SQL

SQL (Structured Query Language) is a database computer language designed for managing data in relational database management systems (RDBMS). Its scope includes data query and update, schema creation and modification, and data access control. SQL was one of the first languages for Edgar F. Codd's relational model in his influential 1970 paper, "A Relational Model of Data for Large Shared Data Banks" and became the most widely used language for relational databases.

Importance to GIS
A GIS most often requires very large databases to store vast amounts of geographic data. SQL becomes an essential tool to manage these databases. SQL expressions are also used in many GIS software operations that analyze geographic data. Therefore, it would be very difficult to manage a GIS without the use of SQL.

History
SQL was developed at IBM by Andrew Richardson, Donald C. Messerly 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. IBM patented this version of SQL in 1985.

During the 1970s, a group at IBM San Jose Research Laboratory developed the System R relational database management system. Donald D. Chamberlin and Raymond F. Boyce of IBM subsequently created the Structured English Query Language (SEQUEL or SEQL) to manage data stored in System R. The acronym SEQUEL was later changed to SQL because "SEQUEL" was a trademark of the UK-based Hawker Siddeley aircraft company.

The first Relational Database Management System (RDBMS) was RDMS, developed at MIT in the early 1970s and Ingres, developed in 1974 at U.C. Berkeley. Ingres implemented a query language known as QUEL, which was later supplanted in the marketplace by SQL.

In the late 1970s, Relational Software, Inc. (now Oracle Corporation) saw the potential of the concepts described by Codd, Chamberlin, and Boyce and developed their own SQL-based RDBMS with aspirations of selling it to the U.S. Navy, Central Intelligence Agency, and other U.S. government agencies. In the summer of 1979, Relational Software, Inc. introduced the first commercially available implementation of SQL, Oracle V2 (Version2) for VAX computers. Oracle V2 beat IBM's release of the System/38 RDBMS to market by a few weeks.

After testing SQL at customer test sites to determine the usefulness and practicality of the system, IBM began developing commercial products based on their System R prototype including System/38, SQL/DS, and DB2, which were commercially available in 1979, 1981, and 1983, respectively.

Common criticisms of SQL include a perceived lack of cross-platform portability between vendors, inappropriate handling of missing data (see Null (SQL)), and unnecessarily complex and occasionally ambiguous language grammar and semantics.

Language elements


The SQL language is sub-divided into several language elements, including:
 * Clauses, which are in some cases optional, constituent components of statements and queries.
 * 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 which are used to limit the effects of statements and queries, or to change program flow.
 * Queries which retrieve data based on specific criteria.
 * Statements which may have a persistent effect on schemas and data, or which may control transactions, program flow, connections, sessions, or diagnostics.
 * SQL statements also include the semicolon (";") statement terminator. Though not required on every platform, it is defined as a standard part of the SQL grammar.
 * Insignificant whitespace is generally ignored in SQL statements and queries, making it easier to format SQL code for readability.

Queries
The most common operation in SQL is the query, which is performed with the declarative  statement. retrieves data from one or more tables, or expressions. Standard SQL statements have no persistent effects on the database. Some non-standard implementations of  can have persistent effects, such as the   syntax that exists in some databases.

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  keyword. An asterisk (" ") can also be used to specify that the query should return all columns of the queried tables. is the most complex statement in SQL, with optional keywords and clauses that include:
 * The  clause which indicates the table(s) from which data is to be retrieved. The   clause can include optional   subclauses to specify the rules for joining tables.
 * The  clause includes a comparison predicate, which restricts the rows returned by the query. The   clause eliminates all rows from the result set for which the comparison predicate does not evaluate to True.
 * The  clause is used to project rows having common values into a smaller set of rows.   is often used in conjunction with SQL aggregation functions or to eliminate duplicate rows from a result set. The   clause is applied before the   clause.
 * The  clause includes a predicate used to filter rows resulting from the   clause. Because it acts on the results of the   clause, aggregation functions can be used in the   clause predicate.
 * The  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   clause, the order of rows returned by an SQL query is undefined.

The following is an example of a  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.

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.

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:

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.

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.

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). 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  and   test whether data is or is not Null.

Note that SQL returns only results for which the WHERE clause returns a value of True. That is, it excludes results with values of False, but also those whose value is Unknown.

Universal quantification is not explicitly supported by SQL, and must be worked out as a negated existential quantification.

SQL also provides the spaceship operator,, to mean NULL-safe equality. That is,

Data manipulation
The Data Manipulation Language (DML) is the subset of SQL used to add, update and delete data:
 * adds rows (formally tuples) to an existing table, e.g.,:
 * modifies a set of existing table rows, e.g.,:
 * removes existing rows from a table, e.g.,:
 * deletes all data from a table in a very fast way. It usually implies a subsequent COMMIT operation.
 * is used to combine the data of multiple tables. It combines the  and   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:


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

Once the  statement completes, the transaction's changes cannot be rolled back.

and  terminate the current transaction and release data locks. In the absence of a  or similar statement, the semantics of SQL are implementation-dependent. Example: A classic bank transfer of funds transaction.

Data definition
The Data Definition Language (DDL) manages table and index structure. The most basic items of DDL are the,  ,  ,   and   statements:

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

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


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

Example:

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:

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.

Criticisms of SQL
SQL is a declarative computer language for use with relational databases. Interestingly, many of the original SQL features were inspired by, but violated, the semantics of the relational model and its tuple calculus realization. Recent extensions to SQL achieved relational completeness, but have worsened the violations, as documented in The Third Manifesto.

Practical criticisms of SQL include:
 * Implementations are inconsistent and, usually, incompatible between vendors. In particular date and time syntax, string concatenation, nulls, and comparison case sensitivity 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  clauses are mistyped. Cartesian joins are so rarely used in practice that requiring an explicit   keyword may be warranted. (SQL 1992 introduced the   keyword that allows the user to make clear that a Cartesian join is intended, but the shorthand "comma-join" with no predicate is still acceptable syntax, which still invites the same mistake.)
 * It is also possible to misconstruct a  on an update or delete, thereby affecting more rows in a table than desired. (A work-around is to use transactions or habitually type in the WHERE clause first, then fill in the rest later.)
 * The grammar of SQL is perhaps unnecessarily complex, borrowing a COBOL-like keyword approach, when a function-influenced syntax could result in more re-use of fewer grammar and syntax rules.

Cross-vendor portability
Popular implementations of SQL commonly omit support for basic features of Standard SQL, such as the  or   data types. As a result, SQL code can rarely be ported between database systems without modifications.

There are several reasons for this lack of portability between database systems:
 * The complexity and size of the SQL standard means that most implementors do not support the entire standard.
 * The standard does not specify database behavior in several important areas (e.g., indexes, file storage...), leaving implementations 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 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.
 * Software vendors often desire to create incompatabilities with other products, as it provides a strong incentive for their existing users to remain loyal (see vendor lock-in).

Standardization
SQL was adopted as a standard by the American National Standards Institute (ANSI) in 1986 as SQL-86 and International Organization for Standardization (ISO) in 1987. The original SQL standard declared that the official pronunciation for SQL is "es queue el". Many English-speaking database professionals still use the nonstandard pronunciation (like the word "sequel"). SEQUEL was an earlier IBM database language, a predecessor to the SQL language.

Until 1996, the National Institute of Standards and Technology (NIST) data management standards program certified SQL DBMS compliance with the SQL standard. Vendors now self-certify the compliance of their products.

The SQL standard has gone through a number of revisions, as shown below:

Interested parties may purchase SQL standards documents from ISO or ANSI. A draft of SQL:2008 is freely available as a zip archive.

Standard structure
The SQL standard is divided into several parts, including:

SQL/Foundation, defined in ISO/IEC 9075, Part 2. This part of the standard contains the most central elements of the language. It consists of both mandatory and optional features.

The SQL/CLI, or Call-Level Interface, part is defined in ISO/IEC 9075, Part 3. SQL/CLI defines common interfacing components (structures and procedures) that can be used to execute SQL statements from applications written in other programming languages. SQL/CLI is defined in such a way that SQL statements and SQL/CLI procedure calls are treated as separate from the calling application's source code. Open Database Connectivity is a well-known superset of SQL/CLI. This part of the standard consists solely of mandatory features.

The SQL/PSM, or Persistent Stored Modules, part is defined by ISO/IEC 9075, Part 4. SQL/PSM standardizes procedural extensions for SQL, including flow of control, condition handling, statement condition signals and resignals, cursors and local variables, and assignment of expressions to variables and parameters. In addition, SQL/PSM formalizes declaration and maintenance of persistent database language routines (e.g., "stored procedures"). This part of the standard consists solely of optional features.

The SQL/MED, or Management of External Data, part is defined by ISO/IEC 9075, Part 9. SQL/MED provides extensions to SQL that define foreign-data wrappers and datalink types to allow SQL to manage external data. External data is data that is accessible to, but not managed by, an SQL-based DBMS. This part of the standard consists solely of optional features.

The SQL/OLB, or Object Language Bindings, part is defined by ISO/IEC 9075, Part 10. SQL/OLB defines the syntax and symantics of SQLJ, which is SQL embedded in Java. The standard also describes mechanisms to ensure binary portability of SQLJ applications, and specifies various Java packages and their contained classes. This part of the standard consists solely of optional features.

The SQL/Schemata, or Information and Definition Schemas, part is defined by ISO/IEC 9075, Part 11. SQL/Schemata defines the Information Schema and Definition Schema, providing a common set of tools to make SQL databases and objects self-describing. These tools include the SQL object identifier, structure and integrity constraints, security and authorization specifications, features and packages of ISO/IEC 9075, support of features provided by SQL-based DBMS implementations, SQL-based DBMS implementation information and sizing items, and the values supported by the DBMS implementations. This part of the standard contains both mandatory and optional features.

The SQL/JRT, or SQL Routines and Types for the Java Programming Language, part is defined by ISO/IEC 9075, Part 13. SQL/JRT specifies the ability to invoke static Java methods as routines from within SQL applications. It also calls for the ability to use Java classes as SQL structured user-defined types. This part of the standard consists solely of optional features.

The SQL/XML, or XML-Related Specifications, part is defined by ISO/IEC 9075, Part 14. SQL/XML specifies SQL-based extensions for using XML in conjunction with SQL. The XML data type is introduced, as well as several routines, functions, and XML-to-SQL data type mappings to support manipulation and storage of XML in an SQL database. This part of the standard consists solely of optional features.

Alternatives to SQL
A distinction should be made between alternatives to relational query languages and alternatives to SQL. Below are proposed relational alternatives to SQL. See navigational database for alternatives to relational:
 * .QL - object-oriented Datalog
 * 4D Query Language (4D QL)
 * Aldat Relational Algebra and Domain algebra
 * Datalog
 * Hibernate Query Language (HQL) - A Java-based tool that uses modified SQL
 * IBM Business System 12 (IBM BS12)
 * ISBL
 * Java Persistence Query Language (JPQL) - The query language used by the Java Persistence API in Java EE5
 * LINQ
 * Object Query Language
 * QBE (Query By Example) created by Moshè Zloof, IBM 1977
 * QLC - Query Interface to Mnesia, ETS, Dets, etc (Erlang programming language)
 * Quel introduced in 1974 by the U.C. Berkeley Ingres project.
 * Tutorial D
 * XQuery

GIS&T Body of Knowledge Concept
SQL is referred to in sections AM2-2 and AM2-3 in the 2006 GIS&T Body of Knowledge.