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Techniques for performing data reconciliation in distributed data store systems

机译:在分布式数据存储系统中执行数据协调的技术

摘要

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.
机译:在一个实施例中,数据协调引擎与包括在分布式数据存储系统中的数据存储节点一起工作,以确保数据存储节点之间的一致性。在操作中,数据协调从每个数据存储节点接收不同的数据快照。作为响应,数据协调引擎会生成一个或多个建议,这些建议旨在解决数据快照之间的不一致问题。然后,数据协调引擎将每个建议发送到不同的数据存储节点。因为数据协调引擎执行数据协调过程中包括的许多资源密集型操作,所以数据存储节点的资源可能主要集中于处理客户端请求,而不是执行数据协调操作。因此,与传统的基于数据存储节点的对帐应用程序不同,数据对帐引擎可以处理大量数据,而不会不当地增加分布式数据存储系统响应客户端请求所需的时间。

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