The Skiplist, or skip list, originally designed as an in-memory data structure, has attracted a lot of attention in recent years as a main-memory component in many NoSQL, cloud-based, and big data systems. Unlike the B-tree, the skiplist does not need complex rebalancing mechanisms, but it still shows expected logarithmic performance. It supports a variety of operations, including insert, point read, and range queries. To make the skiplist more versatile, many optimizations have been applied to its node structure, construction algorithm, list structure, concurrent access, to name a few. Many variants of the skiplist have been proposed and experimented with, in many big-data system scenarios. In addition to being a main-memory component, the skiplist also serves as a core index in systems to address problems including write amplification, write stalls, sorting, range query processing, etc. In this tutorial, we present a comprehensive overview of the skiplist, its variants, optimizations, and various use cases of how big data and NoSQL systems make use of skiplists. Throughout this tutorial, we demonstrate the advantages of using a skiplist or skiplist-like structures in modern data systems.
翻译:跳跃表作为一种内存数据结构,近年来已经受到了很多关注,成为了许多NoSQL、基于云的和大数据系统中的主要内存组件。跳跃表与B树不同,不需要复杂的再平衡机制,但仍展示出预期的对数性能。它支持插入、点读和范围查询等各种操作。为了使跳跃表更加通用,已经对其节点结构、构建算法、列表结构、并发访问等进行了许多优化。跳跃表的很多变种已经在很多大数据系统场景下被提出和实验。除了作为主内存组件之外,跳跃表还作为核心索引在处理写放大、写等待、排序、范围查询等问题的系统中发挥作用。在本教程中,我们全面介绍跳跃表、其变种、优化以及大数据和NoSQL系统如何使用跳跃表的各种用例。在整个教程中,我们展示了现代数据系统中使用跳跃表或类似结构的优点。