package SparkDemo

import java.sql.{Connection, DriverManager, PreparedStatement}

import org.apache.spark.SparkConf

import org.apache.spark.streaming.{Seconds, StreamingContext}

object DStreamToMySQL {

//定义更新函数

def updateFunc(newValues : Seq[Int],state :Option[Int]):Option[Int] = {

val currentCount = newValues.foldLeft(0)(_+_)

val previousCount = state.getOrElse(0)

Some(currentCount+previousCount)

}

def main(args : Array[String]): Unit ={

//建立SparkStream

val conf = new SparkConf().setAppName("DStreamToMySQL")

val ssc = new StreamingContext(conf,Seconds(1))

//设置日志等级

StreamingLoggingExample.setStreamingLogLevels()

val lines = ssc.textFileStream("/tmp/yuhang.zhang/data")

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

val pairWord = words.map((_,1))

//累计更新

val stateWordCount = pairWord.updateStateByKey[Int](updateFunc)

//将stateWordCount存入数据库

//stateWordCount中包含一堆的Rdd

//我们需要对每个Rdd中的每条数据进行处理储存

stateWordCount.foreachRDD(rdd => {

//每个rdd中包含的数据类型为(String,Int)

//我们把所有数据records定义为Iterator类型，方便我们遍历

def func(records:Iterator[(String,Int)]): Unit ={

//注意，conn和stmt定义为var不能是val

var conn: Connection = null

var stmt : PreparedStatement = null

try{

//连接数据库

val url = "jdbc:mysql://localhost:3306/spark" //地址+数据库

val user = "root"

val password = ""

conn = DriverManager.getConnection(url,user,password)

//

records.foreach(p =>{

//wordcount为表名，word和count为要插入数据的属性

//插入数据

val sql = "insert into wordcount(word,count) values(?,?)"

stmt = conn.prepareStatement(sql)

stmt.setString(1,p._1.trim)

stmt.setInt(2,p._2.toInt)

stmt.executeUpdate()

})

}catch {

case e : Exception => e.printStackTrace()

}finally {

if(stmt != null)

stmt.close()

if(conn != null)

conn.close()

}

}

val repairtitionedRDD = rdd.repartition(3)//将每个rdd重新分区

repairtitionedRDD.foreachPartition(func)//对重新分区后的rdd执行func函数

})

ssc.start()//启动

ssc.awaitTermination()//等待终止命令

}

}