Brilliant Computing: SQL

SQL

Queries

The most common operation in SQL is the query, which is performed with the declarative SELECT statement. SELECT retrieves data from one or more tables, or expressions. Standard SQL statements have no persistent effects on the database. Some non-standard implementations of SELECT can have persistent effects, such as the SELECT INTO syntax that exists in some databases.^[10]
Queries allow the user to describe desired data, leaving the database management system (DBMS) responsible for planning, optimizing, and performing the physical operations necessary to produce that result as it chooses.
A query includes a list of columns to be included in the final result immediately following the SELECT keyword. An asterisk ("*") can also be used to specify that the query should return all columns of the queried tables. SELECT is the most complex statement in SQL, with optional keywords and clauses that include:

The FROM clause which indicates the table(s) from which data is to be retrieved. The FROM clause can include optional JOIN subclauses to specify the rules for joining tables.
The WHERE clause includes a comparison predicate, which restricts the rows returned by the query. The WHERE clause eliminates all rows from the result set for which the comparison predicate does not evaluate to True.
The GROUP BY clause is used to project rows having common values into a smaller set of rows. GROUP BY is often used in conjunction with SQL aggregation functions or to eliminate duplicate rows from a result set. The WHERE clause is applied before the GROUP BY clause.
The HAVING clause includes a predicate used to filter rows resulting from the GROUP BY clause. Because it acts on the results of the GROUP BY clause, aggregation functions can be used in the HAVING clause predicate.
The ORDER BY clause identifies which columns are used to sort the resulting data, and in which direction they should be sorted (options are ascending or descending). Without an ORDER BY clause, the order of rows returned by an SQL query is undefined.

The following is an example of a SELECT query that returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the result set.

SELECT * 
    FROM Book
    WHERE price > 100.00
    ORDER BY title;

The example below demonstrates a query of multiple tables, grouping, and aggregation, by returning a list of books and the number of authors associated with each book.

SELECT Book.title,
        count(*) AS Authors
    FROM Book
        JOIN Book_author ON Book.isbn = Book_author.isbn
    GROUP BY Book.title;

Example output might resemble the following:

Title                   Authors
----------------------  -------
SQL Examples and Guide     3
The Joy of SQL             1
An Introduction to SQL     2
Pitfalls of SQL            1

Under the precondition that isbn is the only common column name of the two tables and that a column named title only exists in the Books table, the above query could be rewritten in the following form:

SELECT title,
        count(*) AS Authors
    FROM Book 
        NATURAL JOIN Book_author 
    GROUP BY title;

However, many vendors either do not support this approach, or require column naming conventions.
SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.

SELECT isbn,
        title,
        price, 
        price * 0.06 AS sales_tax
    FROM Book
    WHERE price > 100.00
    ORDER BY title;

Null and Three-Valued Logic (3VL)

The idea of Null was introduced into SQL to handle missing information in the relational model. The introduction of Null (or Unknown) along with True and False is the foundation of Three-Valued Logic. Null does not have a value (and is not a member of any data domain) but is rather a placeholder or “mark” for missing information. Therefore comparisons with Null can never result in either True or False but always in the third logical result, Unknown.^[11]
SQL uses Null to handle missing information it supports three-valued logic (3VL) and the rules governing SQL three-valued logic (3VL) are shown below (p and q represent logical states).^[12] The word NULL is also a reserved keyword in SQL, used to identify the Null special marker.
Additionally, since SQL operators return Unknown when comparing anything with Null, SQL provides two Null-specific comparison predicates: The IS NULL and IS NOT NULL test whether data is or is not Null.^[13]
Note that SQL returns only results for which the WHERE clause returns a value of True. I.e., it excludes results with values of False, but also those whose value is Unknown.

p AND q		p
p AND q		True	False	Unknown
q	True	True	False	Unknown
	False	False	False	False
	Unknown	Unknown	False	Unknown

p OR q		p
p OR q		True	False	Unknown
q	True	True	True	True
	False	True	False	Unknown
	Unknown	True	Unknown	Unknown

p	NOT p
True	False
False	True
Unknown	Unknown

p = q		p
p = q		True	False	Unknown
q	True	True	False	Unknown
	False	False	True	Unknown
	Unknown	Unknown	Unknown	Unknown

Universal quantification is not explicitly supported by SQL, and must be worked out as a negated existential quantification.^[14]^[15]^[16]
SQL also provides the spaceship operator, <=>, to mean NULL-safe equality. That is,

p <=> q		p
p <=> q		True	False	Unknown
q	True	True	False	False
	False	False	True	False
	Unknown	False	False	True

[edit] Data manipulation

The Data Manipulation Language (DML) is the subset of SQL used to add, update and delete data:

INSERT adds rows (formally tuples) to an existing table, e.g.,:

INSERT INTO My_table 
        (field1, field2, field3) 
    VALUES 
        ('test', 'N', NULL);

UPDATE modifies a set of existing table rows, e.g.,:

UPDATE My_table 
    SET field1 = 'updated value' 
    WHERE field2 = 'N';

DELETE removes existing rows from a table, e.g.,:

DELETE FROM My_table 
    WHERE field2 = 'N';

TRUNCATE deletes all data from a table in a very fast way. It usually implies a subsequent COMMIT operation.
MERGE is used to combine the data of multiple tables. It combines the INSERT and UPDATE elements. It is defined in the SQL:2003 standard; prior to that, some databases provided similar functionality via different syntax, sometimes called "upsert".

Transaction controls

Transactions, if available, wrap DML operations:

START TRANSACTION (or BEGIN WORK, or BEGIN TRANSACTION, depending on SQL dialect) mark the start of a database transaction, which either completes entirely or not at all.
COMMIT causes all data changes in a transaction to be made permanent.
ROLLBACK causes all data changes since the last COMMIT or ROLLBACK to be discarded, leaving the state of the data as it was prior to those changes.

Once the COMMIT statement completes, the transaction's changes cannot be rolled back.
COMMIT and ROLLBACK terminate the current transaction and release data locks. In the absence of a START TRANSACTION or similar statement, the semantics of SQL are implementation-dependent. Example: A classic bank transfer of funds transaction.

START TRANSACTION;
  UPDATE Account SET amount=amount-200 WHERE account_number=1234;
  UPDATE Account SET amount=amount+200 WHERE account_number=2345;
IF ERRORS=0 COMMIT;
IF ERRORS<>0 ROLLBACK;

Data definition

The Data Definition Language (DDL) manages table and index structure. The most basic items of DDL are the CREATE, ALTER, RENAME, DROP and TRUNCATE statements:

CREATE creates an object (a table, for example) in the database.
DROP deletes an object in the database, usually irretrievably.
ALTER modifies the structure an existing object in various ways—for example, adding a column to an existing table.

Example:

CREATE TABLE My_table
(
    my_field1   INT,
    my_field2   VARCHAR(50),
    my_field3   DATE         NOT NULL,
    PRIMARY KEY (my_field1, my_field2) 
);

Data control

The Data Control Language (DCL) authorizes users and groups of users to access and manipulate data. Its two main statements are:

GRANT authorizes one or more users to perform an operation or a set of operations on an object.
REVOKE eliminates a grant, which may be the default grant.

Example:

GRANT SELECT, UPDATE 
    ON My_table 
    TO some_user, another_user;
 
REVOKE SELECT, UPDATE 
    ON My_table 
    FROM some_user, another_user;

Procedural extensions

SQL is designed for a specific purpose: to query data contained in a relational database. SQL is a set-based, declarative query language, not an imperative language such as C or BASIC. However, there are extensions to Standard SQL which add procedural programming language functionality, such as control-of-flow constructs. These are:

Source	Common Name	Full Name
ANSI/ISO Standard	SQL/PSM	SQL/Persistent Stored Modules
Interbase/ Firebird	PSQL	Procedural SQL
IBM	SQL PL	SQL Procedural Language (implements SQL/PSM)
Microsoft/ Sybase	T-SQL	Transact-SQL
MySQL	SQL/PSM	SQL/Persistent Stored Module (implements SQL/PSM)
Oracle	PL/SQL	Procedural Language/SQL (based on Ada)
PostgreSQL	PL/pgSQL	Procedural Language/PostgreSQL Structured Query Language (based on Oracle PL/SQL)
PostgreSQL	PL/PSM	Procedural Language/Persistent Stored Modules (implements SQL/PSM)

In addition to the standard SQL/PSM extensions and proprietary SQL extensions, procedural and object-oriented programmability is available on many SQL platforms via DBMS integration with other languages. The SQL standard defines SQL/JRT extensions (SQL Routines and Types for the Java Programming Language) to support Java code in SQL databases. SQL Server 2005 uses the SQLCLR (SQL Server Common Language Runtime) to host managed .NET assemblies in the database, while prior versions of SQL Server were restricted to using unmanaged extended stored procedures which were primarily written in C. Other database platforms, like MySQL and Postgres, allow functions to be written in a wide variety of languages including Perl, Python, Tcl, and C.