Selecting Distinct Values with Corresponding Columns in MySQL

1. Using GROUP BY with an aggregate function:

This approach groups rows based on the distinct column and then uses an aggregate function (like MIN, MAX, or ANY_VALUE) to pick a value from another column for each group.

Here's an example:

SELECT distinct_column, MIN(other_column) AS min_other_value
FROM your_table
GROUP BY distinct_column;

This query will select distinct values from distinct_column and for each distinct value, it will pick the minimum value from other_column and alias it as min_other_value.

1. Using a subquery:

This approach involves a subquery that retrieves the distinct values for the desired column. Then, you join this subquery with the original table to get the corresponding values from other columns.

SELECT t1.distinct_column, t2.other_column
FROM your_table t1
INNER JOIN (
  SELECT DISTINCT distinct_column
  FROM your_table
) AS t2
ON t1.distinct_column = t2.distinct_column;

This query first gets the distinct values from distinct_column in a subquery and stores them in a temporary table named t2. Then, it joins the original table t1 with t2 on the distinct_column to retrieve the corresponding values from other_column.

Choosing the right approach:

• Use GROUP BY with an aggregate function if you're interested in a specific value (like minimum or maximum) from another column for each distinct value.
• Use a subquery if you need all the corresponding values from other columns for each distinct value.

SELECT product_category, MIN(price) AS min_price
FROM products
GROUP BY product_category;

This query assumes a table named products with columns product_category and price. It will:

• Select distinct values from product_category.
• For each distinct category, it will find the minimum value from the price column and alias it as min_price.

This is useful if you want to know the minimum price for each product category.

SELECT o.order_id, p.product_name
FROM orders o
INNER JOIN (
  SELECT DISTINCT customer_id
  FROM orders
) AS unique_customers
ON o.customer_id = unique_customers.customer_id;

This query assumes a table named orders with columns order_id, customer_id, and a table named products with a column product_name. It will:

• Create a subquery that selects distinct values from the customer_id column in the orders table and stores them in a temporary table named unique_customers.
• Join the original orders table (aliased as o) with the unique_customers table on the customer_id column.
• Select order_id from the orders table and product_name (assuming a relationship between orders and products tables) for each distinct customer.

This method works well if the distinct column, along with potentially another column, uniquely identifies a row (unambiguous entity). It uses a LEFT JOIN and filtering to remove duplicates.

Here's the approach:

SELECT distinct_column, other_column
FROM your_table AS main
LEFT JOIN your_table AS dups ON main.distinct_column = dups.distinct_column
  AND (main.other_column < dups.other_column OR main.id < dups.id)  -- Assuming id is unique
WHERE dups.other_column IS NULL;

Explanation:

• We do a LEFT JOIN on the table itself, aliasing the main table as main and the duplicate table as dups.
• We join on the distinct_column, ensuring both tables match.
• The additional condition in the ON clause uses another column (other_column here) or a unique identifier (id in this example) to differentiate rows. It keeps the row with the "smallest" value in the chosen column (you can adjust the comparison for your needs).
• Finally, the WHERE clause filters out rows from the dups table, keeping only the first occurrence of each distinct value in main.

Note: This method can be slow for large datasets and requires the distinct column along with another column to uniquely identify rows.

Composite IN() Subquery (for unambiguous entities):

This method is suitable for situations where the distinct column combined with another column uniquely identifies a row. It uses a subquery with MIN or MAX to get a representative value from another column.

SELECT your_table.*
FROM your_table
WHERE distinct_column IN (
  SELECT DISTINCT distinct_column, MIN(other_column) AS min_other_value
  FROM your_table
  GROUP BY distinct_column
);

• The subquery retrieves distinct values from distinct_column and uses MIN (or MAX) on other_column to pick a representative value for each group (assuming order doesn't matter). It aliases the minimum value as min_other_value.
• The main query then selects all columns from the your_table where the distinct_column is present in the list of distinct values retrieved by the subquery.

Note: This method also assumes a unique combination of distinct_column and another column. It's generally faster than the exclusion join but might not be suitable for all scenarios.

• Use the exclusion join if the distinct column with another column uniquely identifies a row and performance is less of a concern.
• Use the composite IN() subquery if you need all the corresponding values from other columns and the distinct column with another column uniquely identifies a row.