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B-TREEBinary Tree
B-TREEBalanced Multiway Search Tree
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References in periodicals archive ?
In general, the size of a single node for B-Tree and R-Tree is about 4KB, and the total size of the cache is only a few MB.
Popular document stores use B-Trees to index documents in the DBMS rather like an advanced filing cabinet.
The heaped table requires a full table scan to either locate an instance of a single key or to locate multiple instances for a range of keys; while the hashed table can efficiently locate an instance of a specific key, but still requires a full table scan to locate a range of keys; whereas a B-tree can perform both searches efficiently.
Access to a key's (transaction-time) history can be implemented by a hashing function (which must be dynamic hashing, as it has to support the addition of new keys) or a balanced multiway search tree (B-tree).
According to the skeptic, the b-tree in W2 is also identical to the a-tree in W1.
When the location anonymous server has received the request from the user, it searches the location indexes in B-tree and inserts the location information into the request queue.
Meeting the needs of 21st Century Big Data, TokuMX replaces 40-year-old B-tree indexing technology with Tokutek's patented Fractal Tree Indexing to vastly improve how MongoDB organizes and stores information.
Big tables with dynamic data, such as a fact table, rule out B-Tree indexes, as well as hashed clusters.
Inverse lists can do many things that the B-tree indexes commonly used by a relational database cannot.
Examples for such one-dimensional access methods (also called single key structures, although that term is somewhat misleading) include the B-tree [Bayer and McCreight 1972] and extendible hashing [Fagin et al.
Virtually all modern-day file search techniques use some sort of B-Tree structure.