WordCount program using Spark DataFrame

I wanted to figure out how to write Word Count Program using Spark DataFrame API, so i followed these steps. Import org.apache.spark.sql.functions._, it includes UDF's that i need to use import org.apache.spark.sql.functions._ Create a data frame by reading README.md. When you read the file, spark will create a data frame with single column value, the content of the value column would be the line in the file

val df = sqlContext.read.text("README.md")
Next split each of the line into words using split function. This will create a new DataFrame with words column, each words column would have array of words for that line

val wordsDF = df.select(split(df("value")," ").alias("words"))
Next use explode transformation to convert the words array into a dataframe with word column. This is equivalent of using flatMap() method on RDD

val wordDF = wordsDF.select(explode(wordsDF("words")).alias("word"))
Now you have data frame with each line containing single word in the file. So group the data frame based on word and count the occurrence of each word

val wordCountDF = wordDF.groupBy("word").count
This is the code you need if you want to figure out 20 top most words in the file



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Amit Shrivastava said...

Let's say after explode

you had data like

word - Count
Module, 1
Module 2
Module- 1

So though word here is only module, you are counting without stripping special characters. In this case this solution doesn't seems complete no?