What is SQL?
Structured query language (SQL) is a programming language for storing and processing information in a relational database. A relational database stores information in tabular form, with rows and columns representing different data attributes and the various relationships between the data values. You can use SQL statements to store, update, remove, search, and retrieve information from the database. You can also use SQL to maintain and optimize database performance.
Structured query language (SQL) is a programming language for storing and processing information in a relational database. A relational database stores information in tabular form, with rows and columns representing different data attributes and the various relationships between the data values. You can use SQL statements to store, update, remove, search, and retrieve information from the database. You can also use SQL to maintain and optimize database performance.
Why is SQL important?
Structured query language (SQL) is a popular query language that is frequently used in all types of applications. Data analysts and developers learn and use SQL because it integrates well with different programming languages. For example, they can embed SQL queries with the Java programming language to build high-performing data processing applications with major SQL database systems such as Oracle or MS SQL Server. SQL is also fairly easy to learn as it uses common English keywords in its statements
Structured query language (SQL) is a popular query language that is frequently used in all types of applications. Data analysts and developers learn and use SQL because it integrates well with different programming languages. For example, they can embed SQL queries with the Java programming language to build high-performing data processing applications with major SQL database systems such as Oracle or MS SQL Server. SQL is also fairly easy to learn as it uses common English keywords in its statements
History of SQL
SQL was invented in the 1970s based on the relational data model. It was initially known as the structured English query language (SEQUEL). The term was later shortened to SQL. Oracle, formerly known as Relational Software, became the first vendor to offer a commercial SQL relational database management system.
SQL was invented in the 1970s based on the relational data model. It was initially known as the structured English query language (SEQUEL). The term was later shortened to SQL. Oracle, formerly known as Relational Software, became the first vendor to offer a commercial SQL relational database management system.
What are SQL commands?
Structured query language (SQL) commands are specific keywords or SQL statements that developers use to manipulate the data stored in a relational database. You can categorize SQL commands as follows.
Structured query language (SQL) commands are specific keywords or SQL statements that developers use to manipulate the data stored in a relational database. You can categorize SQL commands as follows.
Data definition language
Data definition language (DDL) refers to SQL commands that design the database structure. Database engineers use DDL to create and modify database objects based on the business requirements. For example, the database engineer uses the CREATE command to create database objects such as tables, views, and indexes.
Data definition language (DDL) refers to SQL commands that design the database structure. Database engineers use DDL to create and modify database objects based on the business requirements. For example, the database engineer uses the CREATE command to create database objects such as tables, views, and indexes.
Data query language
Data query language (DQL) consists of instructions for retrieving data stored in relational databases. Software applications use the SELECT command to filter and return specific results from a SQL table.
Data query language (DQL) consists of instructions for retrieving data stored in relational databases. Software applications use the SELECT command to filter and return specific results from a SQL table.
Data manipulation language
Data manipulation language (DML) statements write new information or modify existing records in a relational database. For example, an application uses the INSERT command to store a new record in the database.
Data manipulation language (DML) statements write new information or modify existing records in a relational database. For example, an application uses the INSERT command to store a new record in the database.
Data control language
Database administrators use data control language (DCL) to manage or authorize database access for other users. For example, they can use the GRANT command to permit certain applications to manipulate one or more tables.
Database administrators use data control language (DCL) to manage or authorize database access for other users. For example, they can use the GRANT command to permit certain applications to manipulate one or more tables.
Transaction control language
The relational engine uses transaction control language (TCL) to automatically make database changes. For example, the database uses the ROLLBACK command to undo an erroneous transaction.
Here is a list of some common SQL commands:
1. SELECT - retrieves data from one or more tables
2. INSERT - adds new data into a table
3. UPDATE - modifies existing data in a table
4. DELETE - removes data from a table
5. CREATE TABLE - creates a new table
6. ALTER TABLE - modifies the structure of an existing table
7. DROP TABLE - removes a table from the database
8. CREATE INDEX - creates an index for faster data retrieval
9. ALTER INDEX - modifies an existing index
10. DROP INDEX - removes an index from the database
11. JOIN - combines data from multiple tables based on a specified condition
12. GROUP BY - groups rows based on a specified column or set of columns
13. ORDER BY - sorts rows based on a specified column or set of columns
14. LIMIT - limits the number of rows returned by a query
15. DISTINCT - removes duplicate rows from a result set
16. UNION - combines the results of two or more SELECT statements into a single result set
17. HAVING - filters the results of a GROUP BY query based on a specified condition
18. IN - selects data based on a list of specified values
19. BETWEEN - selects data based on a range of values
20. LIKE - selects data based on a pattern matching condition.
These are just some of the most common SQL commands. There are many more advanced SQL commands that can be used to manipulate data and perform complex queries.
constraints
Constraints are rules that are enforced by a relational database management system (RDBMS) to ensure the integrity and consistency of data stored in a database. Constraints are used to prevent invalid data from being inserted or updated in a table.
There are several types of constraints:
1. Primary Key: A primary key is a column or set of columns that uniquely identifies each row in a table. The primary key constraint ensures that the values in the key column(s) are unique and not null.
2. Foreign Key: A foreign key is a column or set of columns in one table that refers to the primary key of another table. The foreign key constraint ensures that the values in the foreign key column(s) exist in the primary key column(s) of the referenced table.
3. Unique: A unique constraint ensures that the values in a column or set of columns are unique and not null.
4. Check: A check constraint specifies a condition that must be true for each row in a table.
5. Not Null: A not null constraint ensures that a column cannot contain null values.
6. Default: A default constraint specifies a default value for a column when no value is specified.
Constraints can be defined when a table is created using the CREATE TABLE statement, or they can be added later using the ALTER TABLE statement. Constraints can also be dropped using the ALTER TABLE statement.
By using constraints, a database administrator can ensure the quality and consistency of the data stored in a database, which is essential for maintaining data integrity and avoiding data corruption.
set operators
Set operators are used in SQL to combine the result sets of two or more SELECT statements into a single result set. There are three set operators in SQL: UNION, INTERSECT, and EXCEPT (or MINUS in some databases).
Here's a brief description of each set operator:
1. UNION: The UNION operator combines the results of two SELECT statements into a single result set that contains all the rows returned by either SELECT statement. The columns in the result set must have the same data type and must appear in the same order in both SELECT statements. Duplicate rows are automatically removed from the result set.
2. INTERSECT: The INTERSECT operator returns the rows that appear in both result sets of two SELECT statements. The columns in the result set must have the same data type and must appear in the same order in both SELECT statements. Duplicate rows are automatically removed from the result set.
3. EXCEPT/MINUS: The EXCEPT operator (also known as MINUS in some databases) returns the rows that appear in the result set of the first SELECT statement but not in the result set of the second SELECT statement. The columns in the result set must have the same data type and must appear in the same order in both SELECT statements. Duplicate rows are automatically removed from the result set.
Set operators are useful when you need to combine data from multiple tables or queries that have similar structures. They can help simplify complex queries and reduce the need for nested subqueries. However, it's important to use them carefully to ensure that the resulting data set is accurate and meaningful.
The relational engine uses transaction control language (TCL) to automatically make database changes. For example, the database uses the ROLLBACK command to undo an erroneous transaction.
Here is a list of some common SQL commands:
1. SELECT - retrieves data from one or more tables
2. INSERT - adds new data into a table
3. UPDATE - modifies existing data in a table
4. DELETE - removes data from a table
5. CREATE TABLE - creates a new table
6. ALTER TABLE - modifies the structure of an existing table
7. DROP TABLE - removes a table from the database
8. CREATE INDEX - creates an index for faster data retrieval
9. ALTER INDEX - modifies an existing index
10. DROP INDEX - removes an index from the database
11. JOIN - combines data from multiple tables based on a specified condition
12. GROUP BY - groups rows based on a specified column or set of columns
13. ORDER BY - sorts rows based on a specified column or set of columns
14. LIMIT - limits the number of rows returned by a query
15. DISTINCT - removes duplicate rows from a result set
16. UNION - combines the results of two or more SELECT statements into a single result set
17. HAVING - filters the results of a GROUP BY query based on a specified condition
18. IN - selects data based on a list of specified values
19. BETWEEN - selects data based on a range of values
20. LIKE - selects data based on a pattern matching condition.
These are just some of the most common SQL commands. There are many more advanced SQL commands that can be used to manipulate data and perform complex queries.
constraints
Constraints are rules that are enforced by a relational database management system (RDBMS) to ensure the integrity and consistency of data stored in a database. Constraints are used to prevent invalid data from being inserted or updated in a table.
There are several types of constraints:
1. Primary Key: A primary key is a column or set of columns that uniquely identifies each row in a table. The primary key constraint ensures that the values in the key column(s) are unique and not null.
2. Foreign Key: A foreign key is a column or set of columns in one table that refers to the primary key of another table. The foreign key constraint ensures that the values in the foreign key column(s) exist in the primary key column(s) of the referenced table.
3. Unique: A unique constraint ensures that the values in a column or set of columns are unique and not null.
4. Check: A check constraint specifies a condition that must be true for each row in a table.
5. Not Null: A not null constraint ensures that a column cannot contain null values.
6. Default: A default constraint specifies a default value for a column when no value is specified.
Constraints can be defined when a table is created using the CREATE TABLE statement, or they can be added later using the ALTER TABLE statement. Constraints can also be dropped using the ALTER TABLE statement.
By using constraints, a database administrator can ensure the quality and consistency of the data stored in a database, which is essential for maintaining data integrity and avoiding data corruption.
set operators
Set operators are used in SQL to combine the result sets of two or more SELECT statements into a single result set. There are three set operators in SQL: UNION, INTERSECT, and EXCEPT (or MINUS in some databases).
Here's a brief description of each set operator:
1. UNION: The UNION operator combines the results of two SELECT statements into a single result set that contains all the rows returned by either SELECT statement. The columns in the result set must have the same data type and must appear in the same order in both SELECT statements. Duplicate rows are automatically removed from the result set.
2. INTERSECT: The INTERSECT operator returns the rows that appear in both result sets of two SELECT statements. The columns in the result set must have the same data type and must appear in the same order in both SELECT statements. Duplicate rows are automatically removed from the result set.
3. EXCEPT/MINUS: The EXCEPT operator (also known as MINUS in some databases) returns the rows that appear in the result set of the first SELECT statement but not in the result set of the second SELECT statement. The columns in the result set must have the same data type and must appear in the same order in both SELECT statements. Duplicate rows are automatically removed from the result set.
Set operators are useful when you need to combine data from multiple tables or queries that have similar structures. They can help simplify complex queries and reduce the need for nested subqueries. However, it's important to use them carefully to ensure that the resulting data set is accurate and meaningful.
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