SparkStreaming的实现和使用方法

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一.DStream 整合RDD

1.官网算子

2.使用案例

生产中使用多的是一个文件中有很多域名，另一个中是黑名单，要进行剔除数据一：日志信息    DStream    domain,traffic    xinlang.com    xinlang.com    baidu.com数据二：已有的文件  黑名单  RDD    domain    baidu.com

3.RDD实现上述需求

package sparkstreaming02import org.apache.spark.{SparkConf, SparkContext}import scala.collection.mutable.ListBufferobject Demo1 {  def main(args: Array[String]): Unit = {    val conf = new SparkConf().setAppName("Demo1").setMaster("local[2]")    val sc = new SparkContext(conf)    val input1 = new ListBuffer[(String,Long)]    input1.append(("www.xinlang.com", 8888))    input1.append(("www.xinalng.com", 9999))    input1.append(("www.baidu.com", 7777))    val data1 = sc.parallelize(input1)    //进行join一定要是key,value形式的    val input2 = new ListBuffer[(String,Boolean)]    input2.append(("www.baidu.com",true))    val data2 = sc.parallelize(input2)    data1.leftOuterJoin(data2)      .filter(x => {        x._2._2.getOrElse(false) != true      }).map(x => (x._1,x._2._1))      .collect().foreach(println)  }}

4.SparkStreaming实现

package sparkstreaming02import org.apache.spark.SparkConfimport org.apache.spark.streaming.{Seconds, StreamingContext}import scala.collection.mutable.ListBufferobject Streaming {  def main(args: Array[String]): Unit = {    val conf = new SparkConf().setAppName("Streaming").setMaster("local[2]")    val ssc = new StreamingContext(conf,Seconds(10))    val lines = ssc.socketTextStream("s201",9999)    // 数据二： rdd    val input2 = new ListBuffer[(String,Boolean)]    input2.append(("www.baidu.com",true))    val data2 = ssc.sparkContext.parallelize(input2)    lines.map(x=>(x.split(",")(0), x)).transform(      rdd => {        rdd.leftOuterJoin(data2)          .filter(x => {            x._2._2.getOrElse(false) != true //注意 join之后过滤          }).map(x => (x._1,x._2._1))      }    ).print()    ssc.start()    ssc.awaitTermination()  }}

二.SparkStreaming插入外部数据源

1.插入外部数据源用的，但是使用这个有几个坑

、

2.错误一官网例子

3.原因

connect 在Driver端创建，record在executor，发过去序列化错误

4.解决

解决：第一种把connect放到executor端这样弊端是每条记录会生成一个connect太耗费资源        words.foreachRDD { rdd =>          rdd.foreach { record =>            val connection = createConnection()  // executed at the driver            val word = record._1            val count = record._2.toInt            val sql = s"insert into wc (wc,count) values($word,$count)"           connection.createStatement().execute(sql)         }

5.最终解决办法

package sparkstreaming02import java.sql.DriverManagerimport org.apache.spark.SparkConfimport org.apache.spark.streaming.{Seconds, StreamingContext}object MysqlStreaming {  def main(args: Array[String]): Unit = {    val conf = new SparkConf().setMaster("local[2]").setAppName("MysqlStreaming")    val ssc = new StreamingContext(conf,Seconds(1))    val lines = ssc.socketTextStream("s201",9999)    val words = lines.flatMap(x => x.split(",")).map((_,1)).reduceByKey(_+_)//    words.foreachRDD { rdd =>//      val connection = createConnection()  // executed at the driver//      rdd.foreach { record =>//        val word = record._1//        val count = record._2//        val sql = s"insert into wc (word,count) values($word,$count)"//        connection.createStatement().execute(sql)//      }//    }//        words.foreachRDD { rdd =>//          rdd.foreach { record =>//            val connection = createConnection()  // executed at the driver//            val word = record._1//            val count = record._2.toInt//            val sql = s"insert into wc (wc,count) values($word,$count)"//            connection.createStatement().execute(sql)//          }//        }    //最终的写法    words.foreachRDD { rdd =>      rdd.foreachPartition { partitionOfRecords =>        val connection = createConnection()        partitionOfRecords.foreach(          record =>{        val word = record._1        val count = record._2        val sql = s"insert into wc (wc,count) values('$word',$count)"        connection.createStatement().execute(sql)}        )      }    }    ssc.start()    ssc.awaitTermination()  }  def createConnection() = {    Class.forName("com.mysql.cj.jdbc.Driver")    DriverManager.getConnection("jdbc:mysql://localhost:3306/hive?serverTimezone=UTC&useSSL=false","root","123456")  }}

6.出现问题

错误，插入数据库时，你要插入字符串要用''例如：val sql = s"insert into wc (wc,count) values($word,$count)"word是字符串，你要不加双引号就报这个错误正确val sql = s"insert into wc (wc,count) values('$word',$count)"

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