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SQL

From Wikipedia, the free encyclopedia

SQL Paradigm: multi-paradigm: object-oriented, functional, procedural

Appeared in: 1969

Developer: IBM

Typing discipline: static, strong

Major implementations: Many

SQL (commonly expanded to Structured Query Language — see History for the term's derivation) is the most popular computer language used to create, modify, retrieve and manipulate data from relational database management systems. The language has evolved beyond its original purpose to support object-relational database management systems. It is an ANSI/ISO standard.

SQL is commonly spoken either as the names of the letters ess-cue-el (IPA: [ˈɛsˈkjuˈɛl]), or, less formally, like the word sequel (IPA: [ˈsiːkwəl]). Concerning the names of major database products (or projects) containing the letters SQL, each has its own convention: MySQL is officially and commonly pronounced "My Ess Cue El"; PostgreSQL is expediently pronounced postgres; and Microsoft SQL Server is commonly spoken as Microsoft-sequel-server.

Contents

1 History

1.1 Standardization

2 Scope

2.1 Reasons for lack of portability

3 SQL keywords

3.1 Data retrieval

3.2 Data manipulation

3.3 Data transaction

3.4 Data definition

3.5 Data control

3.6 Other

4 Database systems using SQL

5 Criticisms of SQL

6 Alternatives to SQL

7 References

8 External links

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. 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, but not strictly faithful to, 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. 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.[1] 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).[1]

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 is often incorrectly cited as beating IBM to market by two years, when in fact they only beat IBM's release of the System/38 by a few weeks. Considerable public interest then developed; soon many other vendors developed versions, and Oracle's future was ensured.

Standardization

SQL was adopted as a standard by ANSI (American National Standards Institute) in 1986 and ISO (International Organization for Standardization) in 1987. ANSI has declared that the official pronunciation for SQL is /ɛs kjuː ɛl/, although many English-speaking database professionals still pronounce it as sequel.[citation needed]

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.

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).

The SQL standard is not freely available. SQL:2003 may be purchased from ISO or ANSI. A late draft 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

The neutrality of this article or section may be compromised by weasel words.

You can help Wikipedia by improving weasel-worded statements.

SQL is defined by both ANSI and ISO. There are many extensions to and variations on the version of the language. Many of these extensions are of a proprietary nature, such as Oracle Corporation's PL/SQL, IBM's SQL PL (SQL Procedural Language) and Sybase / Microsoft's Transact-SQL. Commercial implementations commonly omit support for basic features of the standard, such as the DATE or TIME data types, preferring some variant of their own. SQL code can rarely be ported between database systems without major modifications, in contrast to ANSI C or ANSI Fortran, which can usually be ported from platform to platform without major structural changes.

SQL is designed for a specific, limited purpose — querying data contained in a relational database. As such, it is a set-based, declarative computer language rather than an imperative language such as C or BASIC which, being general-purpose, are designed to solve a much broader set of problems. Language extensions such as PL/SQL bridge this gap to some extent by adding procedural elements, such as flow-of-control constructs. Another approach is to allow programming language code to be embedded in and interact with the database. For example, Oracle and others include Java in the database, while PostgreSQL allows functions to be written in a wide variety of languages, including Perl, Tcl, and C.

SQL contrasts with the more powerful database-oriented fourth-generation programming languages such as Focus or SAS in its relative functional simplicity and simpler command set. This greatly reduces the degree of difficulty involved in maintaining SQL source code, but it also makes programming such questions as 'Who had the top ten scores?' more difficult, leading to the development of procedural extensions, discussed above. However, it also makes it possible for SQL source code to be produced (and optimized) by software, leading to the development of a number of natural language database query languages, as well as 'drag and drop' database programming packages with 'object oriented' interfaces. Often these allow the resultant SQL source code to be examined, for educational purposes, further enhancement, or to be used in a different environment.

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 standard 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.

Some believe the lack of compatibility between database systems is intentional in order to ensure vendor lock-in [citation needed].

SQL keywords

SQL keywords fall into several groups.

Data retrieval

The most frequently used operation in transactional databases is the data retrieval operation. When restricted to data retrieval commands, SQL acts as a declarative language.

SELECT is used to retrieve zero or more rows from one or more tables in a database. In most applications, SELECT is the most commonly used Data Manipulation Language command. In specifying a SELECT query, the user specifies a description of the desired result set, but they do not specify what physical operations must be executed to produce that result set. Translating the query into an efficient query plan is left to the database system, more specifically to the query optimizer.

Commonly available keywords related to SELECT include:

FROM is used to indicate from which tables the data is to be taken, as well as how the tables JOIN to each other.

WHERE is used to identify which rows to be retrieved, or applied to GROUP BY. WHERE is evaluated before the GROUP BY.

GROUP BY is used to combine rows with related values into elements of a smaller set of rows.

HAVING is used to identify which of the "combined rows" (combined rows are produced when the query has a GROUP BY keyword or when the SELECT part contains aggregates), are to be retrieved. HAVING acts much like a WHERE, but it operates on the results of the GROUP BY and hence can use aggregate functions.

ORDER BY is used to identify which columns are used to sort the resulting data.

Example 1:

SELECT * FROM books

WHERE price > 100.00

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.

Example 2:

SELECT books.title, count(*) AS Authors

FROM books

JOIN book_authors

ON books.book_number = book_authors.book_number

GROUP BY books.title

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

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 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 zero or more 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".

TRUNCATE deletes all data from a table (non-standard, but common SQL command).

DELETE removes zero or more existing rows from a table.

Example:

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

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

DELETE FROM my_table WHERE field2 = 'N';

Data transaction

Transaction, if available, can be used to wrap around the DML operations.

START TRANSACTION (or BEGIN WORK, 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 START TRANSACTION or similar statement, the semantics of SQL are implementation-dependent.

Example:

START TRANSACTION;

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 and DROP commands.

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.

Some database systems also have an ALTER command, which 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 UNSIGNED,

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 -- 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

Some SQL servers allow User Defined Functions

Database systems using SQL

Comparison of relational database management systems

Comparison of truly relational database management systems

Comparison of object-relational database management systems

List of relational database management systems

List of object-relational database management systems

List of hierarchical database management systems

Criticisms of SQL

The neutrality of this article is disputed.

Please see the discussion on the talk page.

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:

It does not provide a standard way, or at least a commonly-supported way, to split large commands into multiple smaller ones that reference each other by name. This tends to result in "run-on SQL sentences" and may force one into a deep hierarchical nesting when a graph-like (reference-by-name) approach may be more appropriate and better repetition-factoring.

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.

For larger statements, it is often difficult to factor repeated patterns and expressions into one or fewer places to avoid repetition and avoid having to make the same change to different places in a given statement.

The difference between value-to-column assignment in UPDATE and INSERT syntax is puzzling and confusing to many.

The language cannot easily be extended by programmers or DBAs. Although some variations allow the addition of functions, the functions can only take scalar values and not tables (real or virtual) as arguments. The archaic syntax (above) may be part of the reason for this.

The language makes it too easy to do a Cartesian join, 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.

SQL's set theory techniques and operations usually cannot also apply to column lists. Thus, column lists cannot be computed dynamically.

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.

IBM Business System 12 (IBM BS12)

Tutorial D

TQL - Luca Cardelli (May not be relational)

Top's Query Language - A draft language influenced by IBM BS12. Tentatively renamed to SMEQL to avoid confusion with similar projects called TQL.

Hibernate Query Language[2] (HQL) - A Java-based tool that uses modified SQL

Quel introduced in 1974 by the U.C. Berkeley Ingres project.

Object Query Language - Object Data Management Group.

Datalog

LINQ

References

^ 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

Discussion on alleged SQL flaws (C2 wiki)

Web page about FSQL: References and links.

Galindo J., Urrutia A., Piattini M., "Fuzzy Databases: Modeling, Design and Implementation". Idea Group Publishing Hershey, USA, 2005.

External links

The 1995 SQL Reunion: People, Projects, and Politics (early history of SQL)

SQL:2003, SQL/XML and the Future of SQL (webcast and podcast with Jim Melton, editor of the SQL standard)

TenMinuteTutor guide to SQL

A Gentle Introduction to SQL at SQLzoo

SQL Help and Tutorial

The SQL Language (PostgreSQL specific details included)

SQL Exercises. SQL DML Help and Tutorial

SQL Tutorial.

A free SQL cookbook for all SQL dialects

Online Interactive SQL Tutorials

How well Oracle, DB2, MSSQL support the SQL Standard

SQL Tutorial

Wikibooks Programming has more about this subject:

SQL

Topics in database management systems (DBMS) ( view • talk • edit )

Concepts

Database normalization | Referential integrity | Relational DBMS | Distributed DBMS | ACID

Objects

Topics in SQL

Comparison of syntax

Implementations of database management systems

Types of implementations

Products

Components

Query language | Query optimizer | Query plan | ODBC | JDBC

Lists

List of object-oriented database management systems

List of relational database management systems

List of truly relational database management systems

Preceding:

Subsequent: System R

Retrieved from "http://en.wikipedia.org/wiki/SQL"

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