1 CS 430 Database Theory Winter 2005 Lecture 12: SQL DML - SELECT

2 SELECT One statement for retrieving data: SELECT FROM WHERE ; Approximately:   (  ( ))  {t. | (t) AND }  Difference: SELECT does not eliminate duplicate rows

3 SELECT Multiple Tables Can have multiple tables in the FROM clause Retrieve names and address of Research department employees  SELECT FNAME, LNAME, ADDRESS FROM EMPLOYEE, DEPARMENT WHERE DNAME = ‘Research’ AND DEPARTMENT.DNUMBER = EMPLOYEE.DNUMBER;

4 Notes:  SQL is officially case insensitive  However, there are situations where it makes a difference E.g. MySQL stores MyISAM tables in individual files making table names case sensitive Attribute names don’t require qualification if they are unique (among all the tables that are part of the query)

5 SELECT Qualifying Attribute Names We can qualify attribute names  Tablename.attribute Assume EMPLOYEE and DEPARTMENT both have NAME and DNUMBER attributes:  SELECT FNAME, EMPLOYEE.NAME, ADDRESS FROM EMPLOYEE, DEPARMENT WHERE DEPARTMENT.NAME = ‘Research’ AND DEPARTMENT.DNUMBER = EMPLOYEE.DNUMBER;

6 SELECT Qualifying Attribute Names (2) [AS] :  SELECT FNAME, E.NAME, ADDRESS FROM EMPLOYEE AS E, DEPARMENT AS D WHERE D.NAME = ‘Research’ AND D.NUMBER = E.NUMBER; Also can refer to same table more than once:  SELECT E.FNAME, E.LNAME, S.FNAME, S.LNAME FROM EMPLOYEE E, EMPLOYEE S WHERE E.SUPERSSN = S.SSN;

7 SELECT Where Clause is Optional SELECT FNAME, LNAME, SSN FROM EMPLOYEE; Including multiple tables:  SELECT FNAME, LNAME, DNAME FROM EMPLOYEE, DEPARTMENT  Result is a Cartesian Product (all combinations of one row from each table)

8 SELECT * Can use * in place of attributes: SELECT * FROM EMPLOYEE;  Attributes are listed in order of definition Can also qualify * with a table name: SELECT EMPLOYEE.*, DNAME FROM EMPLOYEE, DEPARTMENT WHERE DNO = DNUMBER; Style: Never use * in a program  Always ask for attributes in order expected by program

9 SELECT DISTINCT What is we want duplicates eliminated  That is, when we want a set of results  Usually costs some time to eliminate duplicates  In many cases there are no duplicates, e.g. when we select the key of a table  Usually don’t want to eliminate duplicates when using aggregate functions (e.g. SUM) Do SELECT DISTINCT:  SELECT DISTINCT SALARY FROM EMPLOYEE; Note: ALL is opposite of DISTINCT

10 SELECT Ordering the result Use an ORDER BY clause E.g. SELECT DNAME, LNAME, FNAME FROM EMPLOYEE, DEPARTMENT WHERE DNO = DNUMBER ORDER BY DNAME, LNAME, FNAME;

11 SELECT Ordering the result (2) By default ORDER BY sorts in ascending order, if you want the opposite use ASC and DESC:  SELECT DNAME, LNAME, FNAME FROM EMPLOYEE, DEPARTMENT WHERE DNO = DNUMBER ORDER BY DNAME DESC, LNAME ASC, FNAME ASC;

12 Operations There is a plethora of operations available. Some examples:  Arithmetic: +, -, *, /  Comparison: or !=, >=, >  Pattern Matching: LIKE Operations can appear as part of a condition and as part of attributes to be selected

13 Operations Examples SELECT FNAME, LNAME, 1.1 * SALARY FROM EMPLOYEE; SELECT FNAME, LNAME FROM EMPLOYEE E, EMPLOYEE S WHERE E.MGRSSN = S.SSN AND E.SALARY > 1.5 * S.SALARY; SELECT FNAME, LNAME, 1.1 * SALARY AS NEW_SALARY FROM EMPLOYEE;  Renames the result column (when it makes a difference)

14 Pattern Matching Field LIKE Pattern, Field NOT LIKE Pattern Patterns  % matches zero or more characters like Regular Expression *  _ matches one character like Regular Expression.  Use \ to escape _ and % Example:  ADDRESS LIKE ‘%Houston%’  Houston is anywhere in the address string (would include a street named Houston)

15 Note on Pattern Matching Consider performance when using pattern matching.  SELECT FNAME, LNAME FROM EMPLOYEE WHERE ADDRESS LIKE ‘%Houston%’;  This would require a full table scan of the EMPLOYEE table

16 Three Valued Logic NULLs have multiple meanings All comparison involving a NULL yield NULL or UNKNOWN  Even NULL = NULL, all NULLs are considered distinct AND, OR, NOT  FALSE AND UNKNOWN is FALSE  TRUE OR UNKNOWN is TRUE  NOT UNKNOWN is UNKNOWN

17 More Three Valued Logic Can explicitly test for NULL with IS NULL, IS NOT NULL Example: SELECT FNAME, LNAME FROM EMPLOYEE WHERE SUPERSSN IS NULL;

18 JOINing Tables SQL incorporate notion of JOINed tables  Can specify a join in the FROM clause Example:  SELECT FNAME, LNAME, ADDRESS FROM (EMPLOYEE JOIN DEPARMENT ON DNO = DNUMBER) WHERE DNAME = ‘Research’;

19 More JOINing Tables NATURAL JOIN  SELECT DNAME, DLOCATION FROM (DEPARTMENT NATURAL JOIN DEPT_LOCATIONS); OUTER JOINS  SELECT E.LNAME AS ENAME, S.LNAME AS SNAME FROM (EMPLOYEE E LEFT OUTER JOIN EMPLOYEE S ON E.SUPERSSN = S.SSN);

20 More JOINing Tables Kinds of JOINs  [INNER] JOIN Normal Join  CROSS JOIN Cross Join is a cartesian product (no join condition)  LEFT [OUTER] JOIN  RIGHT [OUTER] JOIN Left and Right Outer Joins  FULL [OUTER] JOIN Two sided outer join Not supported in MySQL

21 Aggregate Functions Aggregate Functions:  COUNT, SUM, MAX, MIN, AVG, and some more  SUM, AVG work on numeric values  MAX, MIN work on values with a “total order”  COUNT returns number of tuples or values Simple example: SELECT AVG(SALARY), MAX(SALARY) FROM EMPLOYEE; Note: Can include WHERE Clause and Joins SELECT AVG(SALARY), MAX(SALARY) FROM (EMPLOYEE JOIN DEPARTMENT ON DNO=DNUMBER) WHERE DNAME = ‘Research’;

22 COUNT() COUNT counts the number of tuples or values COUNT(*) will count the number of tuples in the query COUNT(SALARY) will count the number of tuples with a non-null SALARY COUNT(DISTINCT SALARY) will count the number of DISTINCT values for SALARY

23 GROUP BY Problem with simple aggregates: Can’t return more than one row  Relational Algebra: Group rows together and compute aggregate function over the group (“script F” operator) SQL: GROUP BY CLAUSE Simple example: SELECT DNO, COUNT(*), AVG(SALARY) FROM EMPLOYEE GROUP BY DNO;

24 MORE GROUP BY Restriction (Queries with GROUP BY): All attributes used in the SELECT clause (includes used in expressions) must be either:  Named in the GROUP BY clause  Or, Used in an Aggregate function Illegal Example (should be):  SELECT DNO, SALARY FROM EMPLOYEE GROUP BY DNO; Legal Example:  SELECT DNO, MAX(SALARY) FROM EMPLOYEE GROUP BY DNO;

25 GROUP BY and NULLs If some of the rows being grouped have null attributes for a GROUPing attribute a separate group is created for those rows with that attribute being NULL Example:  Get number of employees supervised by each supervisor: SELECT SUPERSSN, COUNT(*) FROM EMPLOYEE GROUP BY SUPERSSN;

26 HAVING HAVING provides a condition that is tested after the rows are grouped:  Example: HAVING COUNT(*) > 2 (more than two tuples in the group). EXAMPLE: SELECT SUPERSSN, MAX(SALARY) FROM EMPLOYEE GROUP BY SUPERSSN HAVING COUNT(*) >= 2;

27 MORE GROUP BY and HAVING Semantics  The rest of the query (without GROUP BY and HAVING clauses) is processed first, resulting in a table of tuples  That table is then grouped according to the GROUP BY and Aggregate functions are computed as needed for the SELECT and HAVING clauses  Any HAVING clause is applied  The appropriate attributes from the resulting tuples are returned as the result

28 Nested Queries (Need MySQL 4.1 or later) Mini-example:  SELECT DISTINCT PNUMBER FROM PROJECT WHERE PNUMBER IN (SELECT PNUMBER FROM … WHERE … ); In general: Anything that can be done with a nested query can be done without

29 More Nested Queries IN can work with tuples: Example:  Find all employees who work the same (project, hours) combination on some project that SSN ‘ ’ works on. SELECT DISTINCT ESSN FROM WORKS_ON WHERE (PNO, HOURS) IN (SELECT PNO, HOURS FROM WORKS_ON WHERE SSN = ‘ ’);

30 More Nested Queries IN is the same as = ANY You can use ANY and ALL with any comparison (>, =, etc.) operator Example:  Find all employees whose salary is greater than all the employees in department 5  SELECT LNAME, FNAME FROM EMPLOYEE WHERE SALARY > ALL (SELECT SALARY FROM EMPLOYEE WHERE DNO = 5);

31 Correlated Nested Queries Refers to queries where a nested query refers to attributes in an outer query Example:  Find the name of all employees who have a dependent with the same first name and sex  SELECT E.FNAME, E.LNAME FROM EMPLOYEE E WHERE E.SSN IN (SELECT ESSN FROM DEPENDENT E.FNAME = DEPENDENT_NAME AND E.SEX = SEX);

32 EXISTS and NOT EXISTS EXISTS and NOT EXISTS are predicates that can be applied to a subquery Example:  Find all employees having dependents  SELECT FNAME, LNAME FROM EMPLOYEE WHERE NOT EXISTS (SELECT * FROM DEPENDENT WHERE SSN = ESSN);

33 UNION You can get the result of more than one query combined into a single result: SELECT … UNION SELECT …  Results in a table whose rows are the union of the results from the two queries  SELECT DISTINCT is implied with UNIONS This is a set operation

34 SELECT Statement Summary Lots of options You can mix and match pretty much arbitrarily Build up queries much as you would relational algebra expressions