Scenario: we have a massive sales table and a smaller product table. The join is taking too long. What would you do?

When a join between a very large sales table and a smaller product table is slow, the first step is to examine the execution plan to see which join algorithm is used. If the product table is small, a hash join or a merge join may be appropriate, but you must ensure that the join key is indexed on the sales table. Create a composite index on the sales table’s foreign key to the product table and any other columns used in the WHERE clause. Consider partitioning the sales table by date or region to reduce the amount of data scanned. If the product table is read frequently, materialize a denormalized view that contains the most frequently used product attributes. Use query hints or rewrite the query to filter the sales table before the join (e.g., add a date range). Finally, test the query with and without the index and measure the impact. The goal is to reduce the number of rows processed and to use efficient join algorithms, which typically brings the cost from O(n*m) down to O(n log n) or O(n).