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A [[relational database management system]] uses [[SQL]] '''conditions''' or [[Expression (programming)|expressions]] in '''[[Where (SQL)|<tt>WHERE</tt>]]''' clauses and in '''[[Having (SQL)|<tt>HAVING</tt>]]''' clauses to '''<tt>[[select (SQL)|SELECT]]</tt>''' subsets of data.
A [[relational database management system]] uses [[SQL]] '''conditions''' or [[Expression (programming)|expressions]] in '''[[Where (SQL)|{{mono|WHERE}}]]''' clauses and in '''[[Having (SQL)|{{mono|HAVING}}]]''' clauses to '''{{mono|[[select (SQL)|SELECT]]}}''' subsets of data.


== Types of condition ==
== Types of condition ==
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* Many conditions compare values for (for example) equality, inequality or similarity.
* Many conditions compare values for (for example) equality, inequality or similarity.
* The EXISTS condition uses the [[SQL:2003|SQL standard]] [[SQL keywords|keyword]] <code>EXISTS</code><ref>
* The EXISTS condition uses the [[SQL:2003|SQL standard]] keyword <code>EXISTS</code><ref>
{{cite book
{{cite book
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|last= Fehily
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==Examples==
==Examples==
To '''<tt>SELECT</tt>''' one row of data from a table called ''tab'' with a primary key column (''pk'') set to 100 &mdash; use the condition ''pk = 100'':
To '''{{mono|SELECT}}''' one row of data from a table called ''tab'' with a primary key column (''pk'') set to 100 &mdash; use the condition ''pk = 100'':
<syntaxhighlight lang="sql">SELECT * FROM tab WHERE pk = 100</syntaxhighlight>
<syntaxhighlight lang="sql">SELECT * FROM tab WHERE pk = 100</syntaxhighlight>


To identify whether a table ''tab'' has rows of data with a duplicated column ''dk'' &mdash; use the condition ''having count(*) > 1'':
To identify whether a table ''tab'' has rows of data with a duplicated column ''dk'' &mdash; use the condition ''having count(*) > 1'':
<syntaxhighlight lang="sql">SELECT dk FROM tab GROUP BY dk HAVING count(*) > 1</syntaxhighlight>
<syntaxhighlight lang="sql">SELECT dk FROM tab GROUP BY dk HAVING count(*) > 1</syntaxhighlight>

== Advanced conditional logic in SQL ==
In addition to basic equality and inequality conditions, SQL allows for more complex conditional logic through constructs such as <code>CASE</code>, <code>COALESCE</code>, and <code>NULLIF</code>. The <code>CASE</code> expression, for example, enables SQL to perform conditional branching within queries, providing a mechanism to return different values based on evaluated conditions. This logic can be particularly useful for data transformation during retrieval, especially in SELECT statements. Meanwhile, <code>COALESCE</code> simplifies the process of handling NULL values by returning the first non-NULL value in a given list of expressions, which is especially useful in scenarios where data might be incomplete or missing. Furthermore, SQL's support for three-valued logic (True, False, Unknown) introduces nuances when handling NULL values in conditions, making it essential to carefully structure queries to account for the "Unknown" state that arises in certain comparisons with NULL values. Proper use of these advanced conditions enhances the flexibility and robustness of SQL queries, particularly in complex data retrieval and reporting environments.


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[[Category:SQL]]
[[Category:SQL]]
[[Category:Articles with example SQL code]]

Latest revision as of 08:13, 25 October 2024

A relational database management system uses SQL conditions or expressions in WHERE clauses and in HAVING clauses to SELECT subsets of data.

Types of condition

[edit]
  • Many conditions compare values for (for example) equality, inequality or similarity.
  • The EXISTS condition uses the SQL standard keyword EXISTS[1] to determine whether rows exist in a subquery result.[2]

Examples

[edit]

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:

SELECT dk FROM tab GROUP BY dk HAVING count(*) > 1

Advanced conditional logic in SQL

[edit]

In addition to basic equality and inequality conditions, SQL allows for more complex conditional logic through constructs such as CASE, COALESCE, and NULLIF. The CASE expression, for example, enables SQL to perform conditional branching within queries, providing a mechanism to return different values based on evaluated conditions. This logic can be particularly useful for data transformation during retrieval, especially in SELECT statements. Meanwhile, COALESCE simplifies the process of handling NULL values by returning the first non-NULL value in a given list of expressions, which is especially useful in scenarios where data might be incomplete or missing. Furthermore, SQL's support for three-valued logic (True, False, Unknown) introduces nuances when handling NULL values in conditions, making it essential to carefully structure queries to account for the "Unknown" state that arises in certain comparisons with NULL values. Proper use of these advanced conditions enhances the flexibility and robustness of SQL queries, particularly in complex data retrieval and reporting environments.

References

[edit]
  1. ^ Fehily, Chris (2005). SQL: Visual Quickstart Guide (2 ed.). Peachpit Press. pp. 439–440, 480. ISBN 978-0-321-33417-6. SQL Keywords [...] The appendix lists the SQL:2003 standard's reserved and non-reserved keywords. [...] EXISTS [...]
  2. ^ Fehily, Chris (2005). SQL: Visual Quickstart Guide (2 ed.). Peachpit Press. p. 278. ISBN 978-0-321-33417-6. EXISTS and NOT EXISTS [...] look for the existence or nonexistence of rows in a subquery result.