I need to extract rows from a database table where the pair of values in two columns of one row exactly match the pair in another row. For example, consider a table with separate columns for longitude and latitude. I want to determine if any two rows share identical GPS coordinates. How would you construct a SQL query that identifies such matching rows without relying on the DISTINCT keyword?
One approach to comparing rows without using DISTINCT is to leverage GROUP BY alongside an aggregate function. For example, by grouping on the longitude and latitude columns and filtering groups with more than one entry through a HAVING clause, you can identify rows with matching GPS coordinates. In my experience, this method is efficient and clear, and it scales well as the dataset grows. It also avoids potential performance issues that can arise when using self joins, especially on large tables.
hey try a self join approach. join table to itself on the gps cols and filter on different ids so it excludes self. works well in my work and its easy to read, though u gotta check it on huge datasets. hope that helps.
An alternative approach, which I have found quite effective, involves using window functions. By applying a COUNT aggregate as a window function, partitioning by the two columns of interest, it is possible to compute a count for every row that indicates the frequency of the coordinate pair. This method avoids the need for DISTINCT while also bypassing the complexity of self-joins. The resulting query is straightforward, maintains clarity, and performs reliably even as the dataset grows in size.
hey im also tinkering with subqueries that group gps values then match them back to original rows. did u notice any difference in speed or clarity using that vs self joins? would love to hear more thoughts on that method.