SparkStreaming使用SQL

直接上代码，例子来源于官网的wordcount例子

package Sparkstreaming

import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.SparkSession
import org.apache.spark.storage.StorageLevel
import org.apache.spark.streaming.{Seconds, StreamingContext, Time}

  SQLtest {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setAppName(\"SQLtest\").setMaster(\"local[2]\")
    val ssc = new StreamingContext(conf, Seconds(5))
    val lines = ssc.socketTextStream(\"192.168.116.10\", 9999)
    val words = lines.flatMap(_.split(\" \"))
    words.foreachRDD { (rdd: RDD[String], time: Time) =>
      // Get the singleton instance of SparkSession
      val spark = SparkSessionSingleton.getInstance(rdd.sparkContext.getConf)
      import spark.implicits._

      // Convert RDD[String] to RDD[case class] to Data 
      val wordsData  = rdd.map(w => Record(w)).toDF()

      // Creates a temporary view using the Data 
      wordsData .createOrReplaceTempView(\"words\")

      // Do word count on table using SQL and print it
      val wordCountsData  =
        spark.sql(\"select word, count(*) as total from words group by word\")
      println(s\"========= $time =========\")
      wordCountsData .show()
    }
    ssc.start()
    ssc.awaitTermination()

  }

  case class Record(word: String)


  /** Lazily instantiated singleton instance of SparkSession */
    SparkSessionSingleton {

    @transient private var instance: SparkSession = _

    def getInstance(sparkConf: SparkConf): SparkSession = {
      if (instance == null) {
        instance = SparkSession
          .builder
          .config(sparkConf)
          .getOrCreate()
      }
      instance
    }
  }

}

测试

在Linux新建一个窗口，输入

可以发现IDEA控制台已经输出结果了