So what will be the count of rows in that?

To determine the number of rows in a table or result set, you use the COUNT aggregate function. In SQL, you would write: SELECT COUNT(*) FROM table_name; This returns a single integer representing the total rows. If you need to count distinct values, use COUNT(DISTINCT column). In Spark, you can call df.count() on a DataFrame, which triggers an action that returns the row count. Both approaches are straightforward and are often used in exploratory data analysis or as a sanity check after a transformation.