Last month, Amazon's CTO Werner Vogels posted an article describing approaches to tolerate eventual data consistency in large-scale distributed systems.
上个月，亚马逊公司的CTOWernerVogels发表了一篇文章，描述在大型分布式系统中容忍最终数据一致性的方法。
Weak/eventual consistency happens when not all data replicas participate in the update operation and/or contacted as part of read operation.
只有部分数据副本参与更新操作，且/或作为读操作的一部分与其它副本进行联系时，就会出现弱/最终一致性。
Eventual Consistency - data is not immediately propagated across all nodes... the latency is usually around a second, but for high data sets or loads, you may experience more latency.
一致性延迟——数据不是马上传播到所有节点的……延迟一般在1秒左右，但如果数据量或者负载很大，你可能遇到更多延迟。
Eventual Consistency - data is not immediately propagated across all nodes... the latency is usually around a second, but for high data sets or loads, you may experience more latency.
一致性延迟——数据不是马上传播到所有节点的……延迟一般在1秒左右，但如果数据量或者负载很大，你可能遇到更多延迟。
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