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（skiplist）最初被设计为一种内存数据结构，近年来作为众多NoSQL、云原生及大数据系统中的内存组件备受关注。与B树不同，跳跃表无需复杂的重平衡机制，但依然展现出预期中的对数级性能。它支持插入、点读取和范围查询等多种操作。为提升跳跃表的通用性，研究者对其节点结构、构建算法、链表结构及并发访问等方面进行了诸多优化。在大数据系统场景中，跳跃表的多种变体已被提出并试验。除作为内存组件外，跳跃表还作为核心索引服务于写放大、写停顿、排序、范围查询处理等问题。本教程将全面概述跳跃表及其变体、优化方法，以及大数据与NoSQL系统利用跳跃表的各类应用场景。通过本教程，我们将展示在现代数据系统中使用跳跃表或类跳跃表结构的优势。