论文标题
优化杜鹃滤波器，以获得高爆发耐受性，低潜伏期和高吞吐量
Optimizing Cuckoo Filter for high burst tolerance,low latency, and high throughput
论文作者
论文摘要
在本文中，我们提出了用于会员测试的杜鹃过滤器的实现，该过滤器针对在高工作负载中运行的分布式数据存储进行了优化。在大型数据库中，使用传统搜索方法的查询效率低下。为了达到最佳性能，有必要使用概率数据结构来测试给定密钥的成员资格，以在查询数据时获得误报。广泛使用的Bloom过滤器可用于此功能，但是它们具有限制，例如对删除的支持不支持。为了改进这一点，我们使用了杜鹃滤光片的修改版本，该版本提供了更好的摊销时间供搜索，较少的误报。
In this paper, we present an implementation of a cuckoo filter for membership testing, optimized for distributed data stores operating in high workloads. In large databases, querying becomes inefficient using traditional search methods. To achieve optimal performance it is necessary to use probabilistic data structures to test the membership of a given key, at the cost of getting false positives while querying data. The widely used bloom filters can be used for this, but they have limitations like no support for deletes. To improve upon this we use a modified version of the cuckoo filter that gives better amortized times for search, with less false positives.
