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Chapter 11 - Introduction to Abstract Data Types (ADTs)
Chapter 11 - Introduction to Abstract Data Types (ADTs)

Cache Craftiness for Fast Multicore Key
Cache Craftiness for Fast Multicore Key

... We present Masstree, a fast key-value database designed for SMP machines. Masstree keeps all data in memory. Its main data structure is a trie-like concatenation of B+ -trees, each of which handles a fixed-length slice of a variable-length key. This structure effectively handles arbitrary-length pos ...
Doubly linked lists 1 - Richard Kay`s BCU/CEBE Page
Doubly linked lists 1 - Richard Kay`s BCU/CEBE Page

Cache Craftiness for Fast Multicore Key-Value Storage - PDOS-MIT
Cache Craftiness for Fast Multicore Key-Value Storage - PDOS-MIT

Lists
Lists

... predptr points to the node containing 17 Get a new node pointed to by newptr and store 20 in it Set the next pointer of this new node equal to the next pointer in its predecessor, thus making it point to its ...
Sidebar: Data Structures Binary Search Tree
Sidebar: Data Structures Binary Search Tree

Concurrent Cache-Oblivious B-Trees
Concurrent Cache-Oblivious B-Trees

lecture18
lecture18

Prefix Based Numbering Schemes for XML: Techniques
Prefix Based Numbering Schemes for XML: Techniques

... Therefore, we have the following property [order(y), order(y) + size(y)] ⊂ [order(x), order(x) + size(x)] if and only if y is the child of x. When inserting a child to an existing node, it is always possible to find an interval that satisfies the property above. The computation of a new interval for ...
Priority queues, binary heaps
Priority queues, binary heaps

Efficient Data Structures for Storing Partitions of Integers
Efficient Data Structures for Storing Partitions of Integers

Abstract
Abstract

... A data structure is said to be ephemeral if any changes to the structure destroy the old version. Accesses and updates can be done only on the current version. We call a data structure persistent if it supports accesses to multiple versions. The structure is partially persistent if all versions can ...
Chapter 12
Chapter 12

二叉树(英文)
二叉树(英文)

...  If the tree degenerates into a long chain, then tree search becomes the same as sequential search, doing (n)comparisons on n vertices. This is the worst case for tree search. The number of vertices between the root and the target, inclusive,is the number of comparisons that must be done to find ...
Analysis of Algorithms CS 465/665
Analysis of Algorithms CS 465/665

Introduction (CB chap. 1 & 2)
Introduction (CB chap. 1 & 2)

PPT - SEAS
PPT - SEAS

CS2006Ch04A
CS2006Ch04A

... Two objects of this class can be instantiated and chained together having the next reference of one Node object refer to the other. The second object’s next reference can refer to a third Node object, and so on, creating a linked list of Node objects. Each node will contain some data as specified by ...
data structure
data structure

ppt
ppt

CSC 263 Lecture 1
CSC 263 Lecture 1

... tree in worst case time Θ(log n) (since now the height of the tree is Θ(log n) in the worst case). Insert and Delete will also take time Θ(log n) but if we use the same routine as before, they will cause violations of one of the three Red-Black properties. For instance, if we use the regular BST Ins ...
i, j - eLisa UGM
i, j - eLisa UGM

Document
Document

1. Basic Operations (6 Points). a. To the right of the BST below, draw
1. Basic Operations (6 Points). a. To the right of the BST below, draw

heapsort_1
heapsort_1

< 1 ... 22 23 24 25 26 27 28 29 30 ... 62 >

Red–black tree

A red–black tree is a binary search tree with an extra bit of data per node, its color, which can be either red or black. The extra bit of storage ensures an approximately balanced tree by constraining how nodes are colored from any path from the root to the leaf. Thus, it is a data structure which is a type of self-balancing binary search tree.Balance is preserved by painting each node of the tree with one of two colors (typically called 'red' and 'black') in a way that satisfies certain properties, which collectively constrain how unbalanced the tree can become in the worst case. When the tree is modified, the new tree is subsequently rearranged and repainted to restore the coloring properties. The properties are designed in such a way that this rearranging and recoloring can be performed efficiently.The balancing of the tree is not perfect but it is good enough to allow it to guarantee searching in O(log n) time, where n is the total number of elements in the tree. The insertion and deletion operations, along with the tree rearrangement and recoloring, are also performed in O(log n) time.Tracking the color of each node requires only 1 bit of information per node because there are only two colors. The tree does not contain any other data specific to its being a red–black tree so its memory footprint is almost identical to a classic (uncolored) binary search tree. In many cases the additional bit of information can be stored at no additional memory cost.
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