SparkStearming实战：集成Spark SQL，使用SQL语句进行WordCount

1.需求：
集成Spark SQL，使用SQL语句进行WordCount
2.代码：
(1)pom.xml

<dependencies>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-core -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.11</artifactId>
            <version>2.1.0</version>
        </dependency>

        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.11</artifactId>
            <version>2.1.0</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.11</artifactId>
            <version>2.1.0</version>
        </dependency>
    </dependencies>

(2)MyNetwordWordCountWithSQL.scala

package day1211
import org.apache.log4j.Logger
import org.apache.log4j.Level
import org.apache.spark.SparkConf
import org.apache.spark.streaming.StreamingContext
import org.apache.spark.streaming.Seconds
import org.apache.spark.storage.StorageLevel
import org.apache.spark.sql.SparkSession

object MyNetwordWordCountWithSQL {

  def main(args: Array[String]): Unit = {
    System.setProperty("hadoop.home.dir", "/Users/macbook/Documents/hadoop/hadoop-2.8.4")
    Logger.getLogger("org.apache.spark").setLevel(Level.ERROR)
    Logger.getLogger("org.eclipse.jetty.server").setLevel(Level.OFF)

    val conf = new SparkConf().setMaster("local[2]").setAppName("MyNetwordWordCountWithSQL")

    val ssc = new StreamingContext(conf,Seconds(5))

    val lines = ssc.socketTextStream("192.168.1.121",1235,StorageLevel.MEMORY_ONLY)

    val words = lines.flatMap(_.split(" "))

    //集成Spark SQL 使用SQL语句进行WordCount
    words.foreachRDD( rdd => {

      val spark = SparkSession.builder().config(rdd.sparkContext.getConf).getOrCreate()

      import spark.implicits._
      val df1 = rdd.toDF("word")

      df1.createOrReplaceTempView("words")

      spark.sql("select word , count(1) from words group by word").show()
    })

    ssc.start()
    ssc.awaitTermination()
  }

}

3.运行：

4.结果：