Spark分组排序TopN

数据源

# f://data.txt
# className, studentName, score
c1	a	85
c2	b	77
c3	c	88
c1	d	22
c1	e	66
c3	f	95
c3	g	54
c2	h	91
c2	i	66
c1	j	54
c1	k	65
c2	l	41
c4	m	65

目标

对班级进行分组，对成绩求topN

解决方法

spark core

val classStudentScore = spark.sparkContext.textFile("f://data.txt")
      .map(x=>{
        val splits = x.split("\t")
        (splits(0), (splits(1), splits(2).toInt))
      })
      .groupByKey()
      .map(x=>{
        val className = x._1
        val nameScores = x._2.toArray.sortBy(_._2).reverse.take(3)
        (className, nameScores)
      })
      .foreach(x=>{
        println(x._1)
        x._2.foreach(println)
      })

spark core

    val classStudentScoreRDD = spark.read.text("f://data.txt").rdd
      .map(x => {
        val splits = x.getString(0).split("\t")
        Row(splits(0), splits(1), splits(2).toInt)
      })

    val classStudentScoreDF = spark.createDataFrame(classStudentScoreRDD, new StructType(
      Array(
        StructField("className", StringType, true),
        StructField("studentName", StringType, true),
        StructField("score", IntegerType, true)
      )
    ))

    classStudentScoreDF
      .withColumn("rank",
        row_number()
          over
          partitionBy(col("className"))
            .orderBy(col("score").desc))
      .filter(col("rank").<=(3))
      .show()