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  2. Count-distinct problem - Wikipedia

    en.wikipedia.org/wiki/Count-distinct_problem

    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.

  3. Cardinality (SQL statements) - Wikipedia

    en.wikipedia.org/wiki/Cardinality_(SQL_statements)

    In SQL (Structured Query Language), the term cardinality refers to the uniqueness of data values contained in a particular column (attribute) of a database table. The lower the cardinality, the more duplicated elements in a column. Thus, a column with the lowest possible cardinality would have the same value for every row.

  4. Query optimization - Wikipedia

    en.wikipedia.org/wiki/Query_optimization

    Each different way typically requires different processing time. Processing times of the same query may have large variance, from a fraction of a second to hours, depending on the chosen method. The purpose of query optimization, which is an automated process, is to find the way to process a given query in minimum time.

  5. HyperLogLog - Wikipedia

    en.wikipedia.org/wiki/HyperLogLog

    The HyperLogLog has three main operations: add to add a new element to the set, count to obtain the cardinality of the set and merge to obtain the union of two sets. Some derived operations can be computed using the inclusion–exclusion principle like the cardinality of the intersection or the cardinality of the difference between two HyperLogLogs combining the merge and count operations.

  6. Cardinality (data modeling) - Wikipedia

    en.wikipedia.org/wiki/Cardinality_(data_modeling)

    Within data modelling, cardinality is the numerical relationship between rows of one table and rows in another. Common cardinalities include one-to-one , one-to-many , and many-to-many . Cardinality can be used to define data models as well as analyze entities within datasets.

  7. MinHash - Wikipedia

    en.wikipedia.org/wiki/MinHash

    To estimate J(A,B) using this version of the scheme, let y be the number of hash functions for which h min (A) = h min (B), and use y/k as the estimate. This estimate is the average of k different 0-1 random variables, each of which is one when h min ( A ) = h min ( B ) and zero otherwise, and each of which is an unbiased estimator of J ( A , B ) .

  8. Query plan - Wikipedia

    en.wikipedia.org/wiki/Query_plan

    Since SQL is declarative, there are typically many alternative ways to execute a given query, with widely varying performance. When a query is submitted to the database, the query optimizer evaluates some of the different, correct possible plans for executing the query and returns what it considers the best option.

  9. Entity–relationship model - Wikipedia

    en.wikipedia.org/wiki/Entity–relationship_model

    The miscalculation happens because SQL treats each relationship individually, which may result in double-counting or other inaccuracies. This issue is particularly common in decision support systems. To mitigate this, either the data model or the SQL query itself must be adjusted. Some database querying software designed for decision support ...