Structured Query Language used for defining and manipulating data in Relational DBs aimed at: –reducing training costs –increasing productivity –improve application portability –increase application longevity –reduce dependency on single vendors –enable cross systems communication In practice, SQLs can be a bit different

Querying RDBs with SQL use a form of pseudo english to retrieve data in a view (which looks like a table) syntax is based on a number of “clauses” Select: specifies what data elements will be included in the view From: lists the tables involved Where: specifies conditions to filter the data –specific values sought –links between tables

Example with one table find the name and address of customer number 12

Example with a range find the movies that are classified as adventure

Example with two tables List all movies with their associated type

Example with two tables same for Lucas movies only

Use of a Search Condition - nested queries find the name and address of the customer(s) who has rented star wars

Additional syntax Add computation in the “select” statement: –select SUM(price) –select AVG(price), MAX, MIN, COUNT Simplify comparisons with a BETWEEN clause and LIKE clause (with *, ?) Add sorting instruction after the where clause –ORDER BY name (alphabetical) –ORDER BY price (ascending) Provide aggregate information by grouping data: –GROUP BY customer

Compute fines for a rental

find the average duration of the movies for rent find the average duration of all completed rentals

find how much cash customer “Fred” has generated in total