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=== Queries ===
=== Queries ===


The most common operation in SQL databases is the query, denoted with the <code>SELECT</code> keyword. SQL <code>SELECT</code> queries are [[declarative programming|declarative]]:
The most common operation in SQL databases is the query, which are performed with the [[declarative programming|declarative]] <code>[[Select (SQL)|SELECT]]</code> keyword. <code>SELECT</code> retrieves data from a specified [[Table (database)|table]], or multiple related tables, in a database. While often grouped with [[Data Manipulation Language|Data Manipulation Language (DML)]] statements, <code>SELECT</code> is considered to be separate from SQL DML, as it has no persistent effects on the data stored in the database.


* <code>[[Select (SQL)|SELECT]]</code> retrieves data from [[Table (database)|tables]] in a database. While often grouped with [[Data Manipulation Language]] statements, <code>SELECT</code> is considered by many to be separate from SQL DML. <code>SELECT</code> queries allow the user to specify a description of the desired result set, but it is left to the devices of the [[Database management system|database management system (DBMS)]] to [[query plan|plan]], [[query optimizer|optimize]], and perform the physical operations necessary to produce that result set. A SQL query includes a list of columns to be included in the final result immediately following the <code>SELECT</code> keyword. An asterisk ("*") can also be used as a "wildcard" indicator to specify that all available columns of a table (or multiple tables) are to be returned. <code>SELECT</code> is the most complex statement in SQL, with several optional keywords and clauses:
SQL queries allow the user to specify a description of the desired result set, but it is left to the devices of the [[Database management system|database management system (DBMS)]] to [[query plan|plan]], [[query optimizer|optimize]], and perform the physical operations necessary to produce that result set in as efficient a manner as possible. A SQL query includes a list of columns to be included in the final result immediately following the <code>SELECT</code> keyword. An asterisk ("*") can also be used as a "wildcard" indicator to specify that all available columns of a table (or multiple tables) are to be returned. <code>SELECT</code> is the most complex statement in SQL, with several optional keywords and clauses, including:

** The <code>FROM</code> clause indicates the source tables from which the data is to be drawn. The <code>FROM</code> clause can include optional <code>[[Join (SQL)|JOIN]]</code> clauses to join related tables to one another.
** The <code>[[Where (SQL)|WHERE]]</code> clause includes a comparison predicate, which is used to narrow the result set. The <code>WHERE</code> clause eliminates all rows from the result set for which the comparison predicate does not evaluate to True.
* The <code>FROM</code> clause which indicates the source table or tables from which the data is to be retrieved. The <code>FROM</code> clause can include optional <code>[[Join (SQL)|JOIN]]</code> clauses to join related tables to one another based on user-specified criteria.
* The <code>[[Where (SQL)|WHERE]]</code> clause includes a comparison predicate, which is used to restrict the number of rows returned by the query. The <code>WHERE</code> clause is applied before the <code>GROUP BY</code> clause. The <code>WHERE</code> clause eliminates all rows from the result set where the comparison predicate does not evaluate to True.
** The <code>[[Group by (SQL)|GROUP BY]]</code> clause is used to combine rows with related values into elements of a smaller set of rows.
** The <code>[[Having (SQL)|HAVING]]</code> clause is used to identify which of the "combined rows" (combined rows are produced when the query has a <code>GROUP BY</code> clause or when the <code>SELECT</code> part contains aggregates), are to be retrieved. <code>HAVING</code> acts much like a <code>WHERE</code>, but it operates on the results of the <code>GROUP BY</code>and can include aggregate functions.
* The <code>[[Group by (SQL)|GROUP BY]]</code> clause is used to combine, or group, rows with related values into elements of a smaller set of rows. <code>GROUP BY</code> is often used in conjunction with SQL aggregate functions or to eliminate duplicate rows from a result set.
** The <code>[[Order by (SQL)|ORDER BY]]</code> clause is used to identify which columns are used to sort the resulting data. Unless an <code>ORDER BY</code> clause is included, the order of rows returned by <code>SELECT</code> is never guaranteed.
* The <code>[[Having (SQL)|HAVING]]</code> clause includes a comparison predicate used to eliminate rows after the <code>GROUP BY</code> clause is applied to the result set. Because it acts on the results of the <code>GROUP BY</code> clause, aggregate functions can be used in the <code>HAVING</code> clause predicate.
* The <code>[[Order by (SQL)|ORDER BY]]</code> clause is used to identify which columns are used to sort the resulting data, and in which order they should be sorted (options are ascending or descending). The order of rows returned by a SQL query is never guaranteed unless an <code>ORDER BY</code> clause is specified.

The following is an example of a <code>SELECT</code> query that returns a list of expensive books. The query retrieves all rows from the ''books'' 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 ''books'' table should be included in the result set.


Data retrieval is very often combined with [[data projection]]; usually it isn't the verbatim data stored in [[primitive type|primitive data types]] that a user is looking for or a query is written to serve. Often the data needs to be expressed differently from how it's stored. SQL allows a wide variety of formulas included in the ''select list'' to ''project'' data.
''Example 1:''
''Example 1:''
SELECT * FROM books
SELECT *
FROM books
WHERE price > 100.00
WHERE price > 100.00
ORDER BY title
ORDER BY title;

This is an example that could be used to get a list of expensive books. It retrieves the records from the ''books'' table that have a ''price'' field which is greater than 100.00. The result is sorted alphabetically by book title. The asterisk (*) means to show all columns of the ''books'' table. Alternatively, specific columns could be named.
The example below demonstrates the use of multiple tables in a [[Join (SQL)|join]], grouping, and aggregation in a SQL query, by returning a list of books and the number of authors associated with each book.
''Example 2:''

SELECT books.title, count(*) AS Authors
SELECT books.title, count(*) AS Authors
FROM books
FROM books
JOIN book_authors
JOIN book_authors
ON books.book_number = book_authors.book_number
ON books.isbn = book_authors.isbn
GROUP BY books.title
GROUP BY books.title;


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.
which could also be written as


SELECT title, count(*) AS Authors
SELECT title, count(*) AS Authors
FROM books NATURAL JOIN book_authors
FROM books
NATURAL JOIN book_authors
GROUP BY title
GROUP BY title;


Example output might resemble the following:
under the precondition that book_number is the only common column name of the two tables and that a column named title only exists in books.

Example 2 shows both the use of multiple tables in a [[Join (SQL)|join]], and aggregation (grouping). This example shows how many authors there are per book. Example output may resemble:


Title Authors
Title Authors
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Pitfalls of SQL 1
Pitfalls of SQL 1
How SQL Saved my Dog 1
How SQL Saved my Dog 1

Data retrieval is very often combined with [[data projection]] when the user is looking for calculated values and not just the verbatim data stored in [[primitive type|primitive data types]], or when the data needs to be expressed in a form that is different from how it's stored. 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 books
WHERE price > 100.00
ORDER BY title;


=== Data manipulation ===
=== Data manipulation ===

Revision as of 20:11, 8 June 2007

SQL
Paradigmmulti-paradigm
Designed byDonald D. Chamberlin and Raymond F. Boyce
DeveloperIBM
First appeared1974
Stable release
SQL:2003 / 2003
Typing disciplinestatic, strong
Websitewww.iso.org/standard/76583.html
Major implementations
Many

SQL (IPA: [ˈɛsˈkjuˈɛl] or IPA: [ˈsiːkwəl]) is a computer language used to create, retrieve, update and delete data from relational database management systems. SQL has been standardized by both ANSI and ISO.

The first version of SQL was developed at IBM by Donald D. Chamberlin and Raymond F. Boyce in the early 1970s. This version, initially called SEQUEL, was designed to manipulate and retrieve data stored in IBM's original relational database product, System R. The SQL language was later formally standardized by the American National Standards Institute (ANSI) in 1986. Subsequent versions of the SQL standard have been released as International Organization for Standardization (ISO) standards. Originally standing for Structured Query Language, SQL is now nominally a name with no official expansion, rather than an acronym.

Originally designed as a declarative query and data manipulation language, variations of SQL have been created by SQL database management system (DBMS) vendors that add procedural constructs, control-of-flow statements, user-defined data types, and various other language extensions. With the release of the SQL:1999 standard, many such extensions were formally adopted as part of the SQL language via the SQL Persistent Stored Modules (SQL/PSM) portion of the standard.

SQL has come under criticism for its lack of cross-platform portability between vendors, inappropriate handling of missing data (see Null (SQL)), complex three-valued logic system, and its complex and occasionally ambiguous language grammar and semantics.

History

An influential paper, A Relational Model of Data for Large Shared Data Banks, by Dr. Edgar F. Codd, was published in June 1970 in the Association for Computing Machinery (ACM) journal, Communications of the ACM, although drafts of it were circulated internally within IBM in 1969.[1] Codd's model became widely accepted as the definitive model for relational database management systems (RDBMS or RDMS).

During the 1970s, a group at IBM's San Jose research center developed a database system "System R" based upon Codd's model. Structured English Query Language ("SEQUEL") was designed to manipulate and retrieve data stored in System R. The acronym SEQUEL was later condensed to SQL because the word 'SEQUEL' was held as a trademark by the Hawker Siddeley aircraft company of the UK.[citation needed] Although SQL was influenced by Codd's work, Donald D. Chamberlin and Raymond F. Boyce at IBM were the authors of the SEQUEL language design.[2] Their concepts were published to increase interest in SQL.

The first non-commercial, relational, non-SQL database, Ingres, was developed in 1974 at U.C. Berkeley.

In 1978, methodical testing commenced at customer test sites. Demonstrating both the usefulness and practicality of the system, this testing proved to be a success for IBM. As a result, IBM began to develop commercial products based on their System R prototype that implemented SQL, including the System/38 (announced in 1978 and commercially available in August 1979), SQL/DS (introduced in 1981), and DB2 (in 1983).[2]

At the same time, Relational Software, Inc. (now Oracle Corporation) saw the potential of the concepts described by Chamberlin and Boyce and developed their own version of a RDBMS for the Navy, CIA and others. In the summer of 1979, Relational Software, Inc. introduced Oracle V2 (Version2) for VAX computers as the first commercially available implementation of SQL. Oracle V2 beat IBM's release of the System/38 to the market by a few weeks.

Standardization

SQL was adopted as a standard by ANSI (American National Standards Institute) in 1986 and ISO (International Organization for Standardization) in 1987. However, since the dissolution of the NIST data management standards program in 1996 there has been no certification for compliance with the SQL standard so vendors must be relied on to self-certify.[3]

The SQL standard has gone through a number of revisions:

Year Name Alias Comments
1986 SQL-86 SQL-87 First published by ANSI. Ratified by ISO in 1987.
1989 SQL-89 Minor revision.
1992 SQL-92 SQL2 Major revision (ISO 9075).
1999 SQL:1999 SQL3 Added regular expression matching, recursive queries, triggers, non-scalar types, and some object-oriented features. (The last two are somewhat controversial and not yet widely supported.)
2003 SQL:2003   Introduced XML-related features, window functions, standardized sequences, and columns with auto-generated values (including identity-columns).
2006 SQL:2006   ISO/IEC 9075-14:2006 defines ways in which SQL can be used in conjunction with XML. It defines ways of importing and storing XML data in an SQL database, manipulating it within the database and publishing both XML and conventional SQL-data in XML form. In addition, it provides facilities that permit applications to integrate into their SQL code the use of XQuery, the XML Query Language published by the World Wide Web Consortium (W3C), to concurrently access ordinary SQL-data and XML documents.

The SQL standard is not freely available. SQL:2003 and SQL:2006 may be purchased from ISO or ANSI. A late draft of SQL:2003 is available as a zip archive from Whitemarsh Information Systems Corporation. The zip archive contains a number of PDF files that define the parts of the SQL:2003 specification.

Scope and 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 Development
Method
ANSI SQL/PSM SQL/Persistent Stored Module Standard
IBM SQL PL SQL Procedural Language Proprietary
Microsoft/
Sybase
T-SQL Transact-SQL Proprietary
MySQL MySQL MySQL Open Source/
Proprietary
Oracle PL/SQL Procedural Language/SQL Proprietary
Postgres PostgreSQL Postgres SQL Open Source

In addition to SQL extensions, another approach to mix programability with SQL is to allow procedural or object-oriented programming language code to be embedded in and interact with the database. For example, Oracle and others include Java in the database, and SQL Server 2005 allows any .NET language to be hosted within the database server process, while MySQL and Postgres allow functions to be written in a wide variety of languages, including Perl, Tcl, and C.

Commercial implementations of SQL commonly omit support for basic features of Standard SQL, such as the DATE or TIME data types, preferring variations of their own. As a result, SQL code can rarely be ported between database systems without modifications.

Reasons for lack of portability

There are several reasons for this lack of portability between database systems:

  • The complexity and size of the SQL standard means that most databases do not implement the entire standard.
  • The standard does not specify database behavior in several important areas (e.g. indexes), leaving it up to implementations of the database to decide how to behave.
  • The SQL standard precisely specifies the syntax that a conforming database system must implement. However, the standard's specification of the semantics of language constructs is less well-defined, leading to areas of ambiguity.
  • Many database vendors have large existing customer bases; where the SQL standard conflicts with the prior behavior of the vendor's database, the vendor may be unwilling to break backward compatibility.

SQL keywords

The SQL language is sub-divided into several language elements, including:

  • Statements which may have a persistent effect on schemas and data, or which may control transactions, program flow, connections, sessions, or diagnostics.
  • Queries which retrieve data based on specific criteria.
  • Expressions which can produce either scalar values or tables consisting of columns and rows of data.
  • Predicates which specify conditions that can be evaluated to SQL three-valued logic (3VL) Boolean truth values and are commonly used to limit the effects of statements and queries, or to change program flow.
  • Clauses which are (in some cases optional) constituent components of statements and queries.[4]

Queries

The most common operation in SQL databases is the query, which are performed with the declarative SELECT keyword. SELECT retrieves data from a specified table, or multiple related tables, in a database. While often grouped with Data Manipulation Language (DML) statements, SELECT is considered to be separate from SQL DML, as it has no persistent effects on the data stored in the database.

SQL queries allow the user to specify a description of the desired result set, but it is left to the devices of the database management system (DBMS) to plan, optimize, and perform the physical operations necessary to produce that result set in as efficient a manner as possible. A SQL query includes a list of columns to be included in the final result immediately following the SELECT keyword. An asterisk ("*") can also be used as a "wildcard" indicator to specify that all available columns of a table (or multiple tables) are to be returned. SELECT is the most complex statement in SQL, with several optional keywords and clauses, including:

  • The FROM clause which indicates the source table or tables from which the data is to be retrieved. The FROM clause can include optional JOIN clauses to join related tables to one another based on user-specified criteria.
  • The WHERE clause includes a comparison predicate, which is used to restrict the number of rows returned by the query. The WHERE clause is applied before the GROUP BY clause. The WHERE clause eliminates all rows from the result set where the comparison predicate does not evaluate to True.
  • The GROUP BY clause is used to combine, or group, rows with related values into elements of a smaller set of rows. GROUP BY is often used in conjunction with SQL aggregate functions or to eliminate duplicate rows from a result set.
  • The HAVING clause includes a comparison predicate used to eliminate rows after the GROUP BY clause is applied to the result set. Because it acts on the results of the GROUP BY clause, aggregate functions can be used in the HAVING clause predicate.
  • The ORDER BY clause is used to identify which columns are used to sort the resulting data, and in which order they should be sorted (options are ascending or descending). The order of rows returned by a SQL query is never guaranteed unless an ORDER BY clause is specified.

The following is an example of a SELECT query that returns a list of expensive books. The query retrieves all rows from the books 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 books table should be included in the result set.

Example 1:
SELECT * 
FROM books
WHERE price > 100.00
ORDER BY title;

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

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

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 books 
NATURAL JOIN book_authors 
GROUP BY title;

Example output might resemble the following:

Title                   Authors
----------------------  -------
SQL Examples and Guide     3
The Joy of SQL             1
How to use Wikipedia       2
Pitfalls of SQL            1
How SQL Saved my Dog       1

Data retrieval is very often combined with data projection when the user is looking for calculated values and not just the verbatim data stored in primitive data types, or when the data needs to be expressed in a form that is different from how it's stored. 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 books
WHERE price > 100.00
ORDER BY title;

Data manipulation

First, there are the standard Data Manipulation Language (DML) elements. DML is the subset of the language used to add, update and delete data:

  • INSERT is used to add rows (formally tuples) to an existing table.
  • UPDATE is used to modify the values of a set of existing table rows.
  • MERGE is used to combine the data of multiple tables. It is something of a combination of 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 an "upsert".
  • DELETE removes zero or more existing rows from a table.
INSERT Example:
INSERT INTO my_table (field1, field2, field3) VALUES ('test', 'N', NULL);
UPDATE Example:
UPDATE my_table SET field1 = 'updated value' WHERE field2 = 'N';
DELETE Example:
DELETE FROM my_table WHERE field2 = 'N';

Transaction controls

Transactions, if available, can be used to wrap around the DML operations:

  • BEGIN WORK (or START TRANSACTION, depending on SQL dialect) can be used to mark the start of a database transaction, which either completes completely 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, so that the state of the data is "rolled back" to the way it was prior to those changes being requested.

COMMIT and ROLLBACK interact with areas such as transaction control and locking. Strictly, both terminate any open transaction and release any locks held on data. In the absence of a BEGIN WORK or similar statement, the semantics of SQL are implementation-dependent.

Example:
BEGIN WORK;
UPDATE inventory SET quantity = quantity - 3 WHERE item = 'pants';
COMMIT;

Data definition

The second group of keywords is the Data Definition Language (DDL). DDL allows the user to define new tables and associated elements. Most commercial SQL databases have proprietary extensions in their DDL, which allow control over nonstandard features of the database system. The most basic items of DDL are the CREATE,ALTER,RENAME,TRUNCATE and DROP statements:

  • CREATE causes an object (a table, for example) to be created within the database.
  • DROP causes an existing object within the database to be deleted, usually irretrievably.
  • TRUNCATE deletes all data from a table (non-standard, but common SQL statement).
  • ALTER statement permits the user to modify 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 third group of SQL keywords is the Data Control Language (DCL). DCL handles the authorization aspects of data and permits the user to control who has access to see or manipulate data within the database. Its two main keywords are:

GRANT
Authorizes one or more users to perform an operation or a set of operations on an object.
REVOKE
Removes or restricts the capability of a user to perform an operation or a set of operations.
Example:
GRANT SELECT, UPDATE ON my_table TO some_user, another_user.

Other

  • ANSI-standard SQL supports double dash, --, as a single line comment identifier (some extensions also support curly brackets or C-style /* comments */ for multi-line comments).
Example:
SELECT * FROM inventory -- Retrieve everything from inventory table

Criticisms of SQL

Technically, SQL is a declarative computer language for use with "SQL databases". Theorists and some practitioners note that many of the original SQL features were inspired by, but in violation of, the relational model for database management and its tuple calculus realization. Recent extensions to SQL achieved relational completeness, but have worsened the violations, as documented in The Third Manifesto.

In addition, there are also some criticisms about the practical use of SQL:

  • Implementations are inconsistent and, usually, incompatible between vendors. In particular date and time syntax, string concatenation, nulls, and comparison case sensitivity often vary from vendor to vendor.
  • The language makes it too easy to do a Cartesian join (joining all possible combinations), which results in "run-away" result sets when WHERE clauses are mistyped. Cartesian joins are so rarely used in practice that requiring an explicit CARTESIAN keyword may be warranted.
  • It is also possible to misconstruct a WHERE on an update or delete, thereby affecting more rows in a table than desired.
  • SQL—and the relational model as it is—offer no standard way for handling tree-structures, i.e. rows recursively referring other rows of the same table. Oracle offers a "CONNECT BY" clause, Microsoft offers recursive joins via Common Table Expressions, other solutions are database functions which use recursion and return a row set, as possible in PostgreSQL with PL/PgSQL.

Alternatives to SQL

A distinction should be made between alternatives to relational query languages and alternatives to SQL. The list below are proposed alternatives to SQL, but are still (nominally) relational. See navigational database for alternatives to relational:

Notes

  1. ^ "A Relational Model of Data for Large Shared Data Banks" E. F. Codd, Communications of the ACM, Vol. 13, No. 6, June 1970, pp. 377-387.
  2. ^ Donald D. Chamberlin and Raymond F. Boyce, 1974. "SEQUEL: A structured English query language", International Conference on Management of Data, Proceedings of the 1974 ACM SIGFIDET (now SIGMOD) workshop on Data description, access and control, Ann Arbor, Michigan, pp. 249–264 [1]
  3. ^ Shelley Doll, 2002-06-19, Is SQL a standard anymore?, builder.com.com
  4. ^ ANSI/ISO/IEC International Standard (IS). Database Language SQL—Part 2: Foundation (SQL/Foundation). 1999
  5. ^ The Java Persistence Query Language

References

See also