Parallel bootstrap aggregating in a data warehouse appliance

A computer program product of creating bootstrap samples from a dataset, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a computer system to:

• generate, with a process node, a series of random integers;
• create, with the process node, an assignment map, the assignment map includes a row identifier for each row of the dataset;
• assign, with the process node, a plurality of bootstrap sample identifiers defined by the series of random integers to at least one row identifier in the assignment map;
• locate, with a user-defined table function of the process node, row identifiers in the assignment that have at least one bootstrap sample identifier assigned;
• extract, with the process node, entries in the assignment map that have at least one bootstrap sample identifier assigned, wherein the bootstrap sample identifiers, the row identifier of the entries, and data of the row identified form an output table;
• and
• create, with the process node and based on the assignment map, the output table, each row of the output table includes an instance of a bootstrap sample identifier, the row identifier assigned with the instance of the bootstrap sample identifier, and data from the row of the data set associated with the row identifier.

A system for creating bootstrap samples from a dataset, the system comprising:

• a host server;
• a plurality of process nodes communicatively coupled to the host server;
• and
• a plurality of storage modules, each of the plurality of process nodes in communication with at least one of the plurality of storage modules, wherein each of the plurality of process nodes is configured to perform a method, the method comprising:
• generating a series of random integers;
• creating an assignment map, the assignment map includes a row identifier for each row of the dataset;
• assigning, in the assignment map, a plurality of bootstrap sample identifiers defined by the series of random integers to at least one row identifier in the assignment;
• locating, with a user-defined table function of the process node, row identifiers in the assignment that have at least one bootstrap sample identifier assigned;
• extracting entries in the assignment map that have at least one bootstrap sample identifier assigned, wherein the bootstrap sample identifiers, the row identifier of the entries, and data of the row identified form an output table;
• and
• creating, based on the assignment map, the output table, each row of the output table including an instance of a bootstrap sample identifier, the row identifier assigned with instance of the bootstrap sample identifier, and data from the row of the dataset.