These are the lecture notes for the course CM0622 - Algorithms for Massive Data, Ca' Foscari University of Venice. The goal of this course is to introduce algorithmic techniques for dealing with massive data: data so large that it does not fit in the computer's memory. Broadly speaking, there are two main solutions to deal with massive data: (lossless) compressed data structures and (lossy) data sketches. These notes cover the latter topic: probabilistic filters, sketching under various metrics, Locality Sensitive Hashing, nearest neighbour search, algorithms on streams (pattern matching, counting).

翻译：本讲义为威尼斯大学CM0622课程"大规模数据处理算法"的课堂笔记。该课程旨在介绍处理海量数据的算法技术：当数据规模超出计算机内存容量时的应对方案。广义而言，处理大规模数据主要有两种方法：（无损）压缩数据结构与（有损）数据草图。本笔记聚焦后者，涵盖概率过滤器、多度量体系下的草图技术、局部敏感哈希（Locality Sensitive Hashing）、最近邻搜索、流式算法（模式匹配、计数）等内容。