes = 1, --