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US Patent 10999353 Beacon-based distributed data processing platform

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Is a
Patent
Patent
0

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
0
Patent Number
109993530
Patent Inventor Names
Patricia Gomes Soares Florissi0
Date of Patent
May 4, 2021
0
Patent Application Number
162957300
Date Filed
March 7, 2019
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Patent Citations
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US Patent 10114923 Metagenomics-based biological surveillance system using big data profiles
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US Patent 10122806 Distributed analytics platform
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US Patent 10127352 Distributed data processing platform for metagenomic monitoring and characterization
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US Patent 10148736 Executing parallel jobs with message passing on compute clusters
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US Patent 10250708 High performance distributed system of record
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US Patent 10270707 Distributed catalog service for multi-cluster data processing platform
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US Patent 10277668 Beacon-based distributed data processing platform
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US Patent 10311363 Reasoning on data model for disease monitoring, characterization and investigation
...
Patent Citations Received
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US Patent 11854707 Distributed data analytics
0
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US Patent 11749412 Distributed data analytics
Patent Primary Examiner
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Thuong Nguyen
0
Patent abstract

A method comprises initiating a first application in a first one of a plurality of distributed processing nodes, and responsive to initiation of the first application, identifying a plurality of beacon entities to be contacted in conjunction with execution of at least a portion of the first application. The method also comprises, for each of at least a subset of the identified beacon entities, initiating an additional application in an additional one of the plurality of distributed processing nodes. The method further comprises aggregating processing results from the first and one or more additional processing nodes, and providing the aggregated processing results to a client. The plurality of distributed processing nodes may comprise a plurality of YARN clusters associated with respective data zones, with each of the clusters being configured to perform processing operations utilizing local data resources locally accessible within its corresponding data zone.

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