Convert scala map to dataframe - scala

Question

I am trying to stream twitter data using Apache Spark and I want to save it as csv file into HDFS. I understand that I have to convert it to a dataframe but I am not able to do so.
Here is my full code:
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.streaming.twitter.TwitterUtils
//import com.google.gson.Gson
import org.apache.log4j.{Level, Logger}
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.sql.{DataFrame, Row, SparkSession}
//import org.apache.spark.sql.types.{IntegerType, StringType, StructField, StructType}
//import org.apache.spark.sql.functions._
import sentimentAnalysis.sentimentScore
case class twitterCaseClass (userID: String = "", user: String = "", createdAt: String = "", text: String = "", sentimentType: String = "")
object twitterStream {
//private val gson = new Gson()
def main(args: Array[String]) {
//Twitter API
Logger.getLogger("org").setLevel(Level.ERROR)
System.setProperty("twitter4j.oauth.consumerKey", "#######")
System.setProperty("twitter4j.oauth.consumerSecret", "#######")
System.setProperty("twitter4j.oauth.accessToken", "#######")
System.setProperty("twitter4j.oauth.accessTokenSecret", "#######")
val spark = SparkSession.builder().appName("twitterStream").master("local[*]").getOrCreate()
val sc: SparkContext = spark.sparkContext
val streamContext = new StreamingContext(sc, Seconds(5))
import spark.implicits._
val filters = Array("Singapore")
val filtered = TwitterUtils.createStream(streamContext, None, filters)
val englishTweets = filtered.filter(_.getLang() == "en")
englishTweets.print()
val tweets = englishTweets.map{ col => {
(
"userID" -> col.getId,
"user" -> col.getUser.getScreenName,
"createdAt" -> col.getCreatedAt.toInstant.toString,
"text" -> col.getText.toLowerCase.split(" ").filter(_.matches("^[a-zA-Z0-9 ]+$")).fold("")((a, b) => a + " " + b).trim,
"sentimentType" -> sentimentScore(col.getText).toString
)
}
}
//val tweets = englishTweets.map(gson.toJson(_))
//tweets.saveAsTextFiles("hdfs://localhost:9000/usr/sparkApp/test/")
streamContext.start()
streamContext.awaitTermination()
}
}
I am not sure where did I possibly went wrong. There is another way to go about which is using case class. Is there a good example I can follow?
Update
The result of the Map function which is save into HDFS is like this:
((userID,1345940003533312000),(user,rei_yang),(createdAt,2021-01-04T03:47:57Z),(text,just posted a photo singapore),(sentimentType,NEUTRAL))
Is there a way to code it to a dataframe?