One thing that we run into a lot is when our source data changes a format or has new data, like a new column as an example. We will have these long and complex conversions and then the input file changes and the new column can throw off lots of downstream stuff. this is the single hardest part we have found about using the transform program. If this doesn’t already exists, I wonder if there would ever be a way to say something like “the new input data doesnt look the same, are there new columns we can ignore”. I know that I can add a transform as the first step and remove the column, but to do that I have to first add the new input format and that alone will sometimes blow up filters and lookups downstream. hoping this makes sense.
The way around this is to use a Stack to place all the expected columns in a particular order. Any unexpected columns will then be added to the end.
Ok, so in your example if a new column, say “birthdate” all of a sudden was in the input data, it would push that to the last column and then not impact any downstream transformations? with our developers, I can often have them add additional files to the last column, but I thought that would still impact the downstream conversions. ill try it out.
If you check use only top dataset columns then it won’t add any columns unless they are in the top dataset.
Coming across that as well and Stack is helping a lot, but it would be great if we could set the columns and order within the transform so we don’t have to keep separate template files.
Maybe calling it something like … Structure or Lock Columns?
The way I see it working is that the first time it is placed, it reads the columns in its input and puts them in a list. This way it can be added into an existing transform file before a new file with new or reordered columns is being read and the transform will stay intact.
Then have an interface that allows us to remove the columns we don’t want to keep and also to manually add/enter new columns if we want to have new columns in new files.
The key here is that it does not change the columns by itself any more if its input changes.
You can use Input from clipboard to add known column header to use with Stack. Then check use only top dataset columns in the Stack if you don’t want to add any additional columns. I’m not sure any additional functionality is needed.
what do you mean about “input from clipboard.” How does that prevent you from having to have a “column header file” for each transform. We have about 30 of them we use pretty consistently.
What it means is that instead of using a file for the headers only, you can create your headers and then simply copy it to clip board and then in EDT use input From Clipboard, this way the headers are saved with the transform file and in future if you need to re-arange the columns simply create the new headers and select the Clipboard transform and then click on the Play button on the right pannel to import the new Headers.
Add Stack transform and add your file in whatever way your headers are, since the column headers are used from the clipboard and stacked based on headers.
This way even if you remove the file and add another file, your transforms down the line will stay intact or you can add additional file with same column in different order
Add Stack trasnform
change me to upper,2,3,4
Now if you remove file one and add file2.csv that have the same column header but in different order the transforms will still work