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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.
Although not in standard, most DBMS allows using a select clause without a table by pretending that an imaginary table with one row is used. This is mainly used to perform calculations where a table is not needed. The SELECT clause specifies a list of properties (columns) by name, or the wildcard character (“*”) to mean “all properties”.
For example, AVERAGE=SUM/COUNT and RANGE=MAX−MIN. In the MapReduce framework, these steps are known as InitialReduce (value on individual record/singleton set), Combine (binary merge on two aggregations), and FinalReduce (final function on auxiliary values), [ 5 ] and moving decomposable aggregation before the Shuffle phase is known as an ...
To SELECT one row of data from a table called tab with a primary key column (pk) set to 100 — use the condition pk = 100: SELECT * FROM tab WHERE pk = 100 To identify whether a table tab has rows of data with a duplicated column dk — use the condition having count(*) > 1 :
In relational databases, the information schema (information_schema) is an ANSI-standard set of read-only views that provide information about all of the tables, views, columns, and procedures in a database. [1] It can be used as a source of the information that some databases make available through non-standard commands, such as:
The Flajolet–Martin algorithm is an algorithm for approximating the number of distinct elements in a stream with a single pass and space-consumption logarithmic in the maximal number of possible distinct elements in the stream (the count-distinct problem).
An example of a data table column with low-cardinality would be a CUSTOMER table with a column named NEW_CUSTOMER. This column would contain only two distinct values: Y or N, denoting whether the customer was new or not. Since there are only two possible values held in this column, its cardinality type would be referred to as low-cardinality. [2]
SELECT AVG (salary) FROM employees WHERE department = emp. department In the above nested query the inner query has to be re-executed for each employee. (A sufficiently smart implementation may cache the inner query's result on a department-by-department basis, but even in the best case the inner query must be executed once per department.)