To get a data job in 2021, you are going to need to learn SQL. As with any language and especially when you are a beginner, it can be useful to have a list of common SQL commands and operators in one place to refer to whenever you need it — we’d like to be that place for you!
Below is a comprehensive list of SQL commands, organized by the top-level of each (e.g. SELECT TOP is within the SELECT category).
If you’re on a journey to learn SQL and you’ve been frustrated by the lack of structure or the dull curriculum composed of Google searches, then you may like Dataquest’s interactive SQL courses. Whether you’re a beginner trying to get job-ready or a seasoned developer looking to stay sharp, there’s a SQL course for you.
List of SQL Commands
SELECT is probably the most commonly-used SQL statement. You’ll use it pretty much every time you query data with SQL. It allows you to define what data you want your query to return.
For example, in the code below, we’re selecting a column called
name from a table called
SELECT name FROM customers;
SELECT used with an asterisk (*) will return all of the columns in the table we’re querying.
SELECT * FROM customers;
SELECT DISTINCT only returns data that is distinct — in other words, if there are duplicate records, it will return only one copy of each.
The code below would return only rows with a unique
name from the
SELECT DISTINCT name FROM customers;
SELECT INTO copies the specified data from one table into another.
SELECT * INTO customers FROM customers_bakcup;
SELECT TOP only returns the top
x number or percent from a table.
The code below would return the top 50 results from the
SELECT TOP 50 * FROM customers;
The code below would return the top 50 percent of the
SELECT TOP 50 PERCENT * FROM customers;
AS renames a column or table with an alias that we can choose. For example, in the code below, we’re renaming the
name column as
SELECT name AS first_name FROM customers;
FROM specifies the table we’re pulling our data from:
SELECT name FROM customers;
WHERE filters your query to only return results that match a set condition. We can use this together with conditional operators like
SELECT name FROM customers WHERE name = ‘Bob’;
AND combines two or more conditions in a single query. All of the conditions must be met for the result to be returned.
SELECT name FROM customers WHERE name = ‘Bob’ AND age = 55;
OR combines two or more conditions in a single query. Only one of the conditions must be met for a result to be returned.
SELECT name FROM customers WHERE name = ‘Bob’ OR age = 55;
BETWEEN filters your query to return only results that fit a specified range.
SELECT name FROM customers WHERE age BETWEEN 45 AND 55;
LIKE searches for a specified pattern in a column. In the example code below, any row with a name that included the characters Bob would be returned.
SELECT name FROM customers WHERE name LIKE ‘%Bob%’;
Other operators for LIKE:
IN allows us to specify multiple values we want to select for when using the WHERE command.
SELECT name FROM customers WHERE name IN (‘Bob’, ‘Fred’, ‘Harry’);
IS NULL will return only rows with a NULL value.
SELECT name FROM customers WHERE name IS NULL;
IS NOT NULL
IS NOT NULL does the opposite — it will return only rows without a NULL value.
SELECT name FROM customers WHERE name IS NOT NULL;
CREATE can be used to set up a database, table, index or view.
CREATE DATABASE creates a new database, assuming the user running the command has the correct admin rights.
CREATE DATABASE dataquestDB;
CREATE TABLE creates a new table inside a database. The terms int and varchar(255) in this example specify the datatypes of the columns we’re creating.
CREATE TABLE customers ( customer_id int, name varchar(255), age int );
CREATE INDEX generates an index for a table. Indexes are used to retrieve data from a database faster.
CREATE INDEX idx_name ON customers (name);
CREATE VIEW creates a virtual table based on the result set of an SQL statement. A view is like a regular table (and can be queried like one), but it is not saved as a permanent table in the database.
CREATE VIEW [Bob Customers] AS SELECT name, age FROM customers WHERE name = ‘Bob’;
DROP statements can be used to delete entire databases, tables or indexes.
It goes without saying that the DROP command should only be used where absolutely necessary.
DROP DATABASE deletes the entire database including all of its tables, indexes etc as well as all the data within it.
Again, this is a command we want to be very, very careful about using!
DROP DATABASE dataquestDB;
DROP TABLE deletes a table as well as the data within it.
DROP TABLE customers;
DROP INDEX deletes an index within a database.
DROP INDEX idx_name;
The UPDATE statement is used to update data in a table. For example, the code below would update the age of any customer named
Bob in the
customers table to
UPDATE customers SET age = 56 WHERE name = ‘Bob’;
DELETE can remove all rows from a table (using *), or can be used as part of a WHERE clause to delete rows that meet a specific condition.
DELETE FROM customers WHERE name = ‘Bob’;
ALTER TABLE allows you to add or remove columns from a table. In the code snippets below, we’ll add and then remove a column for
surname. The text
varchar(255) specifies the datatype of the column.
ALTER TABLE customers ADD surname varchar(255);
ALTER TABLE customers DROP COLUMN surname;
We hope this is a helpful resource,
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Learn SQL by actually doing it!
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AGGREGATE FUNCTIONS (COUNT/SUM/AVG/MIN/MAX)
An aggregate function performs a calculation on a set of values and returns a single result.
COUNT returns the number of rows that match the specified criteria. In the code below, we’re using
*, so the total row count for
customers would be returned.
SELECT COUNT(*) FROM customers;
SUM returns the total sum of a numeric column.
SELECT SUM(age) FROM customers;
AVG returns the average value of a numeric column.
SELECT AVG(age) FROM customers;
MIN returns the minimum value of a numeric column.
SELECT MIN(age) FROM customers;
MAX returns the maximum value of a numeric column.
SELECT MAX(age) FROM customers;
The GROUP BY statement groups rows with the same values into summary rows. The statement is often used with aggregate functions. For example, the code below will display the average age for each name that appears in our
SELECT name, AVG(age) FROM customers GROUP BY name;
HAVING performs the same action as the WHERE clause. The difference is that HAVING is used for aggregate functions, whereas WHERE doesn’t work with them.
The below example would return the number of rows for each name, but only for names with more than 2 records.
SELECT COUNT(customer_id), name FROM customers GROUP BY name HAVING COUNT(customer_id) > 2;
ORDER BY sets the order of the returned results. The order will be ascending by default.
SELECT name FROM customers ORDER BY age;
DESC will return the results in descending order.
SELECT name FROM customers ORDER BY age DESC;
The OFFSET statement works with ORDER BY and specifies the number of rows to skip before starting to return rows from the query.
SELECT name FROM customers ORDER BY age OFFSET 10 ROWS;
FETCH specifies the number of rows to return after the OFFSET clause has been processed. The OFFSET clause is mandatory, while the FETCH clause is optional.
SELECT name FROM customers ORDER BY age OFFSET 10 ROWS FETCH NEXT 10 ROWS ONLY;
JOINS (INNER, LEFT, RIGHT, FULL)
A JOIN clause is used to combine rows from two or more tables. The four types of JOIN are INNER, LEFT, RIGHT and FULL.
INNER JOIN selects records that have matching values in both tables.
SELECT name FROM customers INNER JOIN orders ON customers.customer_id = orders.customer_id;
LEFT JOIN selects records from the left table that match records in the right table. In the below example the left table is
SELECT name FROM customers LEFT JOIN orders ON customers.customer_id = orders.customer_id;
RIGHT JOIN selects records from the right table that match records in the left table. In the below example the right table is
SELECT name FROM customers RIGHT JOIN orders ON customers.customer_id = orders.customer_id;
FULL JOIN selects records that have a match in the left or right table. Think of it as the “OR” JOIN compared with the “AND” JOIN (INNER JOIN).
SELECT name FROM customers FULL OUTER JOIN orders ON customers.customer_id = orders.customer_id;
EXISTS is used to test for the existence of any record in a subquery.
SELECT name FROM customers WHERE EXISTS (SELECT order FROM ORDERS WHERE customer_id = 1);
GRANT gives a particular user access to database objects such as tables, views or the database itself. The below example would give SELECT and UPDATE access on the customers table to a user named “usr_bob”.
GRANT SELECT, UPDATE ON customers TO usr_bob;
REVOKE removes a user’s permissions for a particular database object.
REVOKE SELECT, UPDATE ON customers FROM usr_bob;
SAVEPOINT allows you to identify a point in a transaction to which you can later roll back. Similar to creating a backup.
COMMIT is for saving every transaction to the database. A COMMIT statement will release any existing savepoints that may be in use and once the statement is issued, you cannot roll back the transaction.
DELETE FROM customers WHERE name = ‘Bob’; COMMIT;
ROLLBACK is used to undo transactions which are not saved to the database. This can only be used to undo transactions since the last COMMIT or ROLLBACK command was issued. You can also rollback to a SAVEPOINT that has been created before.
ROLLBACK TO SAVEPOINT_NAME;
TRUNCATE TABLE removes all data entries from a table in a database, but keeps the table and structure in place. Similar to DELETE.
TRUNCATE TABLE customers;
UNION combines multiple result-sets using two or more SELECT statements and eliminates duplicate rows.
SELECT name FROM customers UNION SELECT name FROM orders;
UNION ALL combines multiple result-sets using two or more SELECT statements and keeps duplicate rows.
SELECT name FROM customers UNION ALL SELECT name FROM orders;
We hope this page serves as a helpful quick-reference guide to SQL commands. But if you really want to learn your SQL skills, copy-apsting code won’t cut it. Check out our interactive SQL courses and start learning by doing!
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