12.transform以及实时黑名单过滤案例实战

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transform以及实时黑名单过滤案例实战

transform操作，应用在DStream上时，可以用于执行任意的RDD到RDD的转换操作。它可以用于实现，DStream API中所没有提供的操作。比如说，DStream API中，并没有提供将一个DStream中的每个batch，与一个特定的RDD进行join的操作。但是我们自己就可以使用transform操作来实现该功能。

DStream.join()，只能join其他DStream。在DStream每个batch的RDD计算出来之后，会去跟其他DStream的RDD进行join。

案例：广告计费日志实时黑名单过滤

java版本：

  1.  class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="1">
class="hljs-ln-code"> class="hljs-ln-line">package cn.spark.study.streaming;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="2">
    • class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="3"> class="hljs-ln-code"> class="hljs-ln-line">import java.util.ArrayList;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="4"> class="hljs-ln-code"> class="hljs-ln-line">import java.util.List;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="5"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="6"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.SparkConf;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="7"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.api.java.JavaPairRDD;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="8"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.api.java.JavaRDD;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="9"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.api.java.function.Function;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="10"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.api.java.function.PairFunction;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="11"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.streaming.Durations;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="12"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.streaming.api.java.JavaDStream;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="13"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.streaming.api.java.JavaPairDStream;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="14"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.streaming.api.java.JavaReceiverInputDStream;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="15"> class="hljs-ln-code"> class="hljs-ln-line">import org.apache.spark.streaming.api.java.JavaStreamingContext;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="16"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="17"> class="hljs-ln-code"> class="hljs-ln-line">import com.google.common.base.Optional;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="18"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="19"> class="hljs-ln-code"> class="hljs-ln-line">import scala.Tuple2;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="20"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="21"> class="hljs-ln-code"> class="hljs-ln-line">/**
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="22"> class="hljs-ln-code"> class="hljs-ln-line"> * 基于transform的实时广告计费日志黑名单过滤
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="23"> class="hljs-ln-code"> class="hljs-ln-line"> * 这里案例，完全脱胎于真实的广告业务的大数据系统，业务是真实的，实用
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="24"> class="hljs-ln-code"> class="hljs-ln-line"> * @author Administrator
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="25"> class="hljs-ln-code"> class="hljs-ln-line"> *
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="26"> class="hljs-ln-code"> class="hljs-ln-line"> */
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="27"> class="hljs-ln-code"> class="hljs-ln-line">public class TransformBlacklist {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="28"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="29"> class="hljs-ln-code"> class="hljs-ln-line"> @SuppressWarnings("deprecation")
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="30"> class="hljs-ln-code"> class="hljs-ln-line"> public static void main(String[] args) {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="31"> class="hljs-ln-code"> class="hljs-ln-line"> SparkConf conf = new SparkConf()
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="32"> class="hljs-ln-code"> class="hljs-ln-line"> .setMaster("local[2]")
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="33"> class="hljs-ln-code"> class="hljs-ln-line"> .setAppName("TransformBlacklist");
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="34"> class="hljs-ln-code"> class="hljs-ln-line"> JavaStreamingContext jssc = new JavaStreamingContext(conf, Durations.seconds(5));
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="35"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="36"> class="hljs-ln-code"> class="hljs-ln-line"> // 用户对我们的网站上的广告可以进行点击
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="37"> class="hljs-ln-code"> class="hljs-ln-line"> // 点击之后，是不是要进行实时计费，点一下，算一次钱
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="38"> class="hljs-ln-code"> class="hljs-ln-line"> // 但是，对于那些帮助某些无良商家刷广告的人，那么我们有一个黑名单
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="39"> class="hljs-ln-code"> class="hljs-ln-line"> // 只要是黑名单中的用户点击的广告，我们就给过滤掉
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="40"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="41"> class="hljs-ln-code"> class="hljs-ln-line"> // 先做一份模拟的黑名单RDD
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="42"> class="hljs-ln-code"> class="hljs-ln-line"> List> blacklist = new ArrayList>();
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="43"> class="hljs-ln-code"> class="hljs-ln-line"> blacklist.add(new Tuple2("tom", true));
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="44"> class="hljs-ln-code"> class="hljs-ln-line"> final JavaPairRDD blacklistRDD = jssc.sc().parallelizePairs(blacklist);
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="45"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="46"> class="hljs-ln-code"> class="hljs-ln-line"> // 这里的日志格式，就简化一下，就是date username的方式
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="47"> class="hljs-ln-code"> class="hljs-ln-line"> JavaReceiverInputDStream adsClickLogDStream = jssc.socketTextStream("spark1", 9999);
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="48"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="49"> class="hljs-ln-code"> class="hljs-ln-line"> // 所以，要先对输入的数据，进行一下转换操作，变成，(username, date username)
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="50"> class="hljs-ln-code"> class="hljs-ln-line"> // 以便于，后面对每个batch RDD，与定义好的黑名单RDD进行join操作
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="51"> class="hljs-ln-code"> class="hljs-ln-line"> JavaPairDStream userAdsClickLogDStream = adsClickLogDStream.mapToPair(
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="52"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="53"> class="hljs-ln-code"> class="hljs-ln-line"> new PairFunction() {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="54"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="55"> class="hljs-ln-code"> class="hljs-ln-line"> private static final long serialVersionUID = 1L;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="56"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="57"> class="hljs-ln-code"> class="hljs-ln-line"> @Override
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="58"> class="hljs-ln-code"> class="hljs-ln-line"> public Tuple2 call(String adsClickLog)
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="59"> class="hljs-ln-code"> class="hljs-ln-line"> throws Exception {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="60"> class="hljs-ln-code"> class="hljs-ln-line"> return new Tuple2(
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="61"> class="hljs-ln-code"> class="hljs-ln-line"> adsClickLog.split(" ")[1], adsClickLog);
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="62"> class="hljs-ln-code"> class="hljs-ln-line"> }
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="63"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="64"> class="hljs-ln-code"> class="hljs-ln-line"> });
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="65"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="66"> class="hljs-ln-code"> class="hljs-ln-line"> // 然后，就可以执行transform操作了，将每个batch的RDD，与黑名单RDD进行join、filter、map等操作
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="67"> class="hljs-ln-code"> class="hljs-ln-line"> // 实时进行黑名单过滤
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="68"> class="hljs-ln-code"> class="hljs-ln-line"> JavaDStream validAdsClickLogDStream = userAdsClickLogDStream.transform(
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="69"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="70"> class="hljs-ln-code"> class="hljs-ln-line"> new Function, JavaRDD>() {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="71"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="72"> class="hljs-ln-code"> class="hljs-ln-line"> private static final long serialVersionUID = 1L;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="73"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="74"> class="hljs-ln-code"> class="hljs-ln-line"> @Override
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="75"> class="hljs-ln-code"> class="hljs-ln-line"> public JavaRDD call(JavaPairRDD userAdsClickLogRDD)
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="76"> class="hljs-ln-code"> class="hljs-ln-line"> throws Exception {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="77"> class="hljs-ln-code"> class="hljs-ln-line"> // 这里为什么用左外连接？
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="78"> class="hljs-ln-code"> class="hljs-ln-line"> // 因为，并不是每个用户都存在于黑名单中的
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="79"> class="hljs-ln-code"> class="hljs-ln-line"> // 所以，如果直接用join，那么没有存在于黑名单中的数据，会无法join到
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="80"> class="hljs-ln-code"> class="hljs-ln-line"> // 就给丢弃掉了
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="81"> class="hljs-ln-code"> class="hljs-ln-line"> // 所以，这里用leftOuterJoin，就是说，哪怕一个user不在黑名单RDD中，没有join到
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="82"> class="hljs-ln-code"> class="hljs-ln-line"> // 也还是会被保存下来的
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="83"> class="hljs-ln-code"> class="hljs-ln-line"> JavaPairRDD>> joinedRDD =
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="84"> class="hljs-ln-code"> class="hljs-ln-line"> userAdsClickLogRDD.leftOuterJoin(blacklistRDD);
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="85"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="86"> class="hljs-ln-code"> class="hljs-ln-line"> // 连接之后，执行filter算子
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="87"> class="hljs-ln-code"> class="hljs-ln-line"> JavaPairRDD>> filteredRDD =
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="88"> class="hljs-ln-code"> class="hljs-ln-line"> joinedRDD.filter(
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="89"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="90"> class="hljs-ln-code"> class="hljs-ln-line"> new Function
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="91"> class="hljs-ln-code"> class="hljs-ln-line"> Tuple2>>, Boolean>() {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="92"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="93"> class="hljs-ln-code"> class="hljs-ln-line"> private static final long serialVersionUID = 1L;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="94"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="95"> class="hljs-ln-code"> class="hljs-ln-line"> @Override
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="96"> class="hljs-ln-code"> class="hljs-ln-line"> public Boolean call(
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="97"> class="hljs-ln-code"> class="hljs-ln-line"> Tuple2
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="98"> class="hljs-ln-code"> class="hljs-ln-line"> Tuple2>> tuple)
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="99"> class="hljs-ln-code"> class="hljs-ln-line"> throws Exception {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="100"> class="hljs-ln-code"> class="hljs-ln-line"> // 这里的tuple，就是每个用户，对应的访问日志，和在黑名单中
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="101"> class="hljs-ln-code"> class="hljs-ln-line"> // 的状态
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="102"> class="hljs-ln-code"> class="hljs-ln-line"> if(tuple._2._2().isPresent() &&
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="103"> class="hljs-ln-code"> class="hljs-ln-line"> tuple._2._2.get()) {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="104"> class="hljs-ln-code"> class="hljs-ln-line"> return false;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="105"> class="hljs-ln-code"> class="hljs-ln-line"> }
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="106"> class="hljs-ln-code"> class="hljs-ln-line"> return true;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="107"> class="hljs-ln-code"> class="hljs-ln-line"> }
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="108"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="109"> class="hljs-ln-code"> class="hljs-ln-line"> });
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="110"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="111"> class="hljs-ln-code"> class="hljs-ln-line"> // 此时，filteredRDD中，就只剩下没有被黑名单过滤的用户点击了
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="112"> class="hljs-ln-code"> class="hljs-ln-line"> // 进行map操作，转换成我们想要的格式
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="113"> class="hljs-ln-code"> class="hljs-ln-line"> JavaRDD validAdsClickLogRDD = filteredRDD.map(
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="114"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="115"> class="hljs-ln-code"> class="hljs-ln-line"> new Function>>, String>() {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="116"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="117"> class="hljs-ln-code"> class="hljs-ln-line"> private static final long serialVersionUID = 1L;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="118"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="119"> class="hljs-ln-code"> class="hljs-ln-line"> @Override
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="120"> class="hljs-ln-code"> class="hljs-ln-line"> public String call(
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="121"> class="hljs-ln-code"> class="hljs-ln-line"> Tuple2>> tuple)
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="122"> class="hljs-ln-code"> class="hljs-ln-line"> throws Exception {
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="123"> class="hljs-ln-code"> class="hljs-ln-line"> return tuple._2._1;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="124"> class="hljs-ln-code"> class="hljs-ln-line"> }
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="125"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="126"> class="hljs-ln-code"> class="hljs-ln-line"> });
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="127"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="128"> class="hljs-ln-code"> class="hljs-ln-line"> return validAdsClickLogRDD;
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="129"> class="hljs-ln-code"> class="hljs-ln-line"> }
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="130"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="131"> class="hljs-ln-code"> class="hljs-ln-line"> });
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="132"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="133"> class="hljs-ln-code"> class="hljs-ln-line"> // 打印有效的广告点击日志
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="134"> class="hljs-ln-code"> class="hljs-ln-line"> // 其实在真实企业场景中，这里后面就可以走写入kafka、ActiveMQ等这种中间件消息队列
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="135"> class="hljs-ln-code"> class="hljs-ln-line"> // 然后再开发一个专门的后台服务，作为广告计费服务，执行实时的广告计费，这里就是只拿到了有效的广告点击
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="136"> class="hljs-ln-code"> class="hljs-ln-line"> validAdsClickLogDStream.print();
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="137"> class="hljs-ln-code"> class="hljs-ln-line">
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="138"> class="hljs-ln-code"> class="hljs-ln-line"> jssc.start();
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="139"> class="hljs-ln-code"> class="hljs-ln-line"> jssc.awaitTermination();
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="140"> class="hljs-ln-code"> class="hljs-ln-line"> jssc.close();
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="141"> class="hljs-ln-code"> class="hljs-ln-line"> }
  • class="hljs-ln-numbers"> class="hljs-ln-line hljs-ln-n" data-line-number="142"> class="hljs-ln-code"> class="hljs-ln-line">}
    •  class="hide-preCode-box"> class="hljs-button signin active" data-title="登录复制" data-report-click="{"spm":"1001.2101.3001.4334"}" onclick="hljs.signin(event)">

    scala版本：

     

    package cn.spark.study.streaming
 
import org.apache.spark.SparkConf
import org.apache.spark.streaming.StreamingContext
import org.apache.spark.streaming.Seconds
 
/**
 * @author Administrator
 */
object TransformBlacklist {
  
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf()
        .setMaster("local[2]")  
        .setAppName("TransformBlacklist")
    val ssc = new StreamingContext(conf, Seconds(5))
    
    val blacklist = Array(("tom", true))  
    val blacklistRDD = ssc.sparkContext.parallelize(blacklist, 5)  
    
    val adsClickLogDStream = ssc.socketTextStream("spark1", 9999)   
    val userAdsClickLogDStream = adsClickLogDStream
        .map { adsClickLog => (adsClickLog.split(" ")(1), adsClickLog) }
    
    val validAdsClickLogDStream = userAdsClickLogDStream.transform(userAdsClickLogRDD => {
      val joinedRDD = userAdsClickLogRDD.leftOuterJoin(blacklistRDD)
      val filteredRDD = joinedRDD.filter(tuple => {
        if(tuple._2._2.getOrElse(false)) {  
          false
        } else {
          true
        }
      })
      val validAdsClickLogRDD = filteredRDD.map(tuple => tuple._2._1)
      validAdsClickLogRDD
    })
    
    validAdsClickLogDStream.print()
    
    ssc.start()
    ssc.awaitTermination()
  }
} class="hide-preCode-box">

    运行步骤：

     

    1.启动nc

    nc -lk 9999

    2.本地运行，直接在IDE中运行程序

    运行结果：

     

     

    文章最后，给大家推荐一些受欢迎的技术博客链接：

    1. Hadoop相关技术博客链接
    2. Spark 核心技术链接
    3. JAVA相关的深度技术博客链接
    4. 超全干货--Flink思维导图，花了3周左右编写、校对
    5. 深入JAVA 的JVM核心原理解决线上各种故障【附案例】
    6. 请谈谈你对volatile的理解？--最近小李子与面试官的一场“硬核较量”
    7. 聊聊RPC通信，经常被问到的一道面试题。源码+笔记，包懂

     

    欢迎扫描下方的二维码或 搜索 公众号“10点进修”，我们会有更多、且及时的资料推送给您，欢迎多多交流！

                                               

           

    >>
    注：本文转载自blog.csdn.net的不埋雷的探长的文章"https://blog.csdn.net/weixin_32265569/article/details/78571497"。版权归原作者所有，此博客不拥有其著作权，亦不承担相应法律责任。如有侵权，请联系我们删除。
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