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* The language makes it too easy to do a [[Cartesian product|Cartesian]] [[Join (SQL)|join]], which results in "run-away" result sets when <code>WHERE</code> clauses are mistyped. Cartesian joins are so rarely used in practice that requiring an explicit <code>CARTESIAN</code> keyword may be warranted.
* The language makes it too easy to do a [[Cartesian product|Cartesian]] [[Join (SQL)|join]], which results in "run-away" result sets when <code>WHERE</code> clauses are mistyped. Cartesian joins are so rarely used in practice that requiring an explicit <code>CARTESIAN</code> 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.

* The difference between value-to-column assignment in UPDATE and INSERT can result in confusion and added work for automated SQL code generation modules.

* 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. (Views, and stored procedures can help with this, but often require special database privileges and are not really meant for single-query usage.) Here is an illustration for a "typo finder" query:

'''Sample Table "codeTable"'''
locat code descript
----- ---- --------
10 AA Foo Bar
20 AA Foo Baar
30 AA Foo Bar
10 BB Glab Zab
20 BB Glab Zab
...etc...

'''Sample Query to Find Data-Entry Errors'''

select *
from codeTable
where locat not in (30, 50)
and code not in
(
select code
from
(select code, descript --(gets unique code-and-descript combos)
from codeTable
where locat not in (30, 50)
group by code, descript
)
group by code
having count(*) = 1
)
order by code, locat

Here we have a table of codes in which we want to find and study typos in the descriptions that are supposed to repeat for each location. For example, the second row in the sample data has the typo "Baar". (Perhaps the repetition is bad normalization, but sometimes one has to deal with such data from old systems.)

In this case we want to ignore codes from location 30 and 50 because we know they are not being used right now and thus we don't care to inspect them. To do it properly, we have to apply the filter in two different places. A language which can create a temporary sub-query and then reference that sub-query by name would result in better repetition factoring, reducing the number of places that the filtering criteria have to be applied or changed, such as if we have to change the location exclusion list. Hypothetical fix:

select * into $temp from codeTable
where locat not in (30, 50);
--
select *
from $temp
where code not in
(
select code
from
(select code, descript --(gets unique code-and-descript combos)
from $temp
group by code, descript
)
group by code
having count(*) = 1
)
order by code, locat;

Here the name "$temp" is a temporary or virtual table that is used only by this group of queries. The list of exception locations only has to be kept in one place. The difference is not significant for this example, but if the filtering criteria (WHERE clause) is complex then the difference becomes significant.


==Alternatives to SQL==
==Alternatives to SQL==

Revision as of 00:12, 22 December 2006

SQL
Paradigmmulti-paradigm: object-oriented, functional, procedural
Designed byDonald D. Chamberlin and Raymond F. Boyce
DeveloperIBM
First appeared1969
Stable release
SQL:2003 / 2003
Typing disciplinestatic, strong
Websitewww.iso.org/standard/76583.html
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 (which had been the predecessor to PostgreSQL); and Microsoft SQL Server is commonly spoken as Microsoft-sequel-server.

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 (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).

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

SQL is defined by both ANSI and ISO.

Extensions to and variations of the standards exist: Oracle Corporation's PL/SQL, IBM's SQL PL (SQL Procedural Language) and Sybase / Microsoft's Transact-SQL, which are of a proprietary nature. 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.

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, 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.

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.

Data retrieval is very often combined with data projection; usually it isn't the verbatum 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. A common example would be:

  • SELECT UnitCost * Quantity As TotalCost FROM Orders
Example 1:
  SELECT * FROM books
  WHERE price > 100.00 and price < 150.00
  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 and less than 150.00. 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.
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';

Transaction Control

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 -- 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

Database systems using SQL

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, 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.

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. ^ 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. Discussion on alleged SQL flaws (C2 wiki)
  2. Web page about FSQL: References and links.
  3. Galindo J., Urrutia A., Piattini M., "Fuzzy Databases: Modeling, Design and Implementation". Idea Group Publishing Hershey, USA, 2005.
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