International Business Machines Corporation

Ontera Inc.

Oracle International Corporation

William McKenna

Latha S Colby

David G Wilhite, Jr

Richard Lee Cole

Galt Johnson

Edward P Haslam

Nasi Jazayeri

William Dunbar

Yanan Zhao

Mohamed Ziauddin

Hakan Jakobsson

Lee E Schumacher

Craig J Bunger

Gopal B Mulagund

William B Dunbar

Disclosed herein are methods and compositions for determining an improved estimate of the fractional abundance of target analytes (e.g., specific polynucleotide sequences) in a sample using a nanopore sensor having one or more nanopores-, e.g., by correcting errors inherent to identifying and correlating electrical signals to amounts of a target analyte or reference analyte in a sample.

Multipore determination of fractional abundance of polynucleotide sequences in a sample

Disclosed herein are methods and compositions for determining an improved estimate of the true fractional abundance of target analytes (e.g., specific polynucleotide sequences) in a sample using a nanopore sensor, e.g., by correcting errors inherent to identifying and correlating electrical signals to amounts of a target analyte or reference analyte in a sample.

Fractional abundance of polynucleotide sequences in a sample

Described herein are approaches to implementing dynamic sampling in a way that lessens or eliminates the additional overhead incurred to perform dynamic sampling. Also described are techniques for determining characteristics about predicates not previously determined by conventional techniques for dynamic sampling. Dynamic sampling is used by a query optimizer to dynamically estimate predicate selectivities and statistics. When a database statement is received by a database server, an initial analysis of the database statement is made to determine the efficacy of dynamic sampling, that is, to determine whether optimization of the query would benefit from dynamic sampling and whether performance is not excessively impacted by the dynamic sampling process. If this analysis determines dynamic sampling should be used, then dynamic sampling is undertaken.

Optimizer dynamic sampling

Technique are provided for maintaining pre-computed aggregate views. A pre-computed aggregate view derived from one or more base tables is received, the pre-computed aggregate view including a pre-computed aggregate table and a view definition, the view definition including aggregate functions that can be any combination of sum, sum distinct, count(*), count, count distinct, min, and max, the view definition further including expressions that may be nullable. Changes to the one or more base tables are received, the changes being represented as insertions and deletions and being non-minimal. A set of incremental modifications to the pre-computed aggregate table are derived and applied based on the changes to the one or more base tables, wherein modifications may include any combination of inserts, deletes, and updates. Deriving the set of incremental modifications to the pre-computed aggregate table includes deriving a first table wherein each record, representing an aggregated group of changes, shows for each aggregation function, the contributions of base table changes that are insertions for the group and the contributions of base table changes that are deletions for the group and using some combination of information in the first table, the pre-computed aggregate table, and the one or more base tables from which the pre-computed view is derived.

Maintaining pre-computed aggregate views incrementally in the presence of non-minimal changes

Methods and apparatus implementing a technique for incrementally maintaining pre-computed aggregate views. In general, the technique includes: receiving a pre-computed aggregate view derived from one or more base tables. The pre-computed aggregate view including a pre-computed aggregate table and a view definition. The view definition including aggregation functions that can be any combination of sum, sum distinct, count(*), count distinct, min, and max. The view definition further including expressions that may be nullable. The technique includes receiving changes to the base table, the changes being non-minimal. The technique includes analyzing the view definition, including the type of aggregation functions and the nullability and data type of columns and expressions in the view definition, to reduce or eliminate the use of information in base tables in order to define the incremental modifications to the pre-computed aggregate table.

A system and method for answering a relational database query is presented. According to an embodiment of the present invention, a database query is received. It is then determined whether that query can be rewritten in such a manner as to be able to utilize a precomputed view, such that an answer to the rewritten query is equivalent to an answer to the original query. If the query can be rewritten, it is determined whether the rewritten query can more efficiently derive the answer than the original query. The query which has the most efficiently derived answer is the query which is utilized to derive that answer.

System and method for rewriting relational database queries

Server-integrated methods and apparatus for processing precomputed views for answering user queries on a database are described. In accordance with one embodiment, a system for answering user queries on a database stored on a server includes a query processing system integrated into the server and configured to respond to user queries, and a query processing system integrated into the server and configured to process precomputed results of user queries on the database. In another aspect, a method of answering user queries on a database stored on a server includes responding to user queries received at the server, and processing, at the server, precomputed results of user queries on the database.

Server integrated system and methods for processing precomputed views

Methods and apparatus for processing precomputed views for answering user queries on a database are described. In accordance with one aspect, a user database query on precomputation strategy effectiveness is responded to by defining, based upon user database query history, an analysis space consisting of a subset of all possible views for the database, and by characterizing the views in the analysis space. In accordance with a second aspect, a structure is imposed on an analysis space consisting of a subset of all possible views for the database based upon the capabilities of a query rewriting facility, and the views in the analysis space are characterized. In accordance with a third aspect, an analysis space consisting of a subset of all possible views for the database is defined, and a cost formula is applied to the analysis space based upon a user-defined subset of the data contained in the database. In accordance with a fourth aspect, an analysis space that includes a candidate view composed of a combination of two or more constituent views is defined, and the views in the analysis space are characterized.

Defining and characterizing an analysis space for precomputed views

The invention features methods and apparatus for processing precomputed views for answering user queries on a database. In accordance with one aspect, a user query on the database is analyzed, and a candidate view based upon the user query is generated.

System and method for determining and generating candidate views for a database

A system and a method maintain a precomputed view corresponding to detail data in a database server by: determining a maintenance plan to refresh the precomputed view when detail data is changed; integrating the maintenance plan with a query execution plan in the database server; and executing the query execution plan.

Growing community of inventors

Santa Cruz, CA, United States of America

William McKenna