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  • 性能:Output层面

    将数据保存到MySQL中
    import java.sql.DriverManager
    
    import org.apache.spark.storage.StorageLevel
    import org.apache.spark.streaming.{Seconds, StreamingContext}
    import org.apache.spark.{SparkConf, SparkContext}
    
    /**
      * WordCount程序,Spark Streaming消费TCP Server发过来的实时数据的例子:
      *
      * 1、在master服务器上启动一个Netcat server
      * `$ nc -lk 9998` (如果nc命令无效的话,我们可以用yum install -y nc来安装nc)
      *
      *
      * create table wordcount(ts bigint, word varchar(50), count int);
      *
      * spark-shell --total-executor-cores 4 --executor-cores 2 --master spark://master:7077 --jars mysql-connector-java-5.1.44-bin.jar,
      * c3p0-0.9.1.2.jar,spark-streaming-basic-1.0-SNAPSHOT.jar
      *
      *
      */
    object NetworkWordCountForeachRDD {
      def main(args: Array[String]) {
        val sparkConf = new SparkConf().setAppName("NetworkWordCountForeachRDD")
        val sc = new SparkContext(sparkConf)
    
        // Create the context with a 1 second batch size
        val ssc = new StreamingContext(sc, Seconds(5))
    
        //创建一个接收器(ReceiverInputDStream),这个接收器接收一台机器上的某个端口通过socket发送过来的数据并处理
        val lines = ssc.socketTextStream("master", 9998, StorageLevel.MEMORY_AND_DISK_SER)
    
        //处理的逻辑,就是简单的进行word count
        val words = lines.flatMap(_.split(" "))
        val wordCounts = words.map(x => (x, 1)).reduceByKey(_ + _)
    
        //将结果保存到Mysql(错误代码:Connection不能序列化  Driver端执行的代码不能在execute上 )
        wordCounts.foreachRDD { (rdd, time) =>
          Class.forName("com.mysql.jdbc.Driver")
          val conn = DriverManager.getConnection("jdbc:mysql://master:3306/test", "root", "root")
          val statement = conn.prepareStatement(s"insert into wordcount(ts, word, count) values (?, ?, ?)")
          rdd.foreach { record =>
            statement.setLong(1, time.milliseconds)
            statement.setString(2, record._1)
            statement.setInt(3, record._2)
            statement.execute()
          }
          statement.close()
          conn.close()
        }
        //启动Streaming处理流
        ssc.start()
    
        ssc.stop(false)
    
    
    
        //将结果保存到Mysql(优化代码)
        wordCounts.foreachRDD { (rdd, time) =>
          rdd.foreachPartition { partitionRecords =>
            val conn = ConnectionPool.getConnection
            conn.setAutoCommit(false)
            val statement = conn.prepareStatement(s"insert into wordcount(ts, word, count) values (?, ?, ?)")
            partitionRecords.zipWithIndex.foreach { case ((word, count), index) =>
              statement.setLong(1, time.milliseconds)
              statement.setString(2, word)
              statement.setInt(3, count)
              statement.addBatch()
              if (index != 0 && index % 500 == 0) {
                statement.executeBatch()
                conn.commit()
              }
            }
            statement.executeBatch()
            statement.close()
            conn.commit()
            conn.setAutoCommit(true)
            ConnectionPool.returnConnection(conn)
          }
        }
    
        //等待Streaming程序终止
        ssc.awaitTermination()
      }
    }
    

      

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  • 原文地址:https://www.cnblogs.com/tesla-turing/p/11488365.html
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