Hyperion Solutions Corporation

Complete Genomics, Inc.

Oracle International Corporation

Igor Nazarenko

Radoje Drmanac

Ambuj Shatdal

Aaron L Halpern

Jonathan M Baccash

Uri Rodny

Srinivas Duvvuri

Arun Kumar

Vijay K Anjur

Kevin Kaixuan Liao

Mark Goldenshteyn

Maya Binkovich

Hemanta Banerjee

Vaishnavi Anjur

Paolo Carnevali

Geoffrey Nilsen

Bruce Martin

Nilsen Geoffrey

Generating an index includes receiving a reference sequence and applying one or more key patterns to the reference sequence to obtain a plurality of keys in the index. Each of the one or more key patterns is derived based on a corresponding set of oligomer sequence relationships of a plurality of oligomer sequences that are expected to be generated from the reference, and the keys correspond to a plurality of candidate and/or validated locations in the reference sequence.

Indexing a reference sequence for oligomer sequence mapping

Mapping oligomer sequences includes receiving a set of related oligomer sequences, applying one or more key patterns derived from a set of oligomer sequence relationships to obtain one or more keys that are consistent with the set of related oligomer sequences, modifying positions within these keys, and locating the one or more keys in an index configured to map a plurality of candidate and/or validated keys to their respective possible and/or validated locations in a reference.

Oligomer sequences mapping

Mapping oligomer sequences includes receiving a set of related oligomer sequences, applying one or more key patterns derived from a set of oligomer sequence relationships to obtain one or more keys that are consistent with the set of related oligomer sequences, and locating the one or more keys in an index configured to map a plurality of possible keys to their respective candidate and/or validated locations in a reference.

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

A method of operating a multi-dimensional database is disclosed. In this method, a multi-dimensional portion of the data is transferred to a multi-dimensional database. A relational portion of the cube is kept in the relational database. When data from the relational portion needs to be accessed, the system produces the SQL queries to obtain data from the relational database.

Method of splitting a multi-dimensional cube between a multi-dimensional and a relational database

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.

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Sunnyvale, CA, United States of America

Igor Nazarenko