Information Systems Engineering. SQL Structured Query Language DML Data Manipulation (sub)language

Transcription

1 Information Systems Engineering SQL Structured Query Language DML Data Manipulation (sub)language 1

2 DML SQL subset for data manipulation (DML) includes four main operations SELECT - used for querying a database INSERT - used for adding tuples in a relation DELETE - used for eliminating tuples from a relation UPDATE - used for changing attributes values of tuples in a relation The SELECT statement in its various forms and clauses, implements the relational algebra operations Most DBMS s allow: The emission of single SQL statements The definition of parameterized sequences of statements known as stored procedures MIB - ESIN apm@feup 2

3 SELECT statement Basic form of a SELECT statement Implements a sequence of a relational selection and a projection It has the form SELECT L FROM R [WHERE C] The WHERE clause is optional L is a list of attributes from relation R An * can be used to denote all attributes of R C is a boolean condition It implements the relational operations L ( C (R)) Examples from the Movie World database: SELECT * FROM Movies WHERE studio_name = Disney AND year = 1990 SELECT title, length FROM Movies WHERE length > 120 MIB - ESIN apm@feup 3

4 The conditions The condition C from the WHERE clause Has operands that can be Attributes from relation R Constants Results of pre-defined functions Has operators that can be Comparisons (=, <>, <, >, <=, >=) Arithmetic (+, -, *, /, %) String concatenation (+ in SQL Server, can be ) Logic (OR, AND, NOT, BETWEEN, IN, LIKE) Some examples (year>1970 OR length<90) AND studio_name= MGM (year-1930)*(year-1930) <= 100 year BETWEEN 1939 AND 1945 genre IN ( Drama, SciFi, Comedy ) MIB - ESIN apm@feup 4

5 The operator LIKE LIKE verifies if a string matches a pattern The pattern can be specified using special constructions that represent generic sequences of characters (wild cards) _ - represents any single character % - represents any sequence of zero or more characters [...] - any single character within a range (ex: [a-f]) or set (ex: [abcxyz]) [^...] - any single character not within a range or set (exs: [^f-k], [^fghj]) Example: name LIKE Zh[ae]ng To represent characters that appear in the wildcards we need to precede them with another character specified in a ESCAPE clause Example: phone LIKE %415!-% ESCAPE! MIB - ESIN apm@feup 5

6 The NULL value Some attributes can have the value NULL NULL may be interpreted as unknown or inapplicable Arithmetic or other non-comparison operators between a NULL and other value results in NULL It includes some non expected results: 0*NULL = NULL, year - year is equal to NULL (and not 0) if year is NULL Comparisons between a NULL and other value results in the special boolean UNKNOWN To test if a value is NULL we can not use the = operator (the result would be UNKNOWN) We must use the special operator IS: year IS NULL (result is TRUE or FALSE) phone IS NOT NULL (idem) MIB - ESIN apm@feup 6

7 The UNKNOWN value Truth table for logical operations considering the UNKNOWN value x y x AND y x OR y NOT x TRUE TRUE TRUE TRUE FALSE TRUE UNKNOWN UNKNOWN TRUE FALSE TRUE FALSE FALSE TRUE FALSE UNKNOWN TRUE UNKNOWN TRUE UNKNOWN UNKNOWN UNKNOWN UNKNOWN UNKNOWN UNKNOWN UNKNOWN FALSE FALSE UNKNOWN UNKNOWN FALSE TRUE FALSE TRUE TRUE FALSE UNKNOWN FALSE UNKNOWN TRUE FALSE FALSE FALSE FALSE TRUE Rational We can think in the following values for FALSE=0, UNKNOWN=0,5 and TRUE=1 And in following operations AND min, OR max and NOT x 1-x MIB - ESIN apm@feup 7

8 Projection and renaming The LIST L in SELECT can be used to perform an extended projection operation The renaming of the output attributes is performed appending AS <new_name> We can specify expressions built with attributes and constants and output names with AS <new_name> Examples: SELECT title AS name, length AS duration FROM Movies WHERE studio_name= Paramount AND year=1990 SELECT title, length* AS duration, Hrs AS in_hours FROM Movies title duration in_hours Pretty Woman Hrs MIB - ESIN apm@feup 8

9 Storing results The results of a SELECT can be stored as a new table in the database There is an INTO clause for storing results in a new table: SELECT L [INTO S] FROM R [WHERE C] S is the name of the resultant relation (table) Sometimes the results of a SELECT can produce duplicate tuples To eliminate duplicates ( (...)) from the results of a SELECT statement we need to add the keyword DISTINCT after SELECT SELECT [DISTINCT] L FROM R Example: SELECT DISTINCT title FROM Movies WHERE studio_name = MGM MIB - ESIN apm@feup 9

10 Ordering results Ordering the tuples in the resultant relation can be accomplished with the ORDER BY clause (must be the last in a SELECT) SELECT L FROM R [WHERE C] [ORDER BY (<expr> [ASC DESC]) n ] <expr> can be an attribute name or an expression involving attributes By default the ordering is ascending but can be descending with the suffix DESC Examples: SELECT * FROM Movies WHERE studio_name = MGM ORDER BY length DESC, title SELECT * FROM R ORDER BY a+b DESC MIB - ESIN apm@feup 10

11 More than one relation in FROM In the FROM clause we can have more than one relation The statement performs a product between them The attributes in the SELECT list L can be from any relation The condition C in WHERE can be built with any of the relations attributes The result is a theta join with condition C Example - Consider the following schema Movies(title, year, length, genre, studio_name, producer_id) MovieExec(id, name, address, worth) Query: SELECT name FROM Movies, MovieExec WHERE title = Star Wars AND producer_id = id The result is the name of the producer of Star Wars MIB - ESIN apm@feup 11

12 Disambiguating Disambiguating attributes Example - Married Actors with Movie Executives Add the following relation to the two previous ones: Actor(name, address, gender, birthdate) name and address are common to MovieExec SELECT Actor.name, MovieExec.name FROM Actor, MovieExec WHERE Actor.address = MovieExec.address Using the same relation more than once Example - Married actors SELECT Actor1.name, Actor2.name FROM Actor Actor1, Actor Actor2 WHERE Actor1.address = Actor2.address AND Actor1.name < Actor2.name It is equivalent to R(Actor1.name,Actor2.name) ( A1,A5 ( A2=A6 A1<A5 ( M(A1,A2,A3,A4) (Actor) N(A5,A6,A7,A8) (Actor)))) MIB - ESIN apm@feup 12

13 Set operations Set operations (,, -) can be performed between the results of 2 queries (SELECT statements) The query results must have the same attributes and types The operations are noted as UNION, INTERSECT and EXCEPT Results don t have duplicates To retain duplicates in a union use UNION ALL Example (SELECT name, address FROM Actor WHERE gender = F ) INTERSECT (SELECT name, address FROM MovieExec WHERE worth > ) MIB - ESIN apm@feup 13

14 Subqueries Subqueries are SELECT statements inside other SELECT statement We can use subqueries in 3 circunstances: To produce a scalar value inside a condition C in a WHERE clause To produce a relation used in a WHERE clause (with operators IN, EXISTS, ALL or ANY) To produce a relation used in a FROM clause Subqueries are specified within parenthesis (SELECT L FROM R [WHERE C]) We can have many levels of subqueries MIB - ESIN apm@feup 14

15 Subqueries as scalar values It can be used in a WHERE clause, as if it were a constant The scalar is produced if the query produces only one tuple and we project only one attribute from it Example - The producer of a movie We have already seen that we can find him with the query: SELECT name FROM Movies, MovieExec WHERE title = Star Wars AND producer_id = id We could also formulate the following equivalent: SELECT name FROM MovieExec WHERE id = (SELECT producer_id FROM Movies WHERE title = Star Wars ) MIB - ESIN apm@feup 15

16 Relations as subqueries Conditions can include relations with some operators EXISTS R is a condition that is TRUE if R is not empty val IN R - is TRUE if val is equal to one of the tuples of R val <comparison> ALL R - is TRUE if the <comparison> is verified for every tuple in R val <comparison> ANY R - is TRUE if the <comparison> is verified for at least one tuple of R For the IN, ALL and ANY operators R must be a relation with nr. of attributes equal to sequence val Some equivalences: val IN R val = ANY R val NOT IN R val <> ALL R MIB - ESIN apm@feup 16

17 Example Find the producers of Harrison Ford s movies Assuming relation ActsIn(title, year, name) SELECT name FROM MovieExec WHERE id IN (SELECT producer_id FROM Movies WHERE (title, year) IN (SELECT title, year FROM ActsIn WHERE name = Harrison Ford ) ) Find movies with remakes SELECT title FROM Movies First WHERE year < ANY (SELECT year FROM Movies WHERE title = First.title) First.title is concretized with each title existing in the relation Movies MIB - ESIN apm@feup 17

18 Subqueries in FROM A subquery producing a relation can enter in the FROM clause of another SELECT These subqueries must have an appended name Example Reformulation of finding the producers of Harrison Ford s movies SELECT name FROM MovieExec, (SELECT producer_id FROM Movies, ActsIn WHERE Movies.title = ActsIn.title AND Movies.year = ActsIn.year AND name = Harrison Ford ) Prod WHERE id = Prod.producer_id MIB - ESIN apm@feup 18

19 JOINS as Relations in FROM (1) Product We can use a product of two relations as a relation in a FROM clause Theta join The construction is done with the CROSS JOIN operator: SELECT title, year, name FROM Movies CROSS JOIN ActsIn We can build a theta join as a new relation to use in a FROM clause Outer joins General form: R1 [INNER] JOIN R2 ON C where C is a condition using the attributes of R1 and R2 General form: R1 {LEFT RIGHT FULL} [OUTER] JOIN R2 ON C It adds to the result tuples that were not paired MIB - ESIN apm@feup 19

20 JOINS as Relations in FROM (2) Natural join The natural join implicitly equates attributes with the same name Only one of each pair of equated attributes is retained The natural join can be constructed with a theta join (how?) Some DBMSs support directly natural joins (SQL Server doesn t) When it is supported it has the general form: R1 NATURAL JOIN R2 Natural outer join An outer join applied after a natural join Some DBMSs don t support directly this form (SQL Server and others) General form: R1 NATURAL {FULL LEFT RIGHT} [OUTER] JOIN R2 MIB - ESIN apm@feup 20

21 Examples The studios each actor has worked for SELECT DISTINCT name, studio_name FROM Movies JOIN ActsIn ON Movies.title = ActIn.title AND Movies.year = ActsIn.year Actors and Movie Executives SELECT name, address FROM Actor NATURAL FULL JOIN MovieExec If the DBMS doesn t support natural outer joins: (SELECT Actor.name, Actor.address FROM Actor LEFT JOIN MovieExec ON Actor.name = MovieExec.name AND Actor.address = MovieExec.Address) UNION (SELECT Actor.name, Actor.address FROM Actor RIGHT JOIN MovieExec ON Actor.name = MovieExec.name AND Actor.address = MovieExec.Address) MIB - ESIN apm@feup 21

22 Aggregation SQL support five aggregation operations SUM, AVG, MIN, MAX, COUNT They can be applied to one attribute that makes sense To count all the tuples in the relation use COUNT(*) To count all non-null tuples in an attribute we use COUNT(A) We can take into account only non-duplicate values using DISTINCT inside the operator, like COUNT(DISTINCT A) (rarely makes sense for other operations) Examples SELECT AVG(worth) FROM MovieExec SELECT COUNT(*) FROM ActsIn SELECT COUNT(DISTINCT name) FROM ActsIn MIB - ESIN apm@feup 22

23 Grouping Grouping in SQL implements the relational algebra operator L It uses a new clause in the SELECT statement specified immediately after the WHERE clause SELECT L1 FROM R [WHERE C] [GROUP BY L2] After constructing a resultant relation from R and C the tuples are grouped in the values of attributes present in list L2 The final result will contain columns listed in L1 (which must also be present in L2) and aggregations of any attribute, taken by group, and also present in list L1 MIB - ESIN apm@feup 23

24 Examples Total length of movies produced by each studio SELECT studio_name, SUM(length) FROM Movies GROUP BY studio_name List of studios that have produced movies SELECT studio_name FROM Movies GROUP BY studio_name Total length of movies produced by each producer SELECT name, SUM(length) FROM MovieExec, Movies WHERE id = producer_id GROUP BY name MIB - ESIN apm@feup 24

25 NULLs, Aggregation and Grouping There are some special rules concerning NULL values NULLs are ignored in aggregation operations except when we use COUNT(*) The NULL value is treated as an ordinary value when the groups are formed in the GROUP BY clause (we can have a group of NULLs) Aggregation operations, except COUNTs, performed over empty relations (0 tuples) result in a value of NULL The COUNT aggregation operation performed over an empty relation results in 0 MIB - ESIN apm@feup 25

26 Examples Consider the relation R(A, B) defined as follows: A NULL B NULL Query SELECT A, COUNT(B) FROM R GROUP BY A (NULL, 0) Another query SELECT A, SUM(B) FROM R GROUP BY A (NULL, NULL) MIB - ESIN apm@feup 26

27 Conditions in groups After the group formation, we can eliminate some of them, specifying a condition, usually using the results performed by aggregations on the group That s the role of the HAVING clause specified after the GROUP BY clause Rules about the condition in the HAVING clause Can have aggregation operators that apply only to the tuples of each group Any attribute can be aggregated but only attributes present in the GROUP BY clause can appear without an aggregation operator General form: SELECT L1 FROM R [WHERE C1] [GROUP BY L2] [HAVING C2] MIB - ESIN apm@feup 27

28 Example Total length of movies produced by producers that have movies before 1930 SELECT name, SUM(length) FROM MovieExec, Movies WHERE id = producer_id GROUP BY name HAVING MIN(year) < 1930 MIB - ESIN apm@feup 28

29 All main clauses of a SELECT The full form of the SELECT statement is SELECT L1 [INTO Res] FROM R n [WHERE C1] [GROUP BY L2] [HAVING C2] [ORDER BY L3] The R s in FROM can be JOINs We can rename attributes (with AS) We can rename relations We can use subqueries in R s and C s We can eliminate duplicates (with DISTINCT) MIB - ESIN apm@feup 29

30 Database modifications (1) Adding tuples to a relation It s done with an SQL INSERT statement General form: INSERT INTO R(A 1,, A n ) VALUES (v 1, v n ) A tuple is created in R with value v i for attribute A i If an attribute is missing it is created with a default value The list A 1,, A n can be omitted if the values follow the order of the schema Example: INSERT INTO ActsIn VALUES ( The Maltese Falcon, 1942, Sydney Greenstreet ) MIB - ESIN apm@feup 30

31 Database modifications (2) It is possible to insert several tuples, obtaining them from a subquery: INSERT INTO Studio(name) SELECT DISTINCT name FROM Movies WHERE name NOT IN (SELECT name FROM Studio) Delete tuples from a relation The elimination of tuples from a relation is done with the SQL DELETE statement General form: DELETE FROM R WHERE C All tuples belonging to R and satisfying the condition C will be eliminated MIB - ESIN apm@feup 31

32 Database modifications (3) Updating tuples The values of tuples already present in a relation can be modified using the SQL UPDATE statement General form: UPDATE R SET <assignment> n [WHERE C] <assignment> A = expression, where A is an attribute of R The <assignment> n only applies to tuples satisfying the condition C if it exists Example: prepend Pres. to the names of studio s presidents UPDATE MovieExec SET name = Pres. + name WHERE id IN (SELECT pres_id FROM Studio) MIB - ESIN apm@feup 32