B+ Tree
A balanced multi-way search tree data structure in which all data records are stored in leaf nodes linked in order, while non-leaf nodes store only index keys. It is widely used as an index structure in databases and file systems and supports efficient range queries and point queries.
Timeline (last 90 days)
The key reason InnoDB uses a B+ tree rather than a B tree is that B+ tree non-leaf nodes store only keys and no data, so a single page can hold more index entries, resulting in lower tree height and fewer disk IOs.
B+ trees experience frequent page splits and random I/O under heavy random write loads, leading to write amplification.
Due to frequent page splits, write amplification in B+ trees is typically above 10x; write amplification in LSM-Trees typically fluctuates between 3x and 30x.
BeOS's BFS file system has a built-in database-style metadata indexing feature using a B+ tree index structure, predating macOS Spotlight and Windows desktop search by nearly a decade.
All Facts (5)
WHERE id > maxId LIMIT N的游标分页方式（Keyset Pagination）利用主键索引的B+树有序性，时间复杂度始终为O(log N + M)
90%UnverifiedThe key reason InnoDB uses a B+ tree rather than a B tree is that B+ tree non-leaf nodes store only keys and no data, so a single page can hold more index entries, resulting in lower tree height and fewer disk IOs.
50%UnverifiedB+ trees experience frequent page splits and random I/O under heavy random write loads, leading to write amplification.
50%UnverifiedDue to frequent page splits, write amplification in B+ trees is typically above 10x; write amplification in LSM-Trees typically fluctuates between 3x and 30x.
50%UnverifiedBeOS's BFS file system has a built-in database-style metadata indexing feature using a B+ tree index structure, predating macOS Spotlight and Windows desktop search by nearly a decade.
50%