In order to sort by descending order in Spark DataFrame, we can use desc property of the Column class or desc() sql function. In this article, I will explain the sorting dataframe by using these approaches on multiple columns.
1. Using sort() for descending order
First, let’s do the sort.
// Using sort() for descending order
df.sort("department","state")
Now, let’s do the sort using desc property of Column class and In order to get column class we use col() SQL function
import org.apache.spark.sql.functions.col
df.sort(col("department").desc,col("state").desc)
Finally, let’s see how desc() SQL function by importing org.apache.spark.sql.functions.desc
import org.apache.spark.sql.functions.desc
df.sort(desc("department"),desc("state"))
2. Using orderBy() for descending
Alternatively, we can also use orderBy() function of the DataFrame to sort by descending order. All examples explained with sort() also works here.
// Using orderBy() for descending
df.orderBy("department","state")
import org.apache.spark.sql.functions.col
df.orderBy(col("department").desc,col("state").desc)
import org.apache.spark.sql.functions.desc
df.orderBy(desc("department"),desc("state"))
3. Using SQL to sort
And, we can also use SQL expression to sort by descending order.
// Using SQL to sort
df.createOrReplaceTempView("DEPT")
spark.sql(" select employee_name,desc('department'),desc('state'),salary,age,bonus from DEPT")
Happy Learning !!