Tuesday, August 17, 2010

ROW SAMPLING TRANSFORMATION

What does the Row Sampling Transformation do?
The Row Sampling Transformation takes a fixed number of rows from a source data set – in a similar manner to the Percentage Sampling Transformation, except that instead of a proportion of your data, it takes a fixed number of rows. It splits your data set into two sets, the Sampled and Unsampled outputs
Configuring the Row Sampling Transformation
There are two important properties to configure on the transformation. First is the Number of rows, which determines how many rows will fall into the Sample output. Second is the random seed. This seed tells the random selection algorithm which rows to choose. If you fix the seed, you will get consistent results – if you understand a little about randomisation in computing, you will understand randomness is a bit of a relative concept to a computer. If you leave the checkbox unselected, the package will pick a random seed based on the OSes’ tick count, so results will appear to change.
You can also name your Sample and Unselected outputs, should you wish. It’s worth noting that you aren’t obliged to actually use either output downstream of the component, so you can use this component to select a fixed number of rows from your source – or ignore a fixed number of rows from your source, by only using the Unselected output.





















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