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The table below shows the output from a template call (we'll call the template {{Conditional tables/example 1}}) with different values for {{{variable_foo}}}: Template call Result
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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 ...
SELECT is the most complex statement in SQL, with optional keywords and clauses that include: The FROM clause, which indicates the table(s) to retrieve data from. The FROM clause can include optional JOIN subclauses to specify the rules for joining tables. The WHERE clause includes a comparison predicate, which restricts the rows returned by ...
For example, nested tables (tables inside tables) should be separated into distinct tables when possible. Here is a more advanced example, showing some more options available for making up tables. Users can play with these settings in their own table to see what effect they have.
SQL-92 was the third revision of the SQL database query language. Unlike SQL-89, it was a major revision of the standard. Aside from a few minor incompatibilities, the SQL-89 standard is forward-compatible with SQL-92. The standard specification itself grew about five times compared to SQL-89.
SELECT is the most complex statement in SQL, with optional keywords and clauses that include: The FROM clause, which indicates the tables to retrieve data from. The FROM clause can include optional JOIN subclauses to specify the rules for joining tables. The WHERE clause includes a comparison predicate, which restricts the rows returned by the ...
If a query contains GROUP BY, rows from the tables are grouped and aggregated. After the aggregating operation, HAVING is applied, filtering out the rows that don't match the specified conditions. Therefore, WHERE applies to data read from tables, and HAVING should only apply to aggregated data, which isn't known in the initial stage of a query.