Fast and compact hash tables for integer keys
... strings and integers but requires a form of collision resolution to resolve cases where two or more keys are hashed to the same slot. The simplest and most effective collision resolution scheme for when the number of keys is not known in advance is the use of linked lists. This forms a chaining hash ...
... strings and integers but requires a form of collision resolution to resolve cases where two or more keys are hashed to the same slot. The simplest and most effective collision resolution scheme for when the number of keys is not known in advance is the use of linked lists. This forms a chaining hash ...
CPS 214: Networks and Distributed Systems Lecture 4
... • Web cache returns the page content located at the 1st entry of the table. ...
... • Web cache returns the page content located at the 1st entry of the table. ...
Asynchronous Memory Access Chaining
... between performance (i.e., number of chained memory accesses) and space efficiency [4, 6, 7]. Moreover, when the build relation keys follow a skewed value distribution, hash collisions are unavoidable as some build keys are identical but carry different payloads. Probing such hash table buckets requ ...
... between performance (i.e., number of chained memory accesses) and space efficiency [4, 6, 7]. Moreover, when the build relation keys follow a skewed value distribution, hash collisions are unavoidable as some build keys are identical but carry different payloads. Probing such hash table buckets requ ...
Using Hash Based Apriori Algorithm to Reduce the Candidate 2
... In particular the 2-itemsets, since that is the key to improving performance. This algorithm uses a hash based technique to reduce the number of candidate itemsets generated in the first pass.It is claimed that the number of itemsets in C2 generated using hashing can be smalled,so that the scan requ ...
... In particular the 2-itemsets, since that is the key to improving performance. This algorithm uses a hash based technique to reduce the number of candidate itemsets generated in the first pass.It is claimed that the number of itemsets in C2 generated using hashing can be smalled,so that the scan requ ...
slides
... Lazy relocation: relocation only when the number of elements in a bucket is more than a predefined threshold (e.g. 4). An array of locks: need to acquire lock in any operation. ...
... Lazy relocation: relocation only when the number of elements in a bucket is more than a predefined threshold (e.g. 4). An array of locks: need to acquire lock in any operation. ...
Balloon: A Forward-Secure Append-Only Persistent Authenticated
... personal data are being processed. Balloon can also be used as part of a secure logging system, similar to the history tree system by Crosby and Wallach [6]. Another closely related application is as an extension to Certificate Transparency (CT) [12], where Balloon can be used to provide efficient n ...
... personal data are being processed. Balloon can also be used as part of a secure logging system, similar to the history tree system by Crosby and Wallach [6]. Another closely related application is as an extension to Certificate Transparency (CT) [12], where Balloon can be used to provide efficient n ...
II. Introduction to Data Structure and Abstract Data Types — C
... Basic operations: find unoccupied sets, reserve a set, cancel a seat assignment. 2. An implementation of an ADT consists of storage structures (commonly called data structures) to store the data items and algorithms for the basic operations and relations. Examples: Attempts 1 and 2 for TFA 3. Data a ...
... Basic operations: find unoccupied sets, reserve a set, cancel a seat assignment. 2. An implementation of an ADT consists of storage structures (commonly called data structures) to store the data items and algorithms for the basic operations and relations. Examples: Attempts 1 and 2 for TFA 3. Data a ...
Efficient Similarity Search for Hierarchical Data in Large Databases
... relabeling operations, as weights do not have any influence on the necessary structural modifications. But even when insert/delete operations are weighted, our filter can be used as long as their exists a smallest possible weight wmin for an insert or delete operation. In this case, the term (L1 (hl ...
... relabeling operations, as weights do not have any influence on the necessary structural modifications. But even when insert/delete operations are weighted, our filter can be used as long as their exists a smallest possible weight wmin for an insert or delete operation. In this case, the term (L1 (hl ...
ICOM4015-lec18
... • Adding an element: simple extension of the algorithm for finding an object Compute the hash code to locate the bucket in which the element should be inserted Try finding the object in that bucket If it is already present, do nothing; otherwise, ...
... • Adding an element: simple extension of the algorithm for finding an object Compute the hash code to locate the bucket in which the element should be inserted Try finding the object in that bucket If it is already present, do nothing; otherwise, ...
Lecture 2: Arrays - The Institute of Finance Management (IFM)
... Initialising arrays When an initialization of values is provided for an array, C++ allows the possibility of leaving the square brackets empty [ ]. In this case, the compiler will assume a size for the array that matches the number of values included between braces { }: Int billy [] = { 16, 2, 77 ...
... Initialising arrays When an initialization of values is provided for an array, C++ allows the possibility of leaving the square brackets empty [ ]. In this case, the compiler will assume a size for the array that matches the number of values included between braces { }: Int billy [] = { 16, 2, 77 ...
De-amortized Cuckoo Hashing: Provable Worst
... hashing are that no dynamic memory allocation is performed, and that the lookup procedure queries only two memory entries which are independent and can be queried in parallel. Although the insertion time of cuckoo hashing is essentially constant, with a noticeable probability during the insertion of ...
... hashing are that no dynamic memory allocation is performed, and that the lookup procedure queries only two memory entries which are independent and can be queried in parallel. Although the insertion time of cuckoo hashing is essentially constant, with a noticeable probability during the insertion of ...
Data Structures Lecture 1
... size, isEmpty, get and set run in O(1) time add and remove run in O(n) time in worst case In an add operation, when the array is full, instead of throwing an exception, we can replace the array with a larger one ...
... size, isEmpty, get and set run in O(1) time add and remove run in O(n) time in worst case In an add operation, when the array is full, instead of throwing an exception, we can replace the array with a larger one ...
csci 210: Data Structures Priority Queues and Heaps
... • Priority Queue vs Dictionary and Queues • implementation of PQueue ...
... • Priority Queue vs Dictionary and Queues • implementation of PQueue ...
csci 210: Data Structures Priority Queues and Heaps
... • Priority Queue vs Dictionary and Queues • implementation of PQueue ...
... • Priority Queue vs Dictionary and Queues • implementation of PQueue ...
Bloom filter
A Bloom filter is a space-efficient probabilistic data structure, conceived by Burton Howard Bloom in 1970, that is used to test whether an element is a member of a set. False positive matches are possible, but false negatives are not, thus a Bloom filter has a 100% recall rate. In other words, a query returns either ""possibly in set"" or ""definitely not in set"". Elements can be added to the set, but not removed (though this can be addressed with a ""counting"" filter). The more elements that are added to the set, the larger the probability of false positives.Bloom proposed the technique for applications where the amount of source data would require an impractically large amount of memory if ""conventional"" error-free hashing techniques were applied. He gave the example of a hyphenation algorithm for a dictionary of 500,000 words, out of which 90% follow simple hyphenation rules, but the remaining 10% require expensive disk accesses to retrieve specific hyphenation patterns. With sufficient core memory, an error-free hash could be used to eliminate all unnecessary disk accesses; on the other hand, with limited core memory, Bloom's technique uses a smaller hash area but still eliminates most unnecessary accesses. For example, a hash area only 15% of the size needed by an ideal error-free hash still eliminates 85% of the disk accesses, an 85–15 form of the Pareto principle (Bloom (1970)).More generally, fewer than 10 bits per element are required for a 1% false positive probability, independent of the size or number of elements in the set (Bonomi et al. (2006)).