Microsoft Technology Licensing, LLC

Wisconsin Alumni Research Foundation

Quip Incorporated

Raghu Ramakrishnan

Jonathan David Goldstein

Philip Alan Bernstein

Navin Kabra

Hongfei Guo

Alan David Fekete

Venkatesh Ganti

Per-Åke Larson

Miron Livny

Johannes Ernst Gehrke

Tian Zhang

Vuk Ercegovac

Uri Shaft

Currency and consistency requirements are specified as part of a query against a database that may contain replicated data that is updated asynchronously and therefore may not be completely up to date. The database system constructs query execution plans that include an input selection operator that verifies the currency of a replica and selects a subplan using the replica for execution only when the replica meets the query's currency constraints. It checks possible query execution plans at construction time against the query's consistency constraints and any plans that may produce a result not meeting the consistency constraints are rejected. In this way, the query result is guaranteed to satisfy the query's currency and consistency requirements.

Enforcing currency and consistency constraints in database query processing

The subject invention pertains to transaction processing systems and methodologies that allows update transactions to read stale data copies and update a data store therewith. Each transactional operation, including a read, can carry or be associated with one or more freshness constraints or tests that specify how fresh a data copy must be in order to be read. More specifically, the subject invention provides systems and methods that extend transactions and serializability to account for out-of-date reads that are justified by freshness requirements.

Relaxed currency constraints

A unified database/text retrieval system converts exact database type queries into text inclusion type queries suitable for text retrieval systems through the use of pseudo keywords. Boolean combination of the text inclusion type query elements may be readily manipulated for optimization and applied to a unified index for rapid search results. Absolute relevance values and relevance multiplier values may be added to the query elements to provide a relevance-based sorting not only of text but also of exact match type search results. Relevance values may be deduced automatically from a variety of sources.

Unified database and text retrieval system

A method of creating and updating a binary decision tree from training databases that cannot be fit in high speed solid state memory is provided in which a subset of the training database which can fit into high speed memory is used to create a statistically good estimate of the binary decision tree desired. This statistically good estimate is used to review the entire training database in as little as one sequential scan to collect statistics necessary to verify the accuracy of the binary decision tree and to refine the binary decision tree to be identical to that which would be obtained by a full analysis of the training database.

Method of constructing binary decision trees with reduced memory access

Multi-dimensional data contained in very large databases is efficiently and accurately clustered to determine patterns therein and extract useful information from such patterns. Conventional computer processors may be used which have limited memory capacity and conventional operating speed, allowing massive data sets to be processed in a reasonable time and with reasonable computer resources. The clustering process is organized using a clustering feature tree structure wherein each clustering feature comprises the number of data points in the cluster, the linear sum of the data points in the cluster, and the square sum of the data points in the cluster. A dense region of data points is treated collectively as a single cluster, and points in sparsely occupied regions can be treated as outliers and removed from the clustering feature tree. The clustering can be carried out continuously with new data points being received and processed, and with the clustering feature tree being restructured as necessary to accommodate the information from the newly received data points.

Method and system for data clustering for very large databases

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Madison, WI, United States of America

Raghu Ramakrishnan