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<blockquote data-quote="Hacker News" data-source="post: 69956" data-attributes="member: 365">Are there canonical books, resources, or readings for how to design data structures that will be primarily read and written to a disk rather than memory? Most of what I learned in school about big-O assumes that, for example, random access is O(1). However, random disk reads are really slow due to spacial locality.People who write databases obviously have solutions to this problem - for example, DuckDB is based on a number of papers that have come out over the years on this topic.If I wanted to design, ie, a tree structure which was intended to be read/written from a disk, are there general principles or patterns the have been developed to take advantage of locality of reference, minimize random reads, or decrease the overhead of writes, that I could familiarize myself with?What is the CLRS for disk?<hr />Comments URL: <a href="https://news.ycombinator.com/item?id=32965075" target="_blank">https://news.ycombinator.com/item?id=32965075</a>Points: 8# Comments: 5<a href="https://news.ycombinator.com/item?id=32965075" target="_blank">Continue reading...</a></blockquote>

[QUOTE="Hacker News, post: 69956, member: 365"] Are there canonical books, resources, or readings for how to design data structures that will be primarily read and written to a [I]disk[/I] rather than memory? Most of what I learned in school about big-O assumes that, for example, random access is O(1). However, random disk reads are really slow due to spacial locality. People who write databases obviously have solutions to this problem - for example, DuckDB is based on a number of papers that have come out over the years on this topic. If I wanted to design, ie, a tree structure which was intended to be read/written from a disk, are there general principles or patterns the have been developed to take advantage of locality of reference, minimize random reads, or decrease the overhead of writes, that I could familiarize myself with? What is the CLRS for disk? [HR][/HR] Comments URL: [URL]https://news.ycombinator.com/item?id=32965075[/URL] Points: 8 # Comments: 5 [url="https://news.ycombinator.com/item?id=32965075"]Continue reading...[/url] [/QUOTE]

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