CSCE 608-600 Database Systems Chapter 15: Query Execution 1.
1 CSCE 608-600 Database Systems Anxiao (Andrew) Jiang The Database Language SQL.
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Transcript of 1 CSCE 608-600 Database Systems Anxiao (Andrew) Jiang The Database Language SQL.
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CSCE 608-600 Database Systems
Anxiao (Andrew) Jiang
The Database Language SQL
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Introduction to SQL
Select-From-Where Statements
Subqueries
Grouping and Aggregation
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Select-From-Where Statements
SELECT desired attributes
FROM one or more tables
WHERE 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.
Candies(name, manf)Stores(name, addr, license)Consumers(name, addr, phone)Likes(consumer, candy)Sells(store, candy, price)Frequents(consumer, store)
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Example
Using Candies(name, manf), what candies are made by Hershey?
SELECT name
FROM Candies
WHERE manf = ’Hershey’;
Notice SQL uses single-quotes for strings.SQL is case-insensitive, except inside strings.
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Result of Query
name
Twizzler
Kitkat
AlmondJoy
. . .
The answer is a relation with a single attribute,name, and tuples with the name of each candyby Hershey, such as Twizzler.
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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
To implement this algorithm think of a tuple variable (tv) 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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Operational Semantics
Check ifHershey
name manf
Twizzler Hershey
tv
Include tv.name in the result
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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(consumer, candy) and Frequents(consumer, store), find the candies liked by at least one person who frequents 7-11.
SELECT candyFROM Likes, FrequentsWHERE store = ’7-11’ AND
Frequents.consumer = Likes.consumer;
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Formal Semantics
Almost the same as for single-relation queries:
Start with the product of all the relations in the FROM clause.
Apply the selection condition from the WHERE clause.
Project onto the list of attributes and expressions in the SELECT clause.
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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 Candies(name, manf), find all pairs of candies by the same manufacturer. Do not produce pairs like (Twizzler, Twizzler). Produce pairs in alphabetic order, e.g. (Kitkat,
Twizzler), not (Twizzler, Kitkat).
SELECT c1.name, c2.name
FROM Candies c1, Candies c2
WHERE c1.manf = c2.manf AND
c1.name < c2.name;
tuplevariables
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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.Can 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(store, candy, price), find the stores that sell Kitkats for the same price 7-11 charges for Twizzlers.
Two queries would surely work: Find the price 7-11 charges for Twizzlers. Find the stores that sell Kitkats at that
price.
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Query + Subquery Solution
SELECT storeFROM SellsWHERE candy = ’Kitkat’ AND
price = (SELECT price FROM Sells WHERE store= ’7-11’
AND candy = ’Twizzler’);
The price atwhich 7-11sells Twizzlers
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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 Candies(name, manf) and Likes(consumer, candy), find the name and manufacturer of each candy that Fred likes.
SELECT *
FROM Candies
WHERE name IN (SELECT candy
FROM Likes
WHERE consumer = ’Fred’);
The set ofcandies Fredlikes
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The Exists Operator
EXISTS( <relation> ) is true if and only if the <relation> is not empty.
Example: From Candies(name, manf) , find those candies that are the unique candy by their manufacturer.
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Example Query with EXISTS
SELECT nameFROM Candies c1WHERE NOT EXISTS(
SELECT *FROM CandiesWHERE manf = c1.manf AND
name <> c1.name);
Set ofcandieswith thesamemanf asc1, butnot thesamecandy
Notice scope rule: manf refersto closest nested FROM witha relation having that attribute.
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The Operator ANY
x = ANY( <relation> ) is a boolean condition that is 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(store, candy, price), find the candies sold for the highest price.
SELECT candy
FROM Sells
WHERE price >= ALL(
SELECT price
FROM 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(consumer, candy), Sells(store, candy, price), and Frequents(consumer, store), find the consumers and candies such that:
The consumer likes the candy, and The consumer frequents at least one
store that sells the candy.
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Solution
(SELECT * FROM Likes)
INTERSECT
(SELECT consumer, candy
FROM Sells, Frequents
WHERE Frequents.store = Sells.store
);
The consumer frequentsa store that sells thecandy.
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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
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(store, candy, price), find all the different prices charged for candies:
SELECT DISTINCT priceFROM Sells;
Notice that without DISTINCT, each price would be listed as many times as there were store/candy pairs at that price.
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Example: ALL
Using relations Frequents(consumer, store) and Likes(consumer, candy):
(SELECT consumer FROM Frequents)
EXCEPT ALL
(SELECT consumer FROM Likes); Lists consumers who frequent more stores than
they like candies, 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 Sells; Relations can be parenthesized subqueries, as
well.
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Theta Join
R JOIN S ON <condition> Example: using Consumers(name, addr)
and Frequents(consumer, store):Consumers JOIN Frequents ON
name = consumer;gives us all (c, a, c, s) quadruples such that consumer c lives at address a and frequents store s.
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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(store, candy, price), find the average price of Twizzlers:
SELECT AVG(price)
FROM Sells
WHERE candy = ’Twizzler’;
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Eliminating Duplicates in an Aggregation
Use DISTINCT inside an aggregation.Example: find the number of different
prices charged for Twizzlers:
SELECT COUNT(DISTINCT price)
FROM Sells
WHERE candy = ’Twizzler’;
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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 candy = ’Twizzler’;
SELECT count(price)FROM SellsWHERE candy = ’Twizzler’;
The number of storesthat sell Twizzlers.
The number of storesthat sell Twizzlers at aknown price.