Selecting Distinct Rows with All Columns in SQL

In SQL, you often need to retrieve unique rows from a table based on one or more columns. While the DISTINCT keyword is useful for this purpose, it typically only returns the specified columns, discarding the rest. This tutorial will explain how to achieve the desired result: retrieving all columns for each distinct combination of values in a specified field (or fields).

The Problem

Imagine you have a table containing information about products, including product_id, name, and price. You want to retrieve a list of unique product names, but you also need the associated product_id and price for each unique name. Simply using SELECT DISTINCT name won’t give you the other columns.

Using `GROUP BY`

The most common and often most efficient approach to solve this problem is to use the GROUP BY clause. GROUP BY groups rows that have the same values in one or more columns. When combined with aggregate functions (like MAX, MIN, AVG, SUM, COUNT), it allows you to select additional columns alongside the grouping criteria. However, when you only need one row per group, and you don’t need aggregation, GROUP BY effectively acts like DISTINCT but allows all columns to be retrieved.

Here’s how to apply it:

SELECT *
FROM your_table_name
GROUP BY field1;

Replace your_table_name with the actual name of your table and field1 with the column you want to use to determine distinct rows. This query will return all columns from the table, but only one row for each unique value in field1.

Important Considerations with GROUP BY:

Ambiguous Columns: If you include columns in the SELECT statement that are not part of the GROUP BY clause and you do not use aggregate functions on those columns, the database system might return unpredictable results or throw an error. This is because it’s unclear which value to pick for those non-grouped columns when multiple rows contribute to the same group. Most database systems (like PostgreSQL, SQL Server) require you to either include those columns in the GROUP BY clause or apply an aggregate function to them. MySQL is more lenient but might return an arbitrary value for the non-grouped columns.
Performance: While GROUP BY is a standard approach, its performance can degrade with large tables. Consider adding appropriate indexes on the grouping columns to improve performance.

Using Window Functions (For More Control)

For more complex scenarios, particularly in database systems that support window functions (like PostgreSQL, SQL Server, Oracle), you can use ROW_NUMBER() to select one row per group.

Here’s how:

SELECT *
FROM (
    SELECT 
        *,
        ROW_NUMBER() OVER (PARTITION BY field1 ORDER BY some_other_column) AS row_num
    FROM your_table_name
) AS subquery
WHERE row_num = 1;

This query works as follows:

Inner Query: The inner query calculates a row number (row_num) for each row within each group defined by field1. The ORDER BY some_other_column clause determines the order in which rows are assigned row numbers within each group. You can choose any column to define the ordering.
Outer Query: The outer query filters the results to include only the rows where row_num is 1. This effectively selects one row per group, as defined by field1.

Window functions offer more flexibility in controlling which row is selected within each group.

Alternative Approach: Subqueries and Joins

Another method, although potentially less efficient, involves using a subquery to select the distinct values and then joining it back to the original table:

SELECT c2.*
FROM (SELECT DISTINCT field1 FROM your_table_name AS c) AS c1
JOIN your_table_name AS c2 ON c1.field1 = c2.field1;

This query works by first selecting the distinct values of field1 in the subquery. Then, it joins the subquery result back to the original table on field1, retrieving all columns for each distinct value.

Choosing the Right Method

For simple cases and most database systems, GROUP BY is the preferred and most efficient approach.
If you need more control over which row is selected within each group, or if you are working with a database system that supports window functions, ROW_NUMBER() provides more flexibility.
The subquery and join approach is generally less efficient and should be avoided unless there are specific reasons to use it.