Setting Up a Hot Standby Database
... • Can control checkpoint frequency several ways: via size of redo logs, and parameters such as: – FAST_START_IO_TARGET – LOG_CHECKPOINT_INTERVAL. ...
... • Can control checkpoint frequency several ways: via size of redo logs, and parameters such as: – FAST_START_IO_TARGET – LOG_CHECKPOINT_INTERVAL. ...
Chapter 9
... If (first > last) return false Else Set middle to (first + last)/2 Set result to item.compareTo(list[middle]) If (result is equal to 0) return true Else If (result < 0) Binary Search (first, middle - 1) Else Binary Search (middle + 1, last) ...
... If (first > last) return false Else Set middle to (first + last)/2 Set result to item.compareTo(list[middle]) If (result is equal to 0) return true Else If (result < 0) Binary Search (first, middle - 1) Else Binary Search (middle + 1, last) ...
ch12
... key value Ki, or to a bucket of pointers to file records, each record having search-key value Ki. Only need bucket structure if search-key does not form a primary key. If Li, Lj are leaf nodes and i < j, Li’s search-key values are less than Lj’s ...
... key value Ki, or to a bucket of pointers to file records, each record having search-key value Ki. Only need bucket structure if search-key does not form a primary key. If Li, Lj are leaf nodes and i < j, Li’s search-key values are less than Lj’s ...
Binary Search Trees
... • For every node X in the tree, the values of all the keys in the left subtree are smaller than the key in X and the values of all the keys in the right subtree are larger than the key in X. • Duplicates are not allowed. • An inorder traversal yields the items in sorted order. ...
... • For every node X in the tree, the values of all the keys in the left subtree are smaller than the key in X and the values of all the keys in the right subtree are larger than the key in X. • Duplicates are not allowed. • An inorder traversal yields the items in sorted order. ...
slides04
... Remove element from middle of a collection, maintain order, no shifting. Add an element in the middle, no shifting What’s the problem with a vector (array)? Emacs visits several files, internally keeps a linked-list of buffers Naively keep characters in a linked list, but in practice too much ...
... Remove element from middle of a collection, maintain order, no shifting. Add an element in the middle, no shifting What’s the problem with a vector (array)? Emacs visits several files, internally keeps a linked-list of buffers Naively keep characters in a linked list, but in practice too much ...
Chapter 4 Index Structures
... B-tree of Section 4.3, where we need to know the location of only a single root block. ...
... B-tree of Section 4.3, where we need to know the location of only a single root block. ...
Strict Fibonacci Heaps
... that matches the time bounds of Fibonacci heaps in the worst case on a pointer machine, i.e. we achieve a linear space data structure supporting make-heap, insert, find-min, meld and decrease-key in worst-case O(1) time, and delete and delete-min in worst-case O(lg n) time. This adds the final step ...
... that matches the time bounds of Fibonacci heaps in the worst case on a pointer machine, i.e. we achieve a linear space data structure supporting make-heap, insert, find-min, meld and decrease-key in worst-case O(1) time, and delete and delete-min in worst-case O(lg n) time. This adds the final step ...
Spatial Access Methods
... only the following characteristic families are presented: Quadtree, Grid based methods, and R-tree (Sections 5-7). Special attention is paid to spatial access methods taking multiple scales into account (Section 8). Besides the theory of spatial access methods, the issue of using them in a database ...
... only the following characteristic families are presented: Quadtree, Grid based methods, and R-tree (Sections 5-7). Special attention is paid to spatial access methods taking multiple scales into account (Section 8). Besides the theory of spatial access methods, the issue of using them in a database ...
Linked Lists, stacks and queues
... – Static size: a size must be established when the array is created, and cannot be changed later. The main problems it poses are: • Inefficient use of memory when more positions than needed are reserved, because of being the array sized for the worst case • It may happen at run-time that more positi ...
... – Static size: a size must be established when the array is created, and cannot be changed later. The main problems it poses are: • Inefficient use of memory when more positions than needed are reserved, because of being the array sized for the worst case • It may happen at run-time that more positi ...
iterable - Dave Reed
... LinkedList implementation we could implement the LinkedList class using a singly-linked list however, the one-way links are limiting to insert/delete from an interior location, really need a reference to the previous location e.g., remove(item) must traverse and keep reference to previous node, ...
... LinkedList implementation we could implement the LinkedList class using a singly-linked list however, the one-way links are limiting to insert/delete from an interior location, really need a reference to the previous location e.g., remove(item) must traverse and keep reference to previous node, ...
Data Structures for Disjoint Sets
... In this lecture, we describe some methods for maintaining a collection of disjoint sets. Each set is represented as a pointer-based data structure, with one node per element. We will refer to the elements as either ‘objects’ or ‘nodes’, depending on whether we want to emphasize the set abstraction o ...
... In this lecture, we describe some methods for maintaining a collection of disjoint sets. Each set is represented as a pointer-based data structure, with one node per element. We will refer to the elements as either ‘objects’ or ‘nodes’, depending on whether we want to emphasize the set abstraction o ...
FileSystemImplementation
... Thus, a file of size 18,000 bytes would have two 8K blocks and one 2K fragment (which would not be filled completely). ...
... Thus, a file of size 18,000 bytes would have two 8K blocks and one 2K fragment (which would not be filled completely). ...
B-tree
In computer science, a B-tree is a tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree is a generalization of a binary search tree in that a node can have more than two children (Comer 1979, p. 123). Unlike self-balancing binary search trees, the B-tree is optimized for systems that read and write large blocks of data. B-trees are a good example of a data structure for external memory. It is commonly used in databases and filesystems.