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In computer science, the count-distinct problem [1] (also known in applied mathematics as the cardinality estimation problem) is the problem of finding the number of distinct elements in a data stream with repeated elements. This is a well-known problem with numerous applications.
The Misra–Gries algorithm uses O(k(log(m)+log(n))) space, where m is the number of distinct values in the stream and n is the length of the stream. The factor k accounts for the number of entries that are kept in the associative array A. Each entry consists of a value i and an associated counter c.
Here input is the input array to be sorted, key returns the numeric key of each item in the input array, count is an auxiliary array used first to store the numbers of items with each key, and then (after the second loop) to store the positions where items with each key should be placed, k is the maximum value of the non-negative key values and ...
An associative array stores a set of (key, value) pairs and allows insertion, deletion, and lookup (search), with the constraint of unique keys. In the hash table implementation of associative arrays, an array A {\displaystyle A} of length m {\displaystyle m} is partially filled with n {\displaystyle n} elements, where m ≥ n {\displaystyle m ...
Code Year was a free incentive Codecademy program intended to help people follow through on a New Year's Resolution to learn how to program, by introducing a new course for every week in 2012. [32] Over 450,000 people took courses in 2012, [33] [34] and Codecademy continued the program into 2013. Even though the course is still available, the ...
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For instance, if the three keys 1,3,2 are inserted into a binary search tree in that sequence, the number 1 will sit at the root of the tree, the number 3 will be placed as its right child, and the number 2 as the left child of the number 3.
A universal hashing scheme is a randomized algorithm that selects a hash function h among a family of such functions, in such a way that the probability of a collision of any two distinct keys is 1/m, where m is the number of distinct hash values desired—independently of the two keys. Universal hashing ensures (in a probabilistic sense) that ...