使用Spark RDD找出所有只打1分以下，且评论次数大于5次的用户，用scala编程语言

好的，以下是使用Spark RDD找出所有只打1分以下，且评论次数大于5次的用户的Scala代码：

import org.apache.spark.{SparkConf, SparkContext}

val conf = new SparkConf().setAppName("user analysis")
val sc = new SparkContext(conf)

val data = sc.textFile("ratings.csv")
val header = data.first()
val ratings = data.filter(line => line != header)
                  .map(line => line.split(","))
                  .map(fields => (fields(0), (fields(2).toFloat, 1)))
                  .reduceByKey((x, y) => (x._1 + y._1, x._2 + y._2))
                  .filter(x => x._2._1 / x._2._2 <= 1.0 && x._2._2 > 5)
                  .collect()

println("Users who rated only 1 star and have reviewed more than 5 times:")
for (user <- ratings) {
  println(s"User ${user._1} - Average rating: ${user._2._1 / user._2._2}, Review count: ${user._2._2}")
}

这段代码与Python代码的思路相同，只是使用了Scala语言的语法。