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US Patent 10366111 Scalable distributed computations utilizing multiple distinct computational frameworks

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10366111
Date of Patent
July 30, 2019
Patent Application Number
15683243
Date Filed
August 22, 2017
Patent Citations
‌
US Patent 10015106 Multi-cluster distributed data processing platform
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US Patent 10127352 Distributed data processing platform for metagenomic monitoring and characterization
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US Patent 10122806 Distributed analytics platform
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US Patent 10111492 Article of footwear with dynamic edge cavity midsole
Patent Citations Received
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US Patent 11854707 Distributed data analytics
7
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US Patent 11749412 Distributed data analytics
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US Patent 11314430 Reading data in sub-blocks using data state information
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US Patent 11461372 Data clustering in logic devices using unsupervised learning
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US Patent 11556897 Job-post budget recommendation based on performance
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US Patent 11563805 Method, apparatus, client terminal, and server for data processing
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US Patent 11062084 Generating diverse smart replies using synonym hierarchy
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US Patent 11658926 Generating smart replies involving image files
17
...
Patent Primary Examiner
‌
Shean Tokuta
Patent abstract

An apparatus in one embodiment comprises at least one processing device having a processor coupled to a memory. The processing device is configured to initiate distributed computations across a plurality of data processing clusters associated with respective data zones, and to combine local processing results of the distributed computations from respective ones of the data processing clusters. Each of the data processing clusters is configured to process data from a data source of the corresponding data zone using a local data structure and an associated computational framework of that data processing cluster. A first one of data processing clusters utilizes a first local data structure configured to support a first computational framework, and at least a second one of the data processing clusters utilizes a second local data structure different than the first local data structure and configured to support a second computational framework different than the first computational framework.

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