The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 17, 2023

Filed:

Jan. 04, 2016
Applicant:

Netflix, Inc., Los Gatos, CA (US);

Inventors:

Ioannis Papapanagiotou, Campbell, CA (US);

Shailesh Birari, Campbell, CA (US);

Jason Cacciatore, Los Gatos, CA (US);

Minh Do, San Jose, CA (US);

Christos Kalantzis, San Jose, CA (US);

Assignee:

NETFLIX, INC., Los Gatos, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 16/23 (2019.01); G06F 16/11 (2019.01); G06F 16/174 (2019.01); G06F 16/178 (2019.01); G06F 11/14 (2006.01); H04L 9/40 (2022.01);
U.S. Cl.
CPC ...
G06F 16/2365 (2019.01); G06F 11/1451 (2013.01); G06F 16/128 (2019.01); G06F 16/178 (2019.01); G06F 16/1744 (2019.01); H04L 63/0428 (2013.01); G06F 2201/835 (2013.01); G06F 2201/84 (2013.01);
Abstract

In one embodiment, a data reconciliation engine works with data store nodes included in a distributed data store system to ensure consistency between the data store nodes. In operation, the data reconciliation receives a different data snapshot from each of the data store nodes. In response, the data reconciliation engine generates one or more recommendations designed to resolve inconsistencies between the data snapshots. The data reconciliation engine then transmits each recommendation to a different data store node. Because the data reconciliation engine performs many of the resource-intensive operations included in the data reconciliation process, the resources of the data store nodes may focus primarily on processing client requests instead of performing data reconciliation operations. Consequently, unlike conventional data store node based reconciliation applications, the data reconciliation engine may process large volumes of data without unacceptably increasing the time required for the distributed data store system to respond to client requests.


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