Dataframe: how to groupBy/count then order by count in Scala

Question

I have a dataframe that contains a thousands of rows, what I'm looking for is to group by and count a column and then order by the out put: what I did is somthing looks like :

import org.apache.spark.sql.hive.HiveContext
import sqlContext.implicits._


val objHive = new HiveContext(sc)
val df = objHive.sql("select * from db.tb")
val df_count=df.groupBy("id").count().collect()
df_count.sort($"count".asc).show()

Answer 1

You can use sort or orderBy as below

val df_count = df.groupBy("id").count()

df_count.sort(desc("count")).show(false)

df_count.orderBy($"count".desc).show(false)

Don't use collect() since it brings the data to the driver as an Array.

Hope this helps!

Answer 2

//import the SparkSession which is the entry point for spark underlying API to access
 import org.apache.spark.sql.SparkSession
 import org.apache.spark.sql.functions._

 val pathOfFile="f:/alarms_files/"
//create session and hold it in spark variable
val spark=SparkSession.builder().appName("myApp").getOrCreate()
//read the file below API will return DataFrame of Row
var df=spark.read.format("csv").option("header","true").option("delimiter", "\t").load("file://"+pathOfFile+"db.tab")
//groupBY id column and take count of the column and order it by count of the column
    df=df.groupBy(df("id")).agg(count("*").as("columnCount")).orderBy("columnCount")
//for projecting the dataFrame it will show only top 20 records
    df.show
//for projecting more than 20 records  eg:
    df.show(50)