{"id":153346,"date":"1987-12-01T00:00:00","date_gmt":"1987-12-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/a-simple-and-efficient-implementation-for-small-databases\/"},"modified":"2018-10-16T20:11:05","modified_gmt":"2018-10-17T03:11:05","slug":"a-simple-and-efficient-implementation-for-small-databases","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/a-simple-and-efficient-implementation-for-small-databases\/","title":{"rendered":"A Simple and Efficient Implementation for Small Databases"},"content":{"rendered":"
This paper describes a technique for implementing the sort of small databases that frequently occur in the design of operating systems and distributed systems. We take advantage of the existence of very large virtual memories, and quite large real memories, to make the technique feasible. We maintain the database as a strongly typed data structure in virtual memory, record updates incrementally on disk in a log and occasionally make a checkpoint of the entire database. We recover from crashes by restoring the database from an old checkpoint then replaying the log. We use existing packages to convert between strongly typed data objects and their disk representations, and to communicate strongly typed data across the network (using remote procedure calls). Our memory is managed entirely by a general purpose allocator and garbage collector.This scheme has been used to implement a name server for a distributed system. The resulting implementation has the desirable property of being simultaneously simple, efficient and reliable.<\/p>\n","protected":false},"excerpt":{"rendered":"
This paper describes a technique for implementing the sort of small databases that frequently occur in the design of operating systems and distributed systems. We take advantage of the existence of very large virtual memories, and quite large real memories, to make the technique feasible. We maintain the database as a strongly typed data structure […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13563],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-153346","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of the 11th ACM Symposium on Operating System 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