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SQLSQL CSET 3300. Introduction to SQL Select-From-Where Statements Meaning of queries Subqueries 2.

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Presentation on theme: "SQLSQL CSET 3300. Introduction to SQL Select-From-Where Statements Meaning of queries Subqueries 2."— Presentation transcript:

1 SQLSQL CSET 3300

2 Introduction to SQL Select-From-Where Statements Meaning of queries Subqueries 2

3 Why SQL? SQL is a very-high-level language, in which the programmer is able to avoid specifying a lot of data-manipulation details that would be necessary in languages like C++. What makes SQL viable is that its queries are “optimized” quite well, yielding efficient query executions. 3

4 Select-From-Where Statements The principal form of a query is: SELECT desired attributes FROM one or more tables WHERE condition about tuples of the tables 4

5 Our DB Schema DB schema for SQL queries – Underline indicates key attributes. Beers(name, manf) Bars(name, addr, license) Drinkers(name, addr, phone) Likes(drinker, beer) Sells(bar, beer, price) Frequents(drinker, bar) 5

6 SQL “Select” Example Using Beers(name, manf), what beers are made by Anheuser-Busch? SELECT name FROM Beers WHERE manf = ‘Anheuser-Busch’ 6 The answer is a relation with a single attribute- name, and tuples with the name of each beer by Anheuser-Busch, such as Bud. name Bud Lite Michelob Bud

7 “*” In SELECT Clauses When there is one relation in the FROM clause, * in the SELECT clause stands for “all attributes of this relation.” Example using Beers(name, manf): SELECT * FROM Beers WHERE manf = ‘Anheuser-Busch’ 7 namemanf BudAnheuser-Busch Bud LiteAnheuser-Busch MichelobAnheuser-Busch

8 Renaming Attributes If you want the result to have different attribute names, use “AS ” to rename an attribute. Example based on Beers(name, manf): SELECT name AS beer, manf FROM Beers WHERE manf = ‘Anheuser-Busch’ 8 beermanf BudAnheuser-Busch Bud LiteAnheuser-Busch MichelobAnheuser-Busch

9 Expressions in SELECT Clauses Any expression that makes sense can appear as an element of a SELECT clause. Example: from Sells(bar, beer, price): SELECT bar, beer, price * 120 AS priceInYen FROM Sells; 9 barbeerpriceInYen Joe’sBud300 Sue’sBud Lite350 …

10 Another Example: Constant Expressions From Likes(drinker, beer): SELECT drinker, ‘likes Bud’ AS whoLikesBud FROM Likes WHERE beer = ‘Bud’; 10 DrinkerwhoLikesBud SallyLikes Bud FredLikes Bud ….Likes Bud

11 Complex Conditions in WHERE Clause From Sells(bar, beer, price): – find the price Joe’s Bar charges for Bud: SELECT price FROM Sells WHERE bar = ‘Joe’’s Bar’ AND beer = ‘Bud’; 11

12 Important Points Two single quotes inside a string represent the single-quote (apostrophe). Conditions in the WHERE clause can use AND, OR, NOT, and parentheses in the usual way boolean conditions are built. SQL is case-insensitive. In general, upper and lower case characters are the same, except inside quoted strings. 12

13 Patterns in SQL Where Clauses WHERE clauses can have conditions in which a string is compared with a pattern, to see if it matches. General form: – LIKE or – NOT LIKE Pattern is a quoted string with – % = “any string” – _ = “any character.” 13

14 Example From Drinkers(name, addr, phone): – find the drinkers with exchange 555: SELECT name FROM Drinkers WHERE phone LIKE ‘%555-_ _ _ _’ 14

15 Relations with NULL Values Tuples in SQL relations can have NULL as a value for one or more components. Meaning depends on context. Two common cases: – Missing value : e.g., we know Joe’s Bar has some address, but we don’t know what it is. – Inapplicable : e.g., the value of attribute spouse for an unmarried person. The logic of conditions in SQL is really 3-valued logic: TRUE, FALSE, UNKNOWN. When any value is compared with NULL, the truth value is UNKNOWN. But a query only produces a tuple in the answer if its truth value for the WHERE clause is TRUE (not FALSE or UNKNOWN) 15

16 Example for Relations with NULL From the following Sells relation: SELECT bar FROM Sells WHERE price = 2.00; => We get only “Joe’s” bar 16 barbeerPrice Joe’sBud3.00 Sue’sBud LiteNULL …

17 Ordering the Output Tuples produced by a query can be presented in sorted order. To get output in sorted order – ORDER BY Default order is ascending For descending order append the keyword “DESC” to an attribute 17

18 Example Suppose we have a movies relation – Movie (title, year, length, studioName, producerNo) SELECT * FROM Movie WHERE studioName=“Disney” AND year= “2008” ORDER BY length, title 18

19 Example Using Beers(name, manf) – Find all pairs of beers by the same manufacturer. Do not produce pairs like (Bud, Bud). Produce pairs in alphabetic order, e.g. (Bud, Miller), not (Miller, Bud). SELECT b1.name, b2.name FROM Beers b1, Beers b2 WHERE b1.manf = b2.manf AND b1.name < b2.name 19

20 Subqueries A parenthesized SELECT-FROM-WHERE statement (subquery) can be used as a value in a number of places, including FROM and WHERE clauses. Example: in place of a relation in the FROM clause, we can place another query, and then query its result. – Better use a tuple-variable to name tuples of the result. If a subquery is guaranteed to produce one tuple, then the subquery can be used as a value. 20

21 Example Using Sells(bar, beer, price) – Find the bars that serve Miller for the same price Joe’s bar charges for Bud. Two queries would surely work: 1.Find the price Joe’s bar charges for Bud. 2.Find the bars that serve Miller at that price. 21

22 Query & Subquery Solution SELECT bar FROM Sells WHERE beer = ‘Miller’ AND price = (SELECT price FROM Sells WHERE bar = ‘Joe’’s Bar’ AND beer = ‘Bud’) The price at which Joe sells Bud 22

23 The IN Operator IN is true if and only if the tuple is a member of the relation. – NOT IN means the opposite. IN-expressions can appear in WHERE clauses. The is often a subquery. 23

24 Example Using Beers(beer, manf) and Likes(drinker, beer) – Find the beer and manufacturer of each beer that Fred likes. SELECT * FROM Beers WHERE beer IN (SELECT beer FROM Likes WHERE drinker = ‘Fred’) The set of beers Fred likes 24

25 The Exists Operator EXISTS( ) is true if and only if the is not empty. Being a boolean-valued operator, EXISTS can appear in WHERE clauses. Can use NOT EXISTS also. 25

26 Example Query with EXISTS 26  Using Beers(beer, manf) and Likes(drinker, beer)  Find the beer and manufacturer of each beer that Fred likes. SELECT * FROM Beers B WHERE EXISTS (SELECT * FROM Likes WHERE drinker = ‘Fred’ AND beer = B.beer)

27 The Operator ANY x = ANY( ) is a boolean condition meaning that x equals at least one tuple in the relation. Similarly, = can be replaced by any of the comparison operators. Example: x >= ANY( ) means x is not smaller than all tuples in the relation. – Note tuples must have one component only. 27

28 The Operator ALL Similarly, x <> ALL( ) is true if and only if for every tuple t in the relation, x is not equal to t. – That is, x is not a member of the relation. The <> can be replaced by any comparison operator. Example: x >= ALL( ) means there is no tuple larger than x in the relation. 28

29 Union, Intersection, and Difference Union, intersection, and difference of relations are expressed by the following forms, each involving subqueries: – ( subquery ) UNION ( subquery ) – ( subquery ) INTERSECT ( subquery ) – ( subquery ) EXCEPT ( subquery ) 29

30 Example Using Likes(drinker, beer) Sells(bar, beer, price) Visits(drinker, bar) Find the drinkers and beers such that: 1.The drinker likes the beer, and 2.The drinker visits at least one bar that sells the beer. 30

31 SQL Query (SELECT drinker, beer FROM Likes) INTERSECT (SELECT drinker, beer FROM Sells, Visits WHERE Visits.bar = Sells.bar ) The drinker visits a bar that sells the beer. 31

32 Bag Semantics Although the SELECT-FROM-WHERE statement uses bag semantics, the default for union, intersection, and difference is set semantics. – That is, duplicates are eliminated as the operation is applied. 32

33 Controlling Duplicate Elimination Force the result to be a set by – SELECT DISTINCT... Force the result to be a bag (i.e., don’t eliminate duplicates) by ALL – as in... UNION ALL... 33

34 Example: DISTINCT Using Sells(bar, beer, price) – Find all the different prices charged for beers: SELECT DISTINCT price FROM Sells; Notice that without DISTINCT, each price would be listed as many times as there were bar/beer pairs at that price. 34

35 Aggregations SUM, AVG, COUNT, MIN, and MAX can be applied to a column in a SELECT clause to produce that aggregation on the column. Also, COUNT(*) counts the number of tuples. 35

36 Example: Aggregation From Sells(bar, beer, price) – Find the average price of Bud: SELECT AVG(price) FROM Sells WHERE beer = ‘Bud’ 36

37 Eliminating Duplicates in an Aggregation DISTINCT inside an aggregation causes duplicates to be eliminated before the aggregation. Example: find the number of different prices charged for Bud: SELECT COUNT(DISTINCT price) FROM Sells WHERE beer = ‘Bud’ 37

38 NULL’s Ignored in Aggregation NULL never contributes to a sum, average, or count, and can never be the minimum or maximum of a column. But if there are no non-NULL values in a column, then the result of the aggregation is NULL. 38

39 The number of bars that sell Bud. The number of bars that sell Bud at a known price. Example: Effect of NULL’s SELECT count(*) FROM Sells WHERE beer = ‘Bud’; SELECT count(price) FROM Sells WHERE beer = ‘Bud’; 39

40 Grouping We may follow a SELECT-FROM-WHERE expression by GROUP BY and a list of attributes. The relation that results from the SELECT- FROM-WHERE is grouped according to the values of all those attributes – Any aggregation can be applied for each group. 40

41 Example: Grouping From Sells(bar, beer, price) – Find the average price for each beer: SELECT beer, AVG(price) FROM Sells GROUP BY beer; 41

42 Example: Grouping From Sells(bar, beer, price) and Frequents(drinker, bar) – Find for each drinker the average price of Bud at the bars they frequent: SELECT drinker, AVG(price) FROM Frequents, Sells WHERE beer = ‘Bud’ AND Frequents.bar = Sells.bar GROUP BY drinker; Compute drinker-bar- price of Bud tuples first, then group by drinker. 42

43 Restriction on SELECT Lists! If any aggregation is used, then each element of the SELECT list must be either: 1.Aggregated, or 2.An attribute on the GROUP BY list. 43  You might think you could find the bar that sells Bud the cheapest by: SELECT bar, MIN(price) FROM Sells WHERE beer = ‘Bud’;  But this query is illegal in SQL.  Why? Note bar is neither aggregated nor on the GROUP BY list.

44 HAVING Clauses HAVING may follow a GROUP BY clause. If so, the condition applies to each group, and groups not satisfying the condition are eliminated. 44

45 Example: HAVING From Sells(bar, beer, price) – Find the average price of those beers that are served in at least three bars. SELECT beer, AVG(price) FROM Sells GROUP BY beer HAVING COUNT(bar) >= 3 45 Beer groups with at least 3 bars


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