Features of Semi-Structured Data Models ■Flexible schema Wide column representation:allow each tuple to have a different set of attributes,can add new attributes at any time 。} Sparse column representation:schema has a fixed but large set of attributes,by each tuple may store only a subset Multivalued data types ·Sets,multisets E.g.,:set of interests {'basketball,'La Liga','cooking','anime',jazz') Key-value map (or just map for short) Store a set of key-value pairs E.g.,{(brand,Apple),(ID,MacBook Air),(size,13),(color,silver)) Operations on maps:put(key,value),get(key),delete(key) ·,Arrays Widely used for scientific and monitoring applications Database System Concepts-7th Edition 8.4 ©Silberscha乜，Korth and SudarshanDatabase System Concepts - 7 8.4 ©Silberschatz, Korth and Sudarshan th Edition Features of Semi-Structured Data Models ▪ Flexible schema • Wide column representation: allow each tuple to have a different set of attributes, can add new attributes at any time • Sparse column representation: schema has a fixed but large set of attributes, by each tuple may store only a subset ▪ Multivalued data types • Sets, multisets ▪ E.g.,: set of interests {‘basketball, ‘La Liga’, ‘cooking’, ‘anime’, ‘jazz’} • Key-value map (or just map for short) ▪ Store a set of key-value pairs ▪ E.g., {(brand, Apple), (ID, MacBook Air), (size, 13), (color, silver)} ▪ Operations on maps: put(key, value), get(key), delete(key) • , Arrays ▪ Widely used for scientific and monitoring applications