SparkSQL之UDF使用

package cn.piesat.test

import org.apache.spark.sql.SparkSession

import scala.collection.mutable.ArrayBuffer


object SparkSQLTest {

  def main(args: Array[String]): Unit = {
    val spark=SparkSession.builder().appName("sparkSql").master("local[4]")
      .config("spark.serializer","org.apache.spark.serializer.KryoSerializer").getOrCreate()
    val sc=spark.sparkContext
    val sqlContext=spark.sqlContext
    val workerRDD=sc.textFile("F://Workers.txt").mapPartitions(itor=>{
      val array=new ArrayBuffer[Worker]()
      while(itor.hasNext){
        val splited=itor.next().split(",")
        array.append(new Worker(splited(0),splited(2).toInt,splited(2)))
      }
      array.toIterator
    })
    import spark.implicits._
    //注册UDF
    spark.udf.register("strLen",(str:String,addr:String)=>str.length+addr.length)
    val workDS=workerRDD.toDS()
    workDS.createOrReplaceTempView("worker")
    val resultDF=spark.sql("select strLen(name,addr) from worker")
    val resultDS=resultDF.as("WO")
    resultDS.show()

    spark.stop()

  }

}

SparkSQL之UDF使用

标签：partition   pen   .text   tor   conf   buffer   udf   worker   textfile