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.
Automated Discovery Of Template Patterns Based On Received Server Requests
Konstantinos Morfonios - Foster City CA, US Leonidas Galanis - San Jose CA, US Neoklis Polyzotis - Santa Cruz CA, US Karl Dias - Foster City CA, US
Assignee:
ORACLE INTERNATIONAL CORPORATION - Redwood Shores CA
International Classification:
G06F 15/173
US Classification:
709224
Abstract:
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.
Vahit Hakan Hacigumus - San Jose CA, US Jagan Sankaranarayanan - Santa Clara CA, US Jeffrey LeFevre - Santa Cruz CA, US Junichi Tatemura - Cupertino CA, US Neoklis Polyzotis - Cupertino CA, US
Assignee:
NEC LABORATORIES AMERICA, INC. - Princeton NJ
International Classification:
G06F 17/30
US Classification:
707718, 707721, 707719
Abstract:
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.
- Mountain View CA, US Steven Euijong Whang - Mountain View CA, US Natalya Fridman Noy - San Carlos CA, US Sudip Roy - San Jose CA, US Neoklis Polyzotis - San Jose CA, US Alon Yitzchak Halevy - Los Altos CA, US Christopher Olston - Los Altos CA, US
International Classification:
G06F 17/30 G06F 21/62
Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a catalog for multiple datasets, the method comprising accessing multiple extant data sets, the extant data sets including data sets that are independently generated and structurally dissimilar; organizing the data sets into collections, each data set in each collection belonging to the collection based on collection data associated with the data set; for each collection of data sets: determining, from a subset of the data sets that belong to the collection, metadata that describe the data sets that belong to the collection, wherein the metadata does not include the collection data, and attributing, to other data sets in the collection, the metadata determined from the subset of data sets; and generating, from the collections of data sets and the determined metadata, a catalog for the multiple datasets.
System For Multi-Store Analytics Execution Environments With Storage Constraints
- Princeton NJ, US Jagan Sankaranarayanan - Santa Clara CA, US Jeffrey Paul LeFevre - Santa Cruz CA, US Junichi Tatemura - Cupertino CA, US Neoklis Polyzotis - Santa Cruz CA, US
Assignee:
NEC Laboratories America, Inc. - Princeton NJ
International Classification:
G06F 17/30
US Classification:
707718
Abstract:
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.
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Neoklis Polyzotis
Lived:
Athens, Greece Madison, WI Paris, France Santa Cruz, CA Lausanne Madison, NJ
Work:
UC Santa Cruz - Associate Professor UW at Madison INRIA
Education:
University of Wisconsin-Madison - Computer Sciences, National Technical University of Athens - Elec. and Computer Engineering
Neoklis Polyzotis
Work:
UC Santa Cruz - Assoc Professor
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