Hyperion Solutions Corporation

Oracle International Corporation

Fatlens, Inc.

Complete Genomics, Inc.

Jonathan M Baccash

Radoje Drmanac

Ambuj Shatdal

Igor Nazarenko

Aaron L Halpern

Uri Rodny

Paolo Carnevali

Geoffrey Nilsen

Bruce Martin

Nilsen Geoffrey

The cost of running a query (having a query range) on a multidimensional database may be estimated using a process factors criteria beyond merely the number of affected records. First, a materialized view of the database may be represented as a container of tuples, sorted by key. Then keys may be stepped through, each key representing a mapping of a combination of tuples from the container. At each step, the process may request the next smallest key in the query range greater than or equal to the key of the current step, which results in the tuple in the database whose key is the smallest, greater than or equal to the requested key, and determine if the resulting is in the query range. The cost of the query may then be estimated as the number of tuples upon which the range check was performed.

Query costing in a multidimensional database

Methods and computer program products for creating sketches of a document, which are compared with sketches of other documents, in order to determine the documents' degree of similarity. A sketch is a digest of information from random locations within a document. A document is divided into a set of shingles. Each shingle is converted into a set of fingerprints. A sketch is determined based on one bit fingerprints thus created. In order to create additional sketches of the document, a new set of fingerprints are created by randomization techniques.

Method for document fingerprinting

Selection of certain views of a multidimensional database to materialize may be accomplished using an efficient and effective solution. A set of all potential views may be stored in a structure. A path in the structure may then be traversed in an indicated direction through the structure, the path including two or more potential views and beginning at an indicated view. Then two or more immaterialized views in the path may be compared to each other to determine which immaterialized view is the optimum choice for maximizing benefit if selected to be materialized. Then the traversing and comparing may be continually iterated through, each iteration utilizing an indicated direction different than the last, each iteration also utilizing an indicated view set at the optimum choice determined by the last iteration, the iterating continuing until it converges on a single view. That single view may then be selected for materialization.

View selection for a multidimensional database

The cost of running a query (having a query range) on a multidimensional database may be estimated using a process factors criteria beyond merely the number of affected records. First, a materialized view of the database may be represented as a container of tuples, sorted by key. Then keys may be stepped through, each key representing a mapping of a combination of tuples from the container. At each step, the process may request the next smallest key in the query range greater than or equal to the key of the current step, which results in the tuple in the database whose key is the smallest, greater than or equal to the requested key, and determine if the resulting tuple is in the query range. The cost of the query may then be estimated as the number of tuples upon which the range check was performed.

Growing community of inventors

Sunnyvale, CA, United States of America

Jonathan M Baccash