database management systems chapter 6 the database language sql (i)
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Database Management Systems Chapter 6 The Database Language SQL (I). Instructor: Li Ma Department of Computer Science Texas Southern University, Houston. October, 2006. Introduction to SQL. Select-From-Where Statements Subqueries Grouping and Aggregation. Why SQL?. - PowerPoint PPT PresentationTRANSCRIPT
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Database Management Systems
Chapter 6 The Database Language SQL (I)
Instructor: Li Ma
Department of Computer ScienceTexas Southern University, Houston
October, 2006
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Introduction to SQL
Select-From-Where StatementsSubqueries
Grouping and Aggregation
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Why SQL?
SQL is a very-high-level language. Say “what to do” rather than “how to do it.” Avoid a lot of data-manipulation details
needed in procedural languages like C++ or Java.
Database management system figures out “best” way to execute query. Called “query optimization.”
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Select-From-Where Statements
SELECT desired attributesFROM one or more tablesWHERE condition about tuples of
the tables
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Our Running Example
All our SQL queries will be based on the following database schema. 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)
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Example
Using Beers(name, manf), what beers are made by Anheuser-Busch?
SELECT name
FROM Beers
WHERE manf = ’Anheuser-Busch’;
Notice SQL uses single-quotes for strings.SQL is case-insensitive, except inside strings.
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Result of Query
nameBudBud LiteMichelob . . .
The answer is a relation with a single attribute,name, and tuples with the name of each beerby Anheuser-Busch, such as Bud.
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Meaning of Single-Relation Query
Begin with the relation in the FROM clause.
Apply the selection indicated by the WHERE clause.
Apply the extended projection indicated by the SELECT clause.
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Operational Semantics
Check ifAnheuser-Busch
name manf
Bud Anheuser-Busch
tv
Include tv.name in the result
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Operational Semantics
To implement this algorithm think of a tuple variable ranging over each tuple of the relation mentioned in FROM.
Check if the “current” tuple satisfies the WHERE clause.
If so, compute the attributes or expressions of the SELECT clause using the components of this tuple.
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* 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’;
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Result of Query:
name manfBud Anheuser-BuschBud Lite Anheuser-BuschMichelob Anheuser-Busch . . . . . .
Now, the result has each of the attributesof Beers.
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Renaming Attributes
If you want the result to have different attribute names, use “AS <new name>” to rename an attribute.
Example based on Beers(name, manf):SELECT name AS beer, manf
FROM Beers
WHERE manf = ’Anheuser-Busch’
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Result of Query:
beer manfBud Anheuser-BuschBud Lite Anheuser-BuschMichelob Anheuser-Busch . . . . . .
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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 * 114 AS priceInYen
FROM Sells;
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Result of Query
bar beer priceInYenJoe’s Bud 285Sue’s Miller 342 … … …
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Another Example: Constant Expressions
From Likes(drinker, beer) :
SELECT drinker,
’likes Bud’ AS whoLikesBud
FROM Likes
WHERE beer = ’Bud’;
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Result of Query
drinker whoLikesBudSally likes BudFred likes Bud … …
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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’;
Notice how weget a single-quotein strings.
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Patterns
WHERE clauses can have conditions in which a string is compared with a pattern, to see if it matches.
General form: <Attribute> LIKE <pattern> or <Attribute> NOT LIKE <pattern>
Pattern is a quoted string with % = “any string”; _ = “any character.”
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Example
From Drinkers(name, addr, phone) find the drinkers with exchange 555:
SELECT name
FROM Drinkers
WHERE phone LIKE ’%555-_ _ _ _’;
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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.
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Comparing NULL’s to Values
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).
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Three-Valued Logic To understand how AND, OR, and NOT
work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = ½.
AND = MIN; OR = MAX, NOT(x) = 1-x. Example:TRUE AND (FALSE OR NOT(UNKNOWN))
= MIN(1, MAX(0, (1 - ½ ))) =MIN(1, MAX(0, ½ ) = MIN(1, ½ ) = ½.
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Surprising Example
From the following Sells relation:bar beer priceJoe’s BarBud NULL
SELECT barFROM SellsWHERE price < 2.00 OR price >= 2.00; UNKNOWN UNKNOWN
UNKNOWN
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Reason: 2-Valued Laws != 3-Valued Laws
Some common laws, like commutativity of AND, hold in 3-valued logic.
But not others, e.g., the “law of the excluded middle”: p OR NOT p = TRUE. When p = UNKNOWN, the left side is
MAX( ½, (1 – ½ )) = ½ != 1.
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Multirelation Queries
Interesting queries often combine data from more than one relation.
We can address several relations in one query by listing them all in the FROM clause.
Distinguish attributes of the same name by “<relation>.<attribute>”
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Example
Using relations Likes(drinker, beer) and Frequents(drinker, bar), find the beers liked by at least one person who frequents Joe’s Bar.SELECT beerFROM Likes, FrequentsWHERE bar = ’Joe’’s Bar’ AND
Frequents.drinker = Likes.drinker;
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Formal Semantics
Almost the same as for single-relation queries:
1. Start with the product of all the relations in the FROM clause.
2. Apply the selection condition from the WHERE clause.
3. Project onto the list of attributes and expressions in the SELECT clause.
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Operational Semantics
Imagine one tuple-variable for each relation in the FROM clause. These tuple-variables visit each
combination of tuples, one from each relation.
If the tuple-variables are pointing to tuples that satisfy the WHERE clause, send these tuples to the SELECT clause.
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Example
drinker bar drinker beer
tv1 tv2Sally Bud
Sally Joe’s
Likes Frequents
to outputcheck theseare equal
checkfor Joe
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Explicit Tuple-Variables
Sometimes, a query needs to use two copies of the same relation.
Distinguish copies by following the relation name by the name of a tuple-variable, in the FROM clause.
It’s always an option to rename relations this way, even when not essential.
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Example
From 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.nameFROM Beers b1, Beers b2WHERE b1.manf = b2.manf AND
b1.name < b2.name;
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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.
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Subqueries That Return One Tuple
If a subquery is guaranteed to produce one tuple, then the subquery can be used as a value. Usually, the tuple has one
component. A run-time error occurs if there is no
tuple or more than one tuple.
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Example
From Sells(bar, beer, price), find the bars that serve Miller for the same price Joe charges for Bud.
Two queries would surely work:1. Find the price Joe charges for Bud.2. Find the bars that serve Miller at that
price.
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Query + Subquery Solution
SELECT barFROM SellsWHERE beer = ’Miller’ AND
price = (SELECT price FROM Sells WHERE bar = ’Joe’’s Bar’
AND beer = ’Bud’);
The price atwhich Joesells Bud
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The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation. <tuple> NOT IN <relation> means
the opposite. IN-expressions can appear in
WHERE clauses. The <relation> is often a
subquery.
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Example From Beers(name, manf) and Likes(drinker,
beer), find the name and manufacturer of each beer that Fred likes. SELECT * FROM Beers WHERE name IN (SELECT beer
FROM Likes WHERE drinker =
’Fred’);
The set ofbeers Fredlikes
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The Exists Operator
EXISTS( <relation> ) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf) , find those beers that are the unique beer by their manufacturer.
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Example Query with EXISTS
SELECT nameFROM Beers b1WHERE NOT EXISTS(
SELECT *FROM BeersWHERE manf = b1.manf AND
name <> b1.name);
Set ofbeerswith thesamemanf asb1, butnot thesamebeer
Notice scope rule: manf refersto closest nested FROM witha relation having that attribute.
Notice theSQL “notequals”operator
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The Operator ANY
x = ANY( <relation> ) is a boolean condition true if x equals at least one tuple in the relation.
Similarly, = can be replaced by any of the comparison operators.
Example: x >= ANY( <relation> ) means x is not the smallest tuple in the relation. Note tuples must have one component only.
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The Operator ALL
Similarly, x <> ALL( <relation> ) 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( <relation> )
means there is no tuple larger than x in the relation.
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Example
From Sells(bar, beer, price), find the beer(s) sold for the highest price.
SELECT beerFROM SellsWHERE price >= ALL(
SELECT priceFROM Sells);
price from the outerSells must not beless than any price.
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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 )
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Example
From relations Likes(drinker, beer), Sells(bar, beer, price), and Frequents(drinker, bar), find the drinkers and beers such that:
1. The drinker likes the beer, and2. The drinker frequents at least one
bar that sells the beer.
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Solution
(SELECT * FROM Likes)INTERSECT
(SELECT drinker, beer FROM Sells, Frequents WHERE Frequents.bar = Sells.bar);
The drinker frequentsa bar that sells thebeer.
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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.
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Motivation: Efficiency
When doing projection, it is easier to avoid eliminating duplicates. Just work tuple-at-a-time.
For intersection or difference, it is most efficient to sort the relations first. At that point you may as well
eliminate the duplicates anyway.
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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 . . .
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Example: DISTINCT
From 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.
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Example: ALL
Using relations Frequents(drinker, bar) and Likes(drinker, beer):
(SELECT drinker FROM Frequents)
EXCEPT ALL
(SELECT drinker FROM Likes); Lists drinkers who frequent more bars
than they like beers, and does so as many times as the difference of those counts.
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Join Expressions
SQL provides several versions of (bag) joins.
These expressions can be stand-alone queries or used in place of relations in a FROM clause.
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Products and Natural Joins
Natural join:R NATURAL JOIN S;
Product:R CROSS JOIN S;
Example:Likes NATURAL JOIN Serves;
Relations can be parenthesized subqueries, as well.
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Theta Join
R JOIN S ON <condition> Example: using Drinkers(name, addr)
and Frequents(drinker, bar):Drinkers JOIN Frequents ON
name = drinker;gives us all (d, a, d, b) quadruples such that drinker d lives at address a and frequents bar b.
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Outerjoins
R OUTER JOIN S is the core of an outerjoin expression. It is modified by:
1. Optional NATURAL in front of OUTER.2. Optional ON <condition> after JOIN.3. Optional LEFT, RIGHT, or FULL before
OUTER. LEFT = pad dangling tuples of R only. RIGHT = pad dangling tuples of S only. FULL = pad both; this choice is the default.
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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.
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Example: Aggregation
From Sells(bar, beer, price), find the average price of Bud:
SELECT AVG(price)
FROM Sells
WHERE beer = ’Bud’;
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Eliminating Duplicates in an Aggregation
Use DISTINCT inside an aggregation. Example: find the number of
different prices charged for Bud:SELECT COUNT(DISTINCT
price)
FROM Sells
WHERE beer = ’Bud’;
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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.
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Example: Effect of NULL’s
SELECT count(*)FROM SellsWHERE beer = ’Bud’;
SELECT count(price)FROM SellsWHERE beer = ’Bud’;
The number of barsthat sell Bud.
The number of barsthat sell Bud at aknown price.
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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, and any aggregation is applied only within each group.
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Example: Grouping
From Sells(bar, beer, price), find the average price for each beer:
SELECT beer, AVG(price)
FROM Sells
GROUP BY beer;
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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, SellsWHERE beer = ’Bud’ AND
Frequents.bar = Sells.barGROUP BY drinker;
Computedrinker-bar-price for Budtuples first,then groupby drinker.
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Restriction on SELECT Lists With Aggregation
If any aggregation is used, then each element of the SELECT list must be either:
1. Aggregated, or2. An attribute on the GROUP BY list.
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Illegal Query Example
You might think you could find the bar that sells Bud the cheapest by:
SELECT bar, MIN(price)FROM SellsWHERE beer = ’Bud’;
But this query is illegal in SQL.
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HAVING Clauses
HAVING <condition> may follow a GROUP BY clause.
If so, the condition applies to each group, and groups not satisfying the condition are eliminated.
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Example: HAVING
From Sells(bar, beer, price) and Beers(name, manf), find the average price of those beers that are either served in at least three bars or are manufactured by Pete’s.
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Solution
SELECT beer, AVG(price)FROM SellsGROUP BY beerHAVING COUNT(bar) >= 3 OR
beer IN (SELECT name FROM Beers WHERE manf = ’Pete’’s’);
Beers manu-factured byPete’s.
Beer groups with at least3 non-NULL bars and alsobeer groups where themanufacturer is Pete’s.
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Requirements on HAVING Conditions
These conditions may refer to any relation or tuple-variable in the FROM clause.
They may refer to attributes of those relations, as long as the attribute makes sense within a group; i.e., it is either:
1. A grouping attribute, or2. Aggregated.