The following node is available in the Open Source KNIME predictive analytics and data mining platform version 2.7.1. Discover over 1000 other nodes, as well as enterprise functionality at http://knime.com.

Row Sampling

This node extracts a sample (a bunch of rows) from the input data. The dialog enables you to specify the sample size. The following options are available in the dialog:

Dialog Options

Absolute
Specify the absolute number of rows in the sample. If there are less rows than specified here, all rows are used.
Relative
The percentage of the number of rows in the sample. Must be between 0 and 100, inclusively.
Take from top
This mode selects the top most rows of the table.
Linear sampling
This mode always includes the first and the last row and selects the remaining rows linearly over the whole table (e.g. every third row). This is useful to downsample a sorted column while maintaining minimum and maximum value.
Draw randomly
Random sampling of all rows, you may optionally specify a fixed seed (see below).
Stratified sampling
Check this button if you want stratified sampling, i.e. the distribution of values in the selected column is (approximately) retained in the output table. You may optionally specify a fixed seed (see below).
Use random seed
If either random or stratified sampling is selected, you may enter a fixed seed here in order to get reproducible results upon re-execution. If you do not specify a seed, a new random seed is taken for each execution.

Ports

Input Ports
0 Table to sample from.
Output Ports
0 The sampled table.
This node is contained in KNIME Base Nodes provided by KNIME GmbH, Konstanz, Germany.