Handbok Databaskommunikation

Databas

Google Cloud

Big Query

API

Protokoll

Säkerhet

MySQL Workbench

Explore

SQL

Basics

30 Bra Queries

Cheat Sheet

SQL stands for Structured Query Language. SQL commands are the instructions used to communicate with a database to perform tasks, functions, and queries with data.

SQL commands can be used to search the database and to do other functions like creating tables, adding data to tables, modifying data, and dropping tables.

Here is a list of basic SQL commands (sometimes called clauses) you should know if you are going to work with SQL.

SELECT and FROM

The SELECT part of a query determines which columns of the data to show in the results. There are also options you can apply to show data that is not a table column.

The example below shows three columns SELECTed FROM the “student” table and one calculated column. The database stores the studentID, FirstName, and LastName of the student. We can combine the First and the Last name columns to create the FullName calculated column.

SELECT studentID, FirstName, LastName, FirstName + ' ' + LastName AS FullName

FROM student;

+-----------+-------------------+------------+------------------------+

+-----------+-------------------+------------+------------------------+

+-----------+-------------------+------------+------------------------+

9 rows in set (0.00 sec)

CREATE TABLE

CREATE TABLE does just what it sounds like: it creates a table in the database. You can specify the name of the table and the columns that should be in the table.

CREATE TABLE table_name (

column_1 datatype,

column_2 datatype,

column_3 datatype

);

ALTER TABLE

⁠

ALTER TABLE⁠

changes the structure of a table. Here is how you would add a column to a database:

ALTER TABLE table_name

ADD column_name datatype;

CHECK

The CHECK constraint is used to limit the value range that can be placed in a column.

If you define a CHECK constraint on a single column it allows only certain values for this column. If you define a CHECK constraint on a table it can limit the values in certain columns based on values in other columns in the row.

The following SQL creates a CHECK constraint on the “Age” column when the “Persons” table is created. The CHECK constraint ensures that you can not have any person below 18 years.

CREATE TABLE Persons (

ID int NOT NULL,

LastName varchar(255) NOT NULL,

FirstName varchar(255),

Age int,

CHECK (Age>=18)

);

To allow naming of a CHECK constraint, and for defining a CHECK constraint on multiple columns, use the following SQL syntax:

CREATE TABLE Persons (

ID int NOT NULL,

LastName varchar(255) NOT NULL,

FirstName varchar(255),

Age int,

City varchar(255),

CONSTRAINT CHK_Person CHECK (Age>=18 AND City='Sandnes')

);

WHERE

(AND, OR, IN, BETWEEN, and LIKE)

The WHERE clause is used to limit the number of rows returned.

As an example, first we will show you a SELECT statement and results without a WHERE statement. Then we will add a WHERE statement that uses all five qualifiers above.

SELECT studentID, FullName, sat_score, rcd_updated FROM student;

+-----------+------------------------+-----------+---------------------+

+-----------+------------------------+-----------+---------------------+

| 1 | Monique Davis | 400 | 2017-08-16 15:34:50 |

| 2 | Teri Gutierrez | 800 | 2017-08-16 15:34:50 |

| 3 | Spencer Pautier | 1000 | 2017-08-16 15:34:50 |

| 4 | Louis Ramsey | 1200 | 2017-08-16 15:34:50 |

| 5 | Alvin Greene | 1200 | 2017-08-16 15:34:50 |

| 6 | Sophie Freeman | 1200 | 2017-08-16 15:34:50 |

| 7 | Edgar Frank "Ted" Codd | 2400 | 2017-08-16 15:35:33 |

| 8 | Donald D. Chamberlin | 2400 | 2017-08-16 15:35:33 |

| 9 | Raymond F. Boyce | 2400 | 2017-08-16 15:35:33 |

+-----------+------------------------+-----------+---------------------+

9 rows in set (0.00 sec)

Now, we'll repeat the SELECT query but we'll limit the rows returned using a WHERE statement.

STUDENT studentID, FullName, sat_score, recordUpdated

FROM student

WHERE (studentID BETWEEN 1 AND 5 OR studentID = 8)

AND

sat_score NOT IN (1000, 1400);

+-----------+----------------------+-----------+---------------------+

+-----------+----------------------+-----------+---------------------+

| 1 | Monique Davis | 400 | 2017-08-16 15:34:50 |

| 2 | Teri Gutierrez | 800 | 2017-08-16 15:34:50 |

| 4 | Louis Ramsey | 1200 | 2017-08-16 15:34:50 |

| 5 | Alvin Greene | 1200 | 2017-08-16 15:34:50 |

| 8 | Donald D. Chamberlin | 2400 | 2017-08-16 15:35:33 |

+-----------+----------------------+-----------+---------------------+

5 rows in set (0.00 sec)

UPDATE

To update a record in a table you use the UPDATE statement.

Use the WHERE condition to specify which records you want to update. It is possible to update one or more columns at a time. The syntax is:

UPDATE table_name

SET column1 = value1,

column2 = value2, ...

WHERE condition;

Here is an example updating the Name of the record with Id 4:

UPDATE Person

SET Name = “Elton John”

WHERE Id = 4;

You can also update columns in a table by using values from other tables. Use the JOIN clause to get data from multiple tables. The syntax is:

UPDATE table_name1

SET table_name1.column1 = table_name2.columnA

table_name1.column2 = table_name2.columnB

FROM table_name1

JOIN table_name2 ON table_name1.ForeignKey = table_name2.Key

Here is an example updating Manager of all records:

UPDATE Person

SET Person.Manager = Department.Manager

FROM Person

JOIN Department ON Person.DepartmentID = Department.ID

GROUP BY

GROUP BY allows you to combine rows and aggregate data.

Here is the syntax of GROUP BY:

SELECT column_name, COUNT(*)

FROM table_name

GROUP BY column_name;

HAVING

HAVING allows you to filter the data aggregated by the GROUP BY clause so that the user gets a limited set of records to view.

Here is the syntax of HAVING:

SELECT column_name, COUNT(*)

FROM table_name

GROUP BY column_name

HAVING COUNT(*) > value;

AVG()

“Average” is used to calculate the average of a numeric column from the set of rows returned by a SQL statement.

Here is the syntax for using the function:

SELECT groupingField, AVG(num_field)

FROM table1

GROUP BY groupingField

Here’s an example using the student table:

SELECT studentID, FullName, AVG(sat_score)

FROM student

GROUP BY studentID, FullName;

AS

AS allows you to rename a column or table using an alias.

SELECT user_only_num1 AS AgeOfServer, (user_only_num1 - warranty_period) AS NonWarrantyPeriod FROM server_table

This results in output as below.

+-------------+------------------------+

| AgeOfServer | NonWarrantyPeriod |

+-------------+------------------------+

| 36 | 24 |

| 24 | 12 |

Want to print your doc?
This is not the way.

Try clicking the ⋯ next to your doc name or using a keyboard shortcut (

CtrlP

) instead.