Persistent data structures. Jun 13, 2025 · Dive into the world of persistent data structures and learn about their concepts, benefits, and challenges. A persistent data structure is a data structure that preserves the previous versions of itself when modified, allowing access to any historical version. The course covers the main persistent data structures, their design principles, complexity analysis and applications in functional programming. Learn about data structures that always preserve the previous version of themselves when they are modified. Understand how they can be used to improve code quality and simplify development. Persistent Data Structures 6. . Aug 24, 2024 · This post delves into the theory and practice of persistent data structures, including their use in database systems and other applications requiring efficient storage and retrieval of large datasets. Description: “Persistence”–remembering all past versions of a data structure (“partial persistence”), being able to modify them—forking off new ones (“full persistence”), and merging different versions into one (“confluent persistence”). The obvious way to provide persistence is to make a copy of the data structure each time it is changed. Learn about persistent data structures, which retain the complete history of the data and can be updated efficiently. With this type of persistence the versions don't form a simple linear path - they form a version tree. Learn how to design and implement persistent data structures in OCaml, such as stacks, queues, search trees, hash tables, and sets. Mar 17, 2025 · Examples of Persistent Data Structures: Persistent Arrays: Persistent arrays provide a way to efficiently update and access previous versions of an array. Jul 23, 2025 · All the data structures discussed here so far are non-persistent (or ephemeral). The structure employs techniques like path copying to ensure that modifications result in minimal copying, making it suitable for scenarios where large datasets need versioning. The first lecture covers persistent data structures. Explore the benefits and challenges of immutability, undo, and concurrency with persistent data. Key takeaways include understanding the concept of persistence, creating persistent data structures in popular programming languages, and implementing efficient storage and retrieval algorithms. 854 Notes #2 David Karger 1 Persistent Data Structures Sarnak and Tarjan, "Planar Point Location using persistent trees", Communications of the ACM 29 (1986) 669–679 "Making Data Structures Persistent" by Driscoll, Sarnak, Sleator and Tarjan Journal of Computer and System Sciences 38 (1) 1989 Idea: be able to query and/or modify past versions of data structure Full persistence lets you make queries and modifications to all previous versions of the data structure. Cần hiểu rằng Persistent Data Structures không phải là một loại CTDL mới. Compare different techniques for creating and accessing persistent data structures, such as copy-on-write, fat node, path copying and combination. A persistent data structure is a data structure that always preserves the previous version of itself when it is modified. See examples, references, and open problems for each level of persistence. Learn about different levels of persistence for data structures, such as partial, full, confluent, and functional, and how to achieve them with constant-factor overhead. First we introduce the pointer machine model, and four levels of persistence: partial, full, confluent, and functional. In other words, once a change is made to the structure, both the original and modified versions remain accessible. Trong một số cách cài đặt, Persistent Data Structures còn có thể cho phép thay version hiện tại của CTDL thành một version trong quá khứ (phần 2 mô tả phương pháp cài đặt có thể thực hiện được thao tác này).
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