SQL Cheat Sheet

Last modified: September 08, 2020 • Reading Time: 5 minutes

  1. Data Retrieval
  2. Table Modification
  3. Aggregate Functions
  4. Joins
  5. Database Object Creation & Modification

Data Retrieval

SELECT

A SELECT statement is used to retrieve data from a database. It is the starting point for all other work done in SQL. To use, write SELECT, then list the fields to be retrieved separated by commas. Next, specify where the data is to be retrieved from by using FROM and the table name.

SELECT field1, field2, field3 …
FROM tablename;

Alternately, if you wanted to select all the fields in a table, you can indicate this using the * character. It would look like this:

SELECT *
FROM tablename;

If we wish to modify the results returned, we have the following commands available for our use:

DISTINCT

DISTINCT is used with the SELECT statement to return only unique records across the fields selected. To do this with only 1 field and return the unique values in that field, it would look like this:

SELECT DISTINCT field1
FROM tablename;

When used with 2 or more fields, DISTINCT will return all the records that are unique combinations across the fields selected.

SELECT DISTINCT field1, field2, field3
FROM tablename;

For example, from the following table:

Color Quantity Group
Red 10 A
Red 10 A
Blue 20 A
Green 15 B
Blue 20 A
Red 15 B
Green 40 B
Yellow 20 B

SELECT DISTINCT Color, Quantity, Group would return:

Color Quantity Group
Red 10 A
Blue 20 A
Green 15 B
Red 15 B
Green 40 B
Yellow 20 B

You can see that the query has looked across all the fields being selected and has only returned a single unique occurrence of each record. (The highlighted records above show where duplicate records were eliminated.)

WHERE

The WHERE clause is used with SELECT to filter the returned records based on specified criteria. The syntax would be similar to:

SELECT field1, field2,…, fieldn …
FROM tablename
WHERE fieldn = definition;

Note that WHERE can be used with many different operators besides the = operator shown in the example. Possible operators include:

= Equal to

Greater than < Less than = Greater than or equal <= Less than or equal <> Not equal

BETWEEN Between specified endpoints of a range

LIKE Matching to a pattern

IN Matching to 1 of several specified options

AND, OR, NOT

AND, OR, and NOT can be used with the WHERE clause to expand and further define the filter. These enables the user to return more refined query results.

Use of AND would follow this syntax:

SELECT field1, field2, field3 …
FROM tablename
WHERE condition1 AND condition2 AND condition3 …;

Use of OR would follow this syntax:

SELECT field1, field2, field3 …
FROM tablename
WHERE condition1 OR condition2 OR condition3 …;

Use of NOT would follow this syntax:

SELECT field1, field2, field3 …
FROM tablename
WHERE NOT condition;

ORDER BY

It may be desirable to return query results in a prescribed order. To do this the ORDER BY clause may be used. Default ordering is alphabetic for text fields and smallest to largest for numeric fields.

SELECT field1, field2, … fieldn …
FROM tablename
ORDER BY fieldn;

If you desire, you can specify to order either ascending or descending:

SELECT field1, field2, … fieldn …
FROM tablename
ORDER BY fieldn ASC;

Or

SELECT field1, field2, … fieldn …
FROM tablename
ORDER BY fieldn DESC;

You can also specify more than 1 field to order by. SQL will order from the first field listed, then secondarily from the next field listed, and so forth. You can use ASC and DESC as you choose, attached to each field. As an example, first ordering by field1 ascending, then field2 descending would look like this:

SELECT field1, field2, … fieldn …
FROM tablename
ORDER BY field1 ASC, field2 DESC;

SELECT TOP

SELECT TOP is used to retrieve a smaller subset of records matching to a specified condition – either percentage of records or number of records.

For percentage of records you specify a percentage and then PERCENT:

SELECT TOP 10 PERCENT field1, field2, field3 …
FROM tablename;

For number or records you merely specify the number of records:

SELECT TOP 50 field1, field2, field3 …
FROM tablename;

LIKE

LIKE is used with the WHERE clause to define a pattern as the condition. When records match the pattern specified by the LIKE operator, they are returned as results of the query.

The wildcards used to help define the pattern are:

% The percent symbol replaces any number of characters, including zero.

_ The underscore replaces a single character.

An example using the % wildcard would look like this:

SELECT *
FROM tablename
WHERE field1 LIKE ‘a%’

Note that the pattern description is always enclosed in single quotes. The example above would return all records where the value in field1 began with the letter “a” followed by any number of characters or no other characters.

IN

The IN operator allows you to specify a list of values that each will satisfy the condition of a WHERE clause. Any record which matches to 1 of the list items is returned.

SELECT field1, field2, … fieldn …
FROM tablename
WHERE fieldn IN ( ‘Value1’, ‘Value2’, ‘Value3’ );

In the example above, anytime Value1, Value2, or Value3 appeared in fieldn, its record would be returned in the query result.

BETWEEN

The BETWEEN operator is used with WHERE to select values within a defined range, inclusive of the endpoints. It can be used with numeric values, dates, and text.

SELECT *
FROM tablename
WHERE fieldn BETWEEN value1 AND value2;

NULL

The NULL operator is used in SQL to test for null values and only return those records:

SELECT *
FROM tablename
WHERE fieldn IS NULL;

Alternatively, by pairing NULL with IS NOT, one can return only the records where there are non-null values:

SELECT *
FROM tablename
WHERE fieldn IS NOT NULL;

AS

In SQL, the AS command is used to alias a field being returned by a query:

SELECT
field1 AS name1,
field2 AS name2,
FROM tablename;

This effectively renames the field(s) in the query results with a temporary name (the respective alias given).

UNION

The UNION operator is used to combine the result sets of 2 or more SELECT statements. In order for this to work however, several rules must be followed:

  • Each SELECT statement must return the same number of fields
  • Each SELECT statement must return fields with similar data types
  • Each SELECT statement must return those fields in the same order

    SELECT fieldnames FROM table1 UNION SELECT fieldnames FROM table2;

When the UNION operator combines the result sets, it looks across all the records and removes any duplicate records. To combine the result sets and retain any duplicated records, use UNION ALL:

SELECT fieldnames FROM table1
UNION ALL
SELECT fieldnames FROM table2;

INTERSECT

INTERSECT functions similarly to UNION, however rather than keeping only unique records, INTERSECT looks across 2 or more SELECT statement result sets and only returns those records that are common between each result set.

SELECT fieldnames FROM table1
INTERSECT
SELECT fieldnames FROM table2;

EXCEPT

EXCEPT also functions similarly to UNION and is the inverse of INTERSECT. EXCEPT looks at the result sets for 2 SELECT statements and only returns the records from the first SELECT statement that are not found in the results of the second SELECT statement.

SELECT fieldnames FROM table1
EXCEPT
SELECT fieldnames FROM table2;

GROUP BY

GROUP BY is used to group the records in a result set by a designated field. It is most commonly used with one of the aggregate functions (COUNT, SUM, MAX, MIN, AVG). For example:

SELECT
COUNT field1,
field 2,
…
fieldn
FROM tablename
GROUP BY field2;

HAVING

HAVING is used in the same way as WHERE, but since WHERE cannot be used with aggregate functions, HAVING may be used to impose a condition on the aggregated result set.

SELECT field1, field2, … fieldn
FROM tablename
GROUP BY fieldn
HAVING condition;

2. Table Modification

INSERT INTO

INSERT INTO is used in insert new records into a table. These records may be copied from another table by pairing with SELECT, or their data may be specified using VALUES. Here are examples of the syntax for each:

Here is an example which copies records from table2 into table1:

INSERT INTO table1 ( field1, field2, field3 )
SELECT field1, field2, field3 FROM table2;

In this next example, new records are created, and the data is specified using VALUES:

INSERT INTO table1 (
field1,
field2,
field3
)
VALUES
( value1, value 2, value3 ),
( value1, value 2, value3 ),
( value1, value 2, value3 );

3. Aggregate Functions

The following functions can be used to aggregate data and produce a designated output for reporting:

COUNT

COUNT returns a count of the records matching to a specified criteria. It is common to use WHERE and GROUP BY with these functions. Here is an example of COUNT:

SELECT
COUNT(field1),
field2
FROM tablename
WHERE condition
GROUP BY field2;

AVG

AVG returns the numeric average of the records within a specified field:

SELECT
AVG(field1),
FROM tablename
WHERE condition;

SUM

SUM returns the numeric sum of the records within a specified field:

SELECT
SUM(field1),
FROM tablename
WHERE condition;

MIN / MAX

MIN returns numeric minimum value for a specified field. MAX returns numeric maximum value for a specified field. Their use would look like this:

SELECT
MIN(field1),
FROM tablename
WHERE condition;

Or

SELECT
MAX(field1),
FROM tablename
WHERE condition;

4. Joins

Joins are used in SQL to combine data from multiple tables based on fields common to both tables. Fields with related data are identified and joined. Once this linking is established, the data may be queried and used in its combined format.

LEFT JOIN

The LEFT JOIN returns all records from table1 (the left table) along with all matching records from table2 (the right table).

SELECT field1, field 2 … fieldn
FROM table1
LEFT JOIN _table2_
ON table1.fieldn = table2.fieldn;

RIGHT JOIN

The RIGHT JOIN returns all records from table2 (the right table) along with all matching records from table1 (the left table).

SELECT field1, field 2 … fieldn
FROM table1
LEFT JOIN _table2_
ON table1.fieldn = table2.fieldn;

INNER JOIN

The INNER JOIN returns all records (and only the records) from table1 and table2 which have matching values in the specified join fields.

SELECT field1, field 2 … fieldn
FROM table1
INNER JOIN _table2_
ON table1.fieldn = table2.fieldn;

FULL OUTER JOIN

The FULL OUTER JOIN returns all records for both tables with records matched on the join field combined.

SELECT field1, field 2 … fieldn
FROM table1
FULL OUTER JOIN _table2_
ON table1.fieldn = table2.fieldn;

5. Database Object Creation & Modification

CREATE can be used to create new databases, tables, or views. A table is a permanent database object and contains data. A view is virtualized table and its contents are defined by a query, it does not actually store data, but it may bring together data from multiple tables.

CREATE TABLE

To create a new table in the database and define its structure, use the CREATE statement like this:

CREATE tablename (
field1 datatype,
field2 datatype,
_field3 datatype,
…
);

CREATE VIEW

Since a view is defined by a query, to create a new view, the syntax would look like this:

CREATE viewname AS
SELECT field1, field2, … fieldn
FROM tablename
WHERE condition;

SELECT (view

SELECT can be used to retrieve an existing view. It is written the same as when selecting from a table, only selecting from a view, rather than a table.

SELECT field1, field2, … field2
FROM viewname;

DROP (view

If a view is not longer needed, it can be removed by using DROP:

DROP VIEW viewname;

Written by: Josiah Faas
Reviewed by: Matt David

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