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In SQL, the unique keys have a UNIQUE constraint assigned to them in order to prevent duplicates (a duplicate entry is not valid in a unique column). Alternate keys may be used like the primary key when doing a single-table select or when filtering in a where clause, but are not typically used to join multiple tables.
For purposes of row elimination and duplicate removal, the EXCEPT operator does not distinguish between NULLs. The EXCEPT ALL operator does not remove duplicates, but if a row appears X times in the first query and Y times in the second, it will appear max ( X − Y , 0 ) {\displaystyle \max(X-Y,0)} times in the result set.
There is also an IGNORE clause for the INSERT statement, [7] which tells the server to ignore "duplicate key" errors and go on (existing rows will not be inserted or updated, but all new rows will be inserted). SQLite's INSERT OR REPLACE INTO works similarly. It also supports REPLACE INTO as an alias for compatibility with MySQL. [8]
Also, self-references are possible (not fully implemented in MS SQL Server though [5]). On inserting a new row into the referencing table, the relational database management system (RDBMS) checks if the entered key value exists in the referenced table. If not, no insert is possible.
Without an ORDER BY clause, the order of rows returned by an SQL query is undefined. The DISTINCT keyword [5] eliminates duplicate data. [6] The following example of a SELECT query returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database.It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [1]
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Record linkage (also known as data matching, data linkage, entity resolution, and many other terms) is the task of finding records in a data set that refer to the same entity across different data sources (e.g., data files, books, websites, and databases).