Nec Corporation

Oracle International Corporation

Nec Laboratories America, Inc.

Teradata Us, Inc.

Neoklis Polyzotis

Vahit Hakan Hacigumus

Junichi Tatemura

Jagan Sankaranarayanan

Jeffrey LeFevre

Karl Dias

Leonidas Galanis

George Candea

Konstantinos Morfonios

Systems and methods are disclosed for managing a multi-store execution environment by applying opportunistic materialized views to improve workload performance and executing a plan on multiple database engines to increase query processing speed by leveraging unique capabilities of each engine by enabling stages of a query to execute on multiple engines, and by moving materialized views across engines.

System for multi-store analytics execution environments with storage constraints

A system for evolutionary analytics supports three dimensions (analytical workflows, the users, and the data) by rewriting workflows to be more efficient by using answers materialized as part of previous workflow execution runs in the system.

System for evolutionary analytics

Described herein are methods for determining patterns based on requests received by a server. Based on the determined patterns, insight into the types of requests received by the server can be gained. Additionally, performance statistics and query statistics can be aggregated in a useful way. For example, performance statistics may be summarized for each determined pattern. One technique for determining patterns includes determining a sequence of template identifiers identifying templates that correspond to sub-sequences of requests in a sequence of server requests. A model may be created based on the sequence of template identifiers. Based on the model, template patterns may be determined. Template patterns may further be grouped into pattern clusters.

Automated discovery of template patterns based on received server requests

In one embodiment, a method includes concurrently executing a set of multiple queries, through a processor, to improve a resource usage within a data warehouse system. The method also includes permitting a group of users of the data warehouse system to simultaneously run a set of queries. In addition, the method includes applying a high-concurrency query operator to continuously optimize a large number of concurrent queries for a set of highly concurrent dynamic workloads.

High-concurrency query operator and method

Growing community of inventors

Santa Cruz, CA, United States of America

Neoklis Polyzotis