use the agg method to check if the count of rows where columnName contains 0, is equal to the total number of rows in the dataframe, using the following code: df.agg(count("*").alias("total_count"),count(when(col("columnName")===0,1)).alias("zero_count")).filter("total_count == zero_count").count()

This will return 1 if all the rows contain 0 in the columnName and 0 otherwise

no it doesn't worked, actually what i want is have one column in spark dataframe as count, for that particular column value is greater than 0 means, it needs to exit.

but the above answer is totally different​