sparkStreaming入门

1.环境

jdk : 1.8

scala : 2.11.7

hadoop:2.7

spark : 2.2.0

2. 开发工具

idea 2017.2

3.maven的pom文件

<dependencies>


<dependency>
<groupId>org.apache.maven</groupId>
<artifactId>maven-core</artifactId>
<version>3.5.0</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.39</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_${scala.version}</artifactId>
<version>${spark.version}</version>
</dependency>
</dependencies>

4.sparkStreaming通过本地的socket端口解析日志

package test02

import org.apache.spark.SparkConf
import org.apache.spark.streaming.Seconds
import org.apache.spark.streaming.StreamingContext

object demo5 {
  def main (args : Array[String]) {
    val conf = new SparkConf().setMaster("local[4]").setAppName("SaprkApp")
    val ssc = new StreamingContext(conf, Seconds(10))
    val lines = ssc.socketTextStream("localhost", 9999)

    //测试数据 : 2017-07-18 11:02:52.032 INFO   172.31.20.232:56965 18583551@170718110244697@172.31.33.81 PUBLIC_USER_LOGIN(0202)-0 create session for 18583551/18583551@170718110244697@172.31.33.81
    val loginRDD = lines.map(line =>{
      val pattern = """^(\S+\s\d+\:\d+\:\d+\.\d{3})\s+\S+\s+(\d+\.\d+.\d+\.\d+):\d+\S+\s+(\d+)@(\S+)@\S+\s+PUBLIC_USER_LOGIN\(0202\)-0\s+create session for.*""".r
      var login_time = ""
      var ip_address = ""
      var passport_id = ""
      var session_id = ""
      var scene_name = "login"
      pattern.findAllIn(line).matchData foreach{m =>{
        login_time = m.group(1)
        ip_address = m.group(2)
        passport_id = m.group(3)
        session_id  = m.group(4)

        println(login_time)
        println(ip_address)
        println(passport_id)
        println(session_id)

      }}
      (login_time,ip_address,passport_id,session_id,scene_name)
    })
    val loginRes = loginRDD.filter(_._1 != "").filter(_._2 != "")
    loginRes.print()

    //测试数据 : 2017-07-18 11:03:44.312 INFO   0.0.0.0:18402 26639185@170718110334147@172.31.32.135 ADMIN_SYSTEM_SUCCESS(00FE)-84581  -> USER_DISCONNECTED Time cost 9.09ms
    val logoutRDD = lines.map(line =>{
      val pattern = """^(\S+\s\d+\:\d+\:\d+\.\d{3})\s+\S+\s+(\d+\.\d+\.\d+\.\d+):\d+\S+\s+(\d+)@(\S+)@.*(disconnected|DISCONNECTED).*""".r
      var login_id = ""
      var ip = ""
      var passport_id = ""
      var str = ""
      var scene_name = "logout"
      pattern.findAllIn(line).matchData foreach{m =>{
        login_id = m.group(1)
        ip = m.group(2)
        passport_id = m.group(3)
        str = m.group(4)

        println(login_id)
        println(ip)
        println(passport_id)
        println(str)

      }}
      (login_id,ip,passport_id,str)
    })
    val logoutRes = logoutRDD.filter(_._1 != "").filter(_._2 != "")
    logoutRes.print()
    logoutRes.saveAsTextFiles("/Users/huiliyang/streaming/aa")

    //测试数据 : 2017-08-27 06:04:38.420 [info] <0.3471.83> 172.31.2.201:59154 70281275 PUBLIC_SERVER_CLIENT_LOG(258)-0 LovelyStreet:1228
    val eventRDD = lines.map(line =>{
      val pattern = """^(\S+\s\d+\:\d+\:\d+\.\d{3})\s+\[info\]\s<[\d\.]*>\s?(\d+\.\d+\.\d+.\d+):\d+\S+\s+\S?([1-9]\d{7})(@\d+@\d+\.\d+\.\d+\.\d+)?\S?\s+PUBLIC_(SERVER|SYSTEM)_CLIENT\S+\s(\S+):(\d+)""".r
      var login_time = ""
      var ip_address = ""
      var passport_id = ""
      var session_id = ""
      var str1 = ""
      var str2 = ""
      var str3 = ""
      pattern.findAllIn(line).matchData foreach{m =>{
        login_time = m.group(1)
        ip_address = m.group(2)
        passport_id = m.group(3)
        session_id  = m.group(4)
        str1  = m.group(5)
        str2  = m.group(6)
        str3  = m.group(7)

        println(login_time)
        println(ip_address)
        println(passport_id)
        println(session_id)
        println(str1)
        println(str2)
        println(str3)

      }}
      (login_time,ip_address,passport_id,session_id,str1,str2,str3)
    })
    val eventRes = eventRDD.filter(_._1 != "").filter(_._2 != "")
    eventRes.print()

    ssc.start()
    ssc.awaitTermination()

  }
}

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sparkStreaming入门

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