2–3–4 tree - Wikipedia
In computer science, a 2–3–4 tree (also called a 2–4 tree) is a self-balancing data structure that can be used to implement dictionaries. The numbers mean a tree where every node with children (internal node) has either two, three, or four child nodes: a 2-node has one data element, and if internal has two child nodes; a 3-node has two data elements, and if internal has three child nodes; a 4-node
Robert Sedgewick - Robert Sedgewick
Robert Sedgewick is the founding chair and the William O. Baker Professor in the Department of Computer Science at Princeton University. He was a member of the board of directors of Adobe Systems from 1990 to 2016, served on the faculty at Brown University from 1975 to 1985, and has held visiting research positions at Xerox PARC, IDA, and INRIA. His research expertise is in algorithm science, data
B-tree - Wikipedia
In computer science, a B-tree is a self-balancing tree data structure that maintains sorted data and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree generalizes the binary search tree, allowing for nodes with more than two children.[2] Unlike other self-balancing binary search trees, the B-tree is well suited for storage systems that read and write rel
2–3 tree - Wikipedia
In computer science, a 2–3 tree is a tree data structure, where every node with children (internal node) has either two children (2-node) and one data element or three children (3-node) and two data elements. A 2–3 tree is a B-tree of order 3.[1] Nodes on the outside of the tree (leaf nodes) have no children and one or two data elements.[2][3] 2–3 trees were invented by John Hopcroft in 1970.[4] 2
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Btrees are the new black - Me
Btrees are the new black | Hacker News
llrb package - github.com/petar/GoLLRB/llrb - Go Packages
GitHub - petar/GoLLRB: A Left-Leaning Red-Black (LLRB) implementation of balanced binary search trees for Google Go
B-Tree Visualization
How do I derive the best and worst case height of a B-Tree?
Why is b-tree search O(log n)?
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