Gopivotal, Inc.

Other

Vmware, Inc.

Pivotal Software, Inc.

Gemstone Systems, Inc.

Russell Okamoto

Greg Passmore

Data mining tools often require users to learn arcane query syntax and complex user interfaces in order to compose data mining queries. A 'stratigraph' is a data mining tool that enables non-programmers to explore data by visually assembling queries through direct manipulation and rendering query results in “layers”. Each layer—one for each predicate of a query—can be subsequently filtered by selecting a value from the current layer. Selecting a value in a layer expands the layer to produce a higher layer based on the selected value, all previous layer predicates, and the next user-specified predicate. As exploration continues upward, layers build on top of each other, forming query “spires” that become visual query landmarks. This interactive exploration process is evocative of how geologists decode the story of rock formations by analyzing how strata evolve. Hence the name “stratigraph” is an homage to this science of stratigraphy.

Method and system for data mining layers

A distributed data management system has multiple virtual machine nodes operating on multiple computers that are in communication with each other over a computer network. Each virtual machine node includes at least one data store or 'bucket' for receiving data. A digital hash map data structure is stored in a computer readable medium of at least one of the multiple computers to configure the multiple virtual machine nodes and buckets to provide concurrent, non-blocking access to data in the buckets, the digital hash map data structure including a mapping between the virtual machine nodes and the buckets. The distributed data management system employing dynamic scalability in which one or more buckets from a virtual machine node reaching a memory capacity threshold are transferred to another virtual machine node that is below its memory capacity threshold.

Distributed data management system

A database query optimization method is provided for database queries that include predicates, the queries being directed to at least one database table having data in rows and columns. The method includes associating a lineage bit set with each row of the database table, the lineage bit set providing a binary predicate state indication whether each predicate is met or are not met by data in the row. A dependency bit set is established to provide a binary indication of the predicates that are included in each query. Queries are applied against the database table by a logical operation between the lineage bit set and the dependency bit set. A database query optimization data structure includes a lineage bit set associated with each row in the database table. The lineage bit set provides a binary predicate state indication whether each predicate is met or are not met by data in the row. The data structure further includes a dependency bit set that provides a binary indication of the predicates included in each query.

Multi-query optimization

A method and system for creating hyperlinks and hyperlinked documents from the direct manipulation of information in a hypermedia processing system, or the like, in a fashion that requires little effort on the part of the user. A user can effortlessly create hyperlinks and hyperlinked documents in one seamless motion by simply pressing a predetermined key while dragging and dropping source-visual elements such as a text element onto target visual elements such as another text element. The method and system is defined herein as a &ldquo;drag and link&rdquo; operation, enabling the user to create hyperlinks and hyperlinked documents from the direct manipulation of information with the familiar ease of the conventional drag and drop operation.

Method and system for creating hyperlinks and hyperlinked documents from the direct manipulation of information (&ldquo;Drag and link&rdquo; operation)

Growing community of inventors

Beaverton, OR, United States of America

Russell Okamoto