DB Row Sampler

This node extracts a sample from the input data. The dialog enables you to specify the sample size and the sampling strategy.

Options

Output size type

Defines how the size of the output is specified: as a percentage of total rows (relative) or as an absolute number of rows.

Relative size

Specifies the percentage of rows in the database table to extract. Must be between 0 and 100 (inclusive).

Number of rows

Specifies the absolute number of rows to include in the output. If the input table contains fewer rows than specified, all rows are placed in the output.

Sampling strategy

Determines how rows are selected for the output. Strategies include random, stratified, and first rows (sequential).

• Random: Randomly selects rows from the input table if the connected database supports random sampling. Note that this method might be very slow for large database tables.
• Stratified: Preserves the distribution of values in the selected group column.
• First rows: Allows you to select the top-most rows of the input table. Note that the order of the rows depends on the connected database.

Group column

Specifies the column whose value distribution should be preserved in stratified sampling. Ensures both selected and non-selected rows reflect the same distribution of values.

Fixed random seed

Optional seed value for random or stratified sampling. Using a seed ensures the same rows are selected each time the node is executed. Without a seed, a different random selection will occur each time.

Views

This node has no views

Workflows

• 00 Main MenuKNIME Hub
• 00 Main MenuKNIME Hub
• 01_Create_basic_serviceKNIME Hub
• 02_Snowflake_Model_LearningKNIME Hub
• 04_Snowflake_Dynamic_Data_AppKNIME Hub
• Show all 29 workflows

Links

• No links available

Developers