Infobright Inc.

Security On-demand, Inc.

Arkadiusz G Wojna

Dominik A Slezak

Jakub Wroblewski

Marcin Kowalski

Graham Toppin

Victoria K Eastwood

Cas Kazimierz Apanowicz

Piotr D Synak

Marcin Wojnarski

Richard Glick

Pawel Betlinski

Agnieszka Chadzynska-Krasowska

Janusz Borkowski

Piotr Synak

Joel Alan Holland

Embodiments may provide methods and systems for intelligent capture and fast transformation of granulated data summaries. An engine may be used to transform input data summaries into result sets representing query outcomes. The data summaries contain enough knowledge about the original data to accurately perform operations on the summaries without needing to access the original data. In an embodiment, the contents of data summaries are accessible via an SQL approximate engine which retrieves summaries stored on disk and utilizes them for its operations. Alternatively, the contents of data summaries are accessible via virtual tables which give users direct access to the summary contents and allow for the creation and implementation of algorithms to work with the data summaries independently from the SQL approximate engine.

Systems and methods for intelligent capture and fast transformations of granulated data summaries in database engines

In a method for storing data in a relational database system using a processor, a collection of values is assigned to a structure dictionary, each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection. and the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, automatic detection of frequencies of values occurring in data, analysis of a history of queries, and predetermined information about structures relevant to data content that is stored in the system. For each structure, forming a structure match list from ordinal numbers of values matching the structure, and a structure sub-collection from values matching the structure, using the processor. An outlier match list is formed from ordinal numbers of values that are not null and do not match any structure in the structure dictionary, and an outlier sub-collection is formed from values that are not null and do not match any structure in the structure dictionary. The collection of values is stored in the relational database in a form of structure match lists, structure sub-collections, outlier match list and outlier sub-collection.

System and method for storing data in a relational database

A system and method of processing a data query in a data processing system is provided. The data in the data processing system includes a plurality of individual data elements. The data elements are grouped and stored in at least one data unit. The information about the at least one data unit is gathered and stored in at least one information unit. The method comprises receiving the data query to be executed; using the information in the at least one information unit to optimize and execute the query; resolving the data query; and returning results of the data query for use by the data processing system.

Method and system for storing, organizing and processing data in a relational database

A method for applying adaptive data compression in a relational database system using a filter cascade having at least one compression filter stage in the filter cascade. The method comprises applying a data filter associated with the compression filter stage to the data input to produce reconstruction information and filtered data, then compressing the reconstruction information to be included in a filter stream. The filtered data is provided as a compression filter stage output. The method may comprise evaluating whether the compression filter stage provides improved compression compared to the data input. The filter stage output may be used as the input of a subsequent compression filter stage.

Method and system for data compression in a relational database

In a method for managing metadata in a relational database system using a processor, the metadata is created in a form of rough values corresponding to collections of values, wherein each rough value represents summarized information about values, the values are elements of the corresponding collection of values, and each rough value is substantially smaller than the corresponding collection of values. A collection of values is assigned to a structure dictionary, wherein each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection, and wherein the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, and predetermined information about structures relevant to data content that is stored in the system. A match granule is formed, and for each structure in the structure dictionary, a structure granule is formed. Information represented by the match granule and the structure granules is summarized to form a rough value.

System and method for managing metadata in a relational database

In a method for storing data in a relational database system using a processor, a collection of values is assigned to a structure dictionary, wherein each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection, and wherein the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, and predetermined information about structures relevant to data content that is stored in the system. For each structure in the structure dictionary, a structure match list is formed from ordinal numbers of values matching the structure, and a structure sub-collection from values matching the structure, using the processor. An outlier match list is formed from ordinal numbers of values that are not null and do not match any structure in the structure dictionary, and an outlier sub-collection from values that are not null and do not match any structure in the structure dictionary. The collection of values is stored in the relational database in a form of structure match lists, structure sub-collections, outlier match list and outlier sub-collection.

Growing community of inventors

Warszawa, Poland

Arkadiusz G Wojna