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SQL

Paradigm: multi-paradigm
Appeared in: 1974
Designed by: Donald D. Chamberlin and Raymond F. Boyce
Developer: IBM
Typing discipline: static, strong
Major implementations: Many
 

Structured Query Language (SQL) is the most popular computer language used to create, retrieve, update and delete (see also: CRUD) data from relational database management systems. The language has evolved beyond its original purpose, and now supports object-relational database management systems. SQL has been standardized by both ANSI and ISO.

SQL is commonly spoken either as the names of the letters ess-cue-el (IPA: [ˈɛsˈkjuˈɛl]), or like the word sequel (IPA: [ˈsiːkwəl]). The official pronunciation of SQL according to ANSI is ess-cue-el. However, each of the major database products (or projects) containing the letters SQL has its own convention: MySQL is officially and commonly pronounced “My Ess Cue El“; PostgreSQL is expediently pronounced postgres (being the name of the predecessor to PostgreSQL); and Microsoft SQL Server is commonly spoken as Microsoft-sequel-server.[citation needed]

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 Transaction Controls
    • 3.4 Data definition
    • 3.5 Data control
    • 3.6 Other
  • 4 Criticisms of SQL
  • 5 Alternatives to SQL
  • 6 References
  • 7 See also
  • 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.[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, 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.[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).[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 1992 and ISO (International Organization for Standardization) in 1987.

The SQL standard has gone through a number of revisions:

Year Name Alias Comments

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

SQL is designed for a specific purpose: to query data contained in a relational database. SQL is a set-based, Declarative programming language, not an imperative language such as C or BASIC.

Language extensions such as Oracle Corporation’s 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, and SQL Server 2005 allows any .NET language to be hosted within the database server process, while PostgreSQL allows functions to be written in a wide variety of languages, including Perl, Tcl, and C.

Extensions to and variations of the standards exist. Commercial implementations commonly omit support for basic features of the standard, such as the DATE or TIME data types, preferring variations 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.

PL/SQL, IBM’s SQL PL (SQL Procedural Language) and Sybase / Microsoft’s Transact-SQL are of a proprietary nature because the procedural programming language they present are non-standardized.

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

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.

Data retrieval is very often combined with data projection; usually it isn’t the verbatim data stored in 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:
  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“.
  • 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

Transaction, 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 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.
  • TRUNCATE deletes all data from a table (non-standard, but common SQL command).
  • ALTER command 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 easy to accidentally omit a WHERE on an update or delete, thereby affecting all rows in a table.[citation needed]
  • 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, other solutions are database functions which use recursion and return a row set, as possible in Postgresql with PL/PgSQL and other databases.

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:

References

 

 

  1. ^ http://www.acm.org/classics/nov95/toc.html
  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
  3. ^ http://java.sun.com/javaee/5/docs/tutorial/doc/QueryLanguage.html

Remember: CATALONIA IS NOT SPAIN!

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