show you how to use the MySQL interval for date and time arithmetic with many practical examples.
Understanding MySQL Interval Values
MySQL interval values are special expressions you use to perform date and time arithmetic. They allow you to add or subtract a specific amount of time (like days, months, or minutes) to a date or timestamp.
Basic Syntax
The general format is:
INTERVAL expr unit
expr
:
A number that represents the time value (for example, 1, 30, etc.).unit
: The time measurement (such as DAY, MONTH, MINUTE). This part isn’t case-sensitive, soDAY
is the same asday
.
For example, to create a time period of one day, you write:
INTERVAL 1 DAY
Using Intervals with Dates
You can use these interval values directly in arithmetic operations with dates:
- Adding Time:
- Subtracting Time:
date + INTERVAL expr unit
date - INTERVAL expr unit
Examples
- Adding One Day:
- Subtracting One Day:
This query adds one day to January 1, 2020.
SELECT '2020-01-01' + INTERVAL 1 DAY;
Result: 2020-01-02
You can also subtract time by using a negative value:
SELECT '2020-01-01' + INTERVAL -1 DAY;
Result: 2019-12-31
Using MySQL Date and Time Functions with Intervals
MySQL provides several functions that work with interval values to manipulate dates and times:
- DATE_ADD(): Adds an interval to a given date.
- DATE_SUB(): Subtracts an interval from a given date.
- TIMESTAMPADD(): Adds an interval to a timestamp value.
- TIMESTAMPDIFF(): Computes the difference between two dates in the specified unit.
DATE_ADD(date, INTERVAL expr unit)
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DATE_SUB(date, INTERVAL expr unit)
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TIMESTAMPADD(unit, expr, date)
Examples
- Adding/Subtracting a Month:
- 1_MONTH_LATER: 2020-02-01
- 1_MONTH_BEFORE: 2019-12-01
- Adding 30 Minutes to a Timestamp:
This query shows how to add and subtract one month from January 1, 2020.
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SELECT
DATE_ADD('2020-01-01', INTERVAL 1 MONTH) AS 1_MONTH_LATER,
DATE_SUB('2020-01-01', INTERVAL 1 MONTH) AS 1_MONTH_BEFORE;
Result:
Here, the TIMESTAMPADD()
function adds 30 minutes.
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SELECT TIMESTAMPADD(MINUTE, 30, '2020-01-01') AS 30_MINUTES_LATER;
Result: 2020-01-01 00:30:00
Practical Example: Memberships and Expiration Dates
Imagine you have a table called memberships
to track user memberships. The table includes:
- id: A unique identifier for each member.
- email: The member’s email address.
- plan: The type of membership plan.
- expired_date: The date when the membership expires.
Creating the Table
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CREATE TABLE memberships (
id INT AUTO_INCREMENT PRIMARY KEY,
email VARCHAR(355) NOT NULL,
plan VARCHAR(255) NOT NULL,
expired_date DATE NOT NULL
);
Inserting Sample Data
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INSERT INTO memberships(email, plan, expired_date)
VALUES ('john.doe@example.com', 'Gold', '2017-07-13'),
('jane.smith@example.com', 'Platinum', '2017-07-10'),
('david.corp@example.com', 'Silver', '2017-07-15'),
('julia.william@example.com', 'Gold', '2017-07-20'),
('peter.drucker@example.com', 'Silver', '2017-07-08');
Query: Finding Memberships Expiring Soon
Suppose today is July 6, 2017. To find all members whose memberships expire within the next 7 days, you can use:
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SELECT
email,
plan,
expired_date,
DATEDIFF(expired_date, '2017-07-06') AS remaining_days
FROM memberships
WHERE '2017-07-06' BETWEEN DATE_SUB(expired_date, INTERVAL 7 DAY) AND expired_date;
Explanation:
- DATEDIFF(expired_date, '2017-07-06'): Calculates the number of days between today and the expiration date.
- WHERE clause:
DATE_SUB(expired_date, INTERVAL 7 DAY)
computes a date that is 7 days before the expiration date.- The condition checks if today's date falls between that computed date and the actual expiration date.This means it finds memberships that are going to expire within the next 7 days.
Conclusion
For a data scientist, mastering MySQL interval values is crucial for efficiently managing and analyzing time-based data. Whether you are calculating the difference between dates, scheduling events, or adjusting dates in your datasets, these interval expressions and functions (like DATE_ADD
, DATE_SUB
, and TIMESTAMPADD
) provide powerful tools for manipulating date and time values.
By understanding and using these interval operations, you can enhance your SQL queries to better handle time series data, expiration tracking, and various other time-sensitive tasks.
This explanation and the examples should give you a solid foundation for applying MySQL interval values in your data analysis workflows.