Spark查找某个IP的归属地，二分算法，try{}catch{}的使用，将结果存MySQL数据库

2019年3月15日 212次阅读 来源: 查找算法

1、创建Maven工程

调整Maven仓库所在的位置，具体参考：http://blog.csdn.net/tototuzuoquan/article/details/74571374

2、编写Pom文件

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>cn.toto.spark</groupId>
    <artifactId>bigdata</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>1.7</maven.compiler.source>
        <maven.compiler.target>1.7</maven.compiler.target>
        <encoding>UTF-8</encoding>
        <scala.version>2.10.6</scala.version>
        <spark.version>1.6.2</spark.version>
        <hadoop.version>2.6.4</hadoop.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.10</artifactId>
            <version>${spark.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>${hadoop.version}</version>
        </dependency>

        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.38</version>
        </dependency>
    </dependencies>

    <build>
        <sourceDirectory>src/main/scala</sourceDirectory>
        <testSourceDirectory>src/test/scala</testSourceDirectory>
        <plugins>
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <version>3.2.2</version>
                <executions>
                    <execution>
                        <goals>
                            <goal>compile</goal>
                            <goal>testCompile</goal>
                        </goals>
                        <configuration>
                            <args>
                                <arg>-make:transitive</arg>
                                <arg>-dependencyfile</arg>
                                <arg>${project.build.directory}/.scala_dependencies</arg>
                            </args>
                        </configuration>
                    </execution>
                </executions>
            </plugin>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-shade-plugin</artifactId>
                <version>2.4.3</version>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>shade</goal>
                        </goals>
                        <configuration>
                            <filters>
                                <filter>
                                    <artifact>*:*</artifact>
                                    <excludes>
                                        <exclude>META-INF/*.SF</exclude>
                                        <exclude>META-INF/*.DSA</exclude>
                                        <exclude>META-INF/*.RSA</exclude>
                                    </excludes>
                                </filter>
                            </filters>
                        </configuration>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>

</project>

3、准备要处理的文件

其中ip信息的文件（ip.txt）如下：
《Spark查找某个IP的归属地，二分算法，try{}catch{}的使用，将结果存MySQL数据库》

1.0.1.0|1.0.3.255|16777472|16778239|亚洲|中国|福建|福州||电信|350100|China|CN|119.306239|26.075302
1.0.8.0|1.0.15.255|16779264|16781311|亚洲|中国|广东|广州||电信|440100|China|CN|113.280637|23.125178
1.0.32.0|1.0.63.255|16785408|16793599|亚洲|中国|广东|广州||电信|440100|China|CN|113.280637|23.125178
1.1.0.0|1.1.0.255|16842752|16843007|亚洲|中国|福建|福州||电信|350100|China|CN|119.306239|26.075302
1.1.2.0|1.1.7.255|16843264|16844799|亚洲|中国|福建|福州||电信|350100|China|CN|119.306239|26.075302
1.1.8.0|1.1.63.255|16844800|16859135|亚洲|中国|广东|广州||电信|440100|China|CN|113.280637|23.125178
1.2.0.0|1.2.1.255|16908288|16908799|亚洲|中国|福建|福州||电信|350100|China|CN|119.306239|26.075302

数据访问文件（access.log）如下：**
《Spark查找某个IP的归属地，二分算法，try{}catch{}的使用，将结果存MySQL数据库》

20090121000132095572000|125.213.100.123|show.51.com|/shoplist.php?phpfile=shoplist2.php&style=1&sex=137|Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; Mozilla/4.0(Compatible Mozilla/4.0(Compatible-EmbeddedWB 14.59 http://bsalsa.com/ EmbeddedWB- 14.59  from: http://bsalsa.com/ )|http://show.51.com/main.php|
20090121000132124542000|117.101.215.133|www.jiayuan.com|/19245971|Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; TencentTraveler 4.0)|http://photo.jiayuan.com/index.php?uidhash=d1c3b69e9b8355a5204474c749fb76ef|__tkist=0; myloc=50%7C5008; myage=2009; PROFILE=14469674%3A%E8%8B%A6%E6%B6%A9%E5%92%96%E5%95%A1%3Am%3Aphotos2.love21cn.com%2F45%2F1b%2F388111afac8195cc5d91ea286cdd%3A1%3A%3Ahttp%3A%2F%2Fimages.love21cn.com%2Fw4%2Fglobal%2Fi%2Fhykj_m.jpg; last_login_time=1232454068; SESSION_HASH=8176b100a84c9a095315f916d7fcbcf10021e3af; RAW_HASH=008a1bc48ff9ebafa3d5b4815edd04e9e7978050; COMMON_HASH=45388111afac8195cc5d91ea286cdd1b; pop_1232093956=1232468896968; pop_time=1232466715734; pop_1232245908=1232469069390; pop_1219903726=1232477601937; LOVESESSID=98b54794575bf547ea4b55e07efa2e9e; main_search:14469674=%7C%7C%7C00; registeruid=14469674; REG_URL_COOKIE=http%3A%2F%2Fphoto.jiayuan.com%2Fshowphoto.php%3Fuid_hash%3D0319bc5e33ba35755c30a9d88aaf46dc%26total%3D6%26p%3D5; click_count=0%2C3363619
20090121000132406516000|117.101.222.68|gg.xiaonei.com|/view.jsp?p=389|Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; CIBA)|http://home.xiaonei.com/Home.do?id=229670724|_r01_=1; __utma=204579609.31669176.1231940225.1232462740.1232467011.145; __utmz=204579609.1231940225.1.1.utmccn=(direct)
20090121000132581311000|115.120.36.118|tj.tt98.com|/tj.htm|Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; TheWorld)|http://www.tt98.com/|

4.获取ip归属地信息

package cn.toto.spark

import java.io.{BufferedReader, FileInputStream, InputStreamReader}

import scala.collection.mutable.ArrayBuffer

/** * Created by toto on 2017/7/8. * 查找IP的归属地信息 */
object IPLocationDemo {

  def ip2Long(ip: String): Long = {
    val fragments = ip.split("[.]")
    var ipNum = 0L
    for (i <- 0 until fragments.length){
      ipNum =  fragments(i).toLong | ipNum << 8L
    }
    ipNum
  }

  def readData(path: String) = {
    val br = new BufferedReader(new InputStreamReader(new FileInputStream(path)))
    var s: String = null
    var flag = true
    val lines = new ArrayBuffer[String]()
    while (flag)
    {
      s = br.readLine()
      if (s != null)
        lines += s
      else
        flag = false
    }
    lines
  }

  def binarySearch(lines: ArrayBuffer[String], ip: Long) : Int = {
    var low = 0
    var high = lines.length - 1
    while (low <= high) {
      val middle = (low + high) / 2
      if ((ip >= lines(middle).split("\\|")(2).toLong) && (ip <= lines(middle).split("\\|")(3).toLong))
        return middle
      if (ip < lines(middle).split("\\|")(2).toLong)
        high = middle - 1
      else {
        low = middle + 1
      }
    }
    -1
  }

  /** * 运行后的结果是： * 2016917821 * 120.55.0.0|120.55.255.255|2016870400|2016935935|亚洲|中国|浙江|杭州||阿里巴巴|330100|China|CN|120.153576|30.287459 * * 要求2016917821 在 |2016870400|2016935935| 之间。 * @param args */
  def main(args: Array[String]): Unit = {
    val ip = "120.55.185.61"
    val ipNum = ip2Long(ip)
    println(ipNum)
    val lines = readData("E:\\learnTempFolder\\ip.txt")
    val index = binarySearch(lines, ipNum)
    print(lines(index))
  }
}

运行结果：
《Spark查找某个IP的归属地，二分算法，try{}catch{}的使用，将结果存MySQL数据库》

5.查询IP归属地相关信息，并将这些信息存储到MySQL数据库中

代码如下：

package cn.toto.spark

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

import org.apache.spark.{SparkConf, SparkContext}

/** * Created by toto on 2017/7/8. */
object IPLocation {

  val data2MySQL = (iterator: Iterator[(String, Int)]) => {
    var conn: Connection = null
    var ps : PreparedStatement = null
    val sql = "INSERT INTO location_info (location, counts, accesse_date) VALUES (?, ?, ?)"
    try {
      conn = DriverManager.getConnection("jdbc:mysql://192.168.106.100:3306/bigdata", "root", "123456")
      iterator.foreach(line => {
        ps = conn.prepareStatement(sql)
        ps.setString(1, line._1)
        ps.setInt(2, line._2)
        ps.setDate(3, new Date(System.currentTimeMillis()))
        ps.executeUpdate()
      })
    } catch {
      case e: Exception => println("Mysql Exception")
    } finally {
      if (ps != null)
        ps.close()
      if (conn != null)
        conn.close()
    }
  }

  def ip2Long(ip: String): Long = {
    val fragments = ip.split("[.]")
    var ipNum = 0L
    for (i <- 0 until fragments.length){
      ipNum =  fragments(i).toLong | ipNum << 8L
    }
    ipNum
  }

  def binarySearch(lines: Array[(String, String, String)], ip: Long) : Int = {
    var low = 0
    var high = lines.length - 1
    while (low <= high) {
      val middle = (low + high) / 2
      if ((ip >= lines(middle)._1.toLong) && (ip <= lines(middle)._2.toLong))
        return middle
      if (ip < lines(middle)._1.toLong)
        high = middle - 1
      else {
        low = middle + 1
      }
    }
    -1
  }

  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setMaster("local[2]").setAppName("IpLocation")
    val sc = new SparkContext(conf)

    val ipRulesRdd = sc.textFile("E://workspace//ip.txt").map(line =>{
      val fields = line.split("\\|")
      val start_num = fields(2)
      val end_num = fields(3)
      val province = fields(6)
      (start_num, end_num, province)
    })
    //全部的ip映射规则
    val ipRulesArrary = ipRulesRdd.collect()

    //广播规则
    val ipRulesBroadcast = sc.broadcast(ipRulesArrary)

    //加载要处理的数据
    val ipsRDD = sc.textFile("E://workspace//access.log").map(line => {
      val fields = line.split("\\|")
      fields(1)
    })

    val result = ipsRDD.map(ip => {
      val ipNum = ip2Long(ip)
      val index = binarySearch(ipRulesBroadcast.value, ipNum)
      val info = ipRulesBroadcast.value(index)
      //(ip的起始Num， ip的结束Num，省份名)
      info
    }).map(t => (t._3, 1)).reduceByKey(_+_)

    //向MySQL写入数据
    result.foreachPartition(data2MySQL(_))

    //println(result.collect().toBuffer)
    sc.stop()
  }
}

数据库SQL：

CREATE DATABASE bigdata CHARACTER SET utf8;

USE bigdata;

CREATE TABLE location_info ( id INT(10) AUTO_INCREMENT PRIMARY KEY, location VARCHAR(100), counts INT(10), accesse_date DATE ) ENGINE=INNODB DEFAULT CHARSET=utf8;

运行程序，运行结果后：
《Spark查找某个IP的归属地，二分算法，try{}catch{}的使用，将结果存MySQL数据库》

    原文作者：查找算法
    原文地址: https://blog.csdn.net/tototuzuoquan/article/details/74858512
    本文转自网络文章，转载此文章仅为分享知识，如有侵权，请联系博主进行删除。
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