Getting the Minimum Date Across All Records and Sum for Each Type

Introduction

In this article, we’ll explore how to achieve two common data analysis tasks in MySQL: getting the minimum date across all records and summing values for each type. We’ll examine both traditional sub-query methods and newer window functions.

The Data

Our starting point is a simple table with four columns:

• balance_date: Date of balance update
• name: Account holder’s name
• wallet_type: Type of wallet (debit, credit, or crypto)
• available_balance: Current available balance

The data is provided as follows:

Traditional Sub-Queries

One way to solve this task is by using sub-queries. The following query gets the minimum date for each name and sums up available_balance but doesn’t filter the minimum date for each type.

SELECT 
  (SELECT MIN(balance_date) 
   FROM mytable d1 WHERE d1.name = d.name) AS min_date, 
  name,
  wallet_type,
  SUM(available_balance) AS available_balance
FROM mytable d
GROUP BY name, wallet_type

Limitations of Traditional Sub-Queries

This method has several limitations:

• It returns the sum for each name and wallet_type, which is not what we want. We need to only consider each type individually.
• The sub-query itself can become inefficient if you have large datasets, since it must be executed for each row in your table.

Using MySQL Window Functions (MySQL 8.0+)

The newer window functions offer a much more elegant solution for this problem. Introduced in MySQL 8.0, these allow us to perform complex calculations directly within the query without having to rely on sub-queries or joins.

Partitioning by Name and Type

SELECT 
  MIN(balance_date) OVER(PARTITION BY name) AS min_date, 
  name,
  wallet_type,
  SUM(available_balance) OVER(PARTITION BY name, wallet_type) AS available_balance 
FROM mytable

This query will return the minimum date for each name but not necessarily across all records. To include all records, we’ll need to add a condition.

Getting Minimum Date Across All Records

To get the minimum date that applies to all records (not just per type or name), you would use the following:

SELECT 
  MIN(CASE WHEN RANK() OVER(ORDER BY balance_date) = 1 THEN balance_date END) AS min_date, 
  name,
  wallet_type,
  SUM(available_balance) AS available_balance 
FROM mytable d
GROUP BY name, wallet_type

This query calculates the minimum date that appears first in the sorted list of all dates.

Rank Function for Earliest Date

The RANK() function is used to rank records based on a value (in this case, balance_date). It assigns ranks starting from 1, and since we want the earliest date, we only consider those with rank 1.

However, using a sub-query or another query method might be slightly simpler for achieving the goal of getting an aggregate sum while considering each type individually.

Conclusion

• Traditional sub-queries can become inefficient for large datasets.
• MySQL window functions are more efficient and allow for complex calculations directly within the query.
• These functions make it straightforward to perform tasks like aggregating values, getting minimum or maximum dates across all records, and ranking data.

Whether you’re working with a simple dataset or a massive one, understanding how to use MySQL’s advanced features can significantly improve your productivity and ability to solve complex problems.

Last modified on 2025-04-08