How to Get First Row Per Group in Redshift

When working with large datasets in Amazon Redshift, it's common to need to retrieve the first row of each group based on some criteria, such as the earliest or latest timestamp. This article covers several methods to achieve this, including using window functions and subqueries.

Method 1: Using Window Functions

Redshift supports window functions, which allow you to perform calculations across a set of table rows related to the current row. To retrieve the first row per group, we can use the ROW_NUMBER() function in combination with the PARTITION BY clause.

SELECT *
FROM (
    SELECT *,
           ROW_NUMBER() OVER (PARTITION BY group_column ORDER BY date_column) AS row_num
    FROM your_table
) AS subquery
WHERE row_num = 1;
                                

In the example above:

• PARTITION BY group_column: Divides the data into groups based on the group_column.
• ORDER BY date_column: Orders the rows within each group by the date_column.
• ROW_NUMBER(): Assigns a unique number to each row within its group, starting at 1 for the first row.

This query returns the first row for each group based on the earliest date_column.

Method 2: Using a Subquery

If you prefer a simpler approach or need to use Redshift versions that do not support window functions, a subquery can also be used to retrieve the first row per group.

SELECT t1.*
FROM your_table t1
JOIN (
    SELECT group_column, MIN(date_column) AS min_date
    FROM your_table
    GROUP BY group_column
) t2 ON t1.group_column = t2.group_column AND t1.date_column = t2.min_date;
                                

This query works by first finding the minimum date_column for each group using a subquery. Then, it joins the result with the main table to retrieve the entire row corresponding to the minimum date for each group.

Choosing the Right Method

Both methods are valid, but the choice between them depends on the specific requirements and Redshift version you are working with. Window functions provide a more efficient and flexible solution, especially for complex queries. Subqueries may be preferable in simpler cases or when dealing with older versions of Redshift.

Conclusion

Getting the first row per group in Redshift is a common requirement, and both window functions and subqueries offer efficient ways to achieve this. Window functions are more powerful and flexible, but subqueries may be useful in certain situations. Choose the method that best fits your needs.