Chapter 17: Indexing Structures for Files and Indexing Structures for
... 60‐315 Dr. C. I. Ezeife (2017) with Figures and some materials from Elmasri & Navathe, 7th Ed ...
... 60‐315 Dr. C. I. Ezeife (2017) with Figures and some materials from Elmasri & Navathe, 7th Ed ...
Binary Tree
... or if num is present, it returns NULL. Otherwise, it returns a pointer to the last node of the tree that was encountered during the search. The new element is to be inserted as a child of this node. Deletion from a Binary Search Tree Deletion of a leaf node is easy. For example, if a leaf node is ...
... or if num is present, it returns NULL. Otherwise, it returns a pointer to the last node of the tree that was encountered during the search. The new element is to be inserted as a child of this node. Deletion from a Binary Search Tree Deletion of a leaf node is easy. For example, if a leaf node is ...
A B-tree - UCSD CSE
... • Insert and delete are more involved; they modify the tree, and this must be done in a way to keep the B-tree properties invariant • In a B+ tree with parameters M,L these must be invariant: • Data records are stored only in the leaves • A leaf always holds between ceil(L/2.) and L data records (in ...
... • Insert and delete are more involved; they modify the tree, and this must be done in a way to keep the B-tree properties invariant • In a B+ tree with parameters M,L these must be invariant: • Data records are stored only in the leaves • A leaf always holds between ceil(L/2.) and L data records (in ...
Data Structures So Far
... remove(e): Remove from P and return entry e. replaceKey(e,k): Replace with k and return the old key; an error condition occurs if k is invalid (that is, k cannot be compared with other keys). replaceValue(e,x): Replace with x and return the old ...
... remove(e): Remove from P and return entry e. replaceKey(e,k): Replace with k and return the old key; an error condition occurs if k is invalid (that is, k cannot be compared with other keys). replaceValue(e,x): Replace with x and return the old ...
Introduction: the standard external
... leaf (assuming there is more than one) stores between B/2 and B objects. Note that the data associated with any node in the B-tree fits into a single block.9 Each internal node stores a sorted sequence of search keys; the number of search keys is one less than the number of children. The r search ke ...
... leaf (assuming there is more than one) stores between B/2 and B objects. Note that the data associated with any node in the B-tree fits into a single block.9 Each internal node stores a sorted sequence of search keys; the number of search keys is one less than the number of children. The r search ke ...
Complete Binary Trees
... see details of how the An array of data entries are stored. We don't care what's in this part of the array. ...
... see details of how the An array of data entries are stored. We don't care what's in this part of the array. ...
Starting Out with C++, 3 rd Edition
... • Deleting a leaf node is easy. • We simply find its parent and set the child pointer that links to it to NULL, and then free the node's memory. • But what if we want to delete a node that has child nodes? We must delete the node while at the same time preserving the subtrees that the node links to. ...
... • Deleting a leaf node is easy. • We simply find its parent and set the child pointer that links to it to NULL, and then free the node's memory. • But what if we want to delete a node that has child nodes? We must delete the node while at the same time preserving the subtrees that the node links to. ...
Fundamental Data Structures
... Forests: a graph that has no cycles but is not necessarily connected. Properties of trees |E| = |V| - 1 For every two vertices in a tree there always exists exactly one simple path from one of these vertices to the other. Why? Rooted trees:The above property makes it possible to select an ...
... Forests: a graph that has no cycles but is not necessarily connected. Properties of trees |E| = |V| - 1 For every two vertices in a tree there always exists exactly one simple path from one of these vertices to the other. Why? Rooted trees:The above property makes it possible to select an ...
DISJOINT SETS AND UNION/FIND ALGORITHM
... related. This is done by performing finds on both a and b and checking whether they are in the same equivalence class. If they are not, then we apply union. This operation merges the two equivalence classes containing a and b into a new equivalence class. ...
... related. This is done by performing finds on both a and b and checking whether they are in the same equivalence class. If they are not, then we apply union. This operation merges the two equivalence classes containing a and b into a new equivalence class. ...
thm07 - augmenting ds p2
... Case 2: We go left, low[i] ≤ max-y[left[p]] If T[left[p]] does not contain an interval i‘ that overlaps i, then T[right[p]] cannot contain such an interval as well! ...
... Case 2: We go left, low[i] ≤ max-y[left[p]] If T[left[p]] does not contain an interval i‘ that overlaps i, then T[right[p]] cannot contain such an interval as well! ...
Quadtree
A quadtree is a tree data structure in which each internal node has exactly four children. Quadtrees are most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions. The regions may be square or rectangular, or may have arbitrary shapes. This data structure was named a quadtree by Raphael Finkel and J.L. Bentley in 1974. A similar partitioning is also known as a Q-tree. All forms of quadtrees share some common features: They decompose space into adaptable cells Each cell (or bucket) has a maximum capacity. When maximum capacity is reached, the bucket splits The tree directory follows the spatial decomposition of the quadtree.