spark streaming从指定offset处消费Kafka数据

﹏ヽ暗。殇╰゛Y 2022-04-02 05:46 463阅读 0赞

### 一. 前言 ###

当spark streaming程序意外退出时，数据仍然再往Kafka中推送，然而由于Kafka默认是从latest的offset读取，这会导致数据丢失。为了避免数据丢失，那么我们需要记录每次消费的offset，以便下次检查并且从指定的offset开始读取

### 二. 环境 ###

kafka-0.9.0、spark-1.6.0、jdk-1.7、scala-2.10.5、idea16

### 三. 实现代码 ###

#### 1. 引入spark和kafka的相关依赖包 ####

<?xml version="1.0" encoding="UTF-8"?>  
    <project xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  
             xmlns="http://maven.apache.org/POM/4.0.0"  
             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>com.ngaa</groupId>  
        <artifactId>test-my</artifactId>  
        <version>1.0-SNAPSHOT</version>  
        <inceptionYear>2008</inceptionYear>  
        <properties>  
            <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>  
            <project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>  
              
            <maven.compiler.source>1.7</maven.compiler.source>  
            <maven.compiler.target>1.7</maven.compiler.target>  
            <encoding>UTF-8</encoding>  
              
            <scala.version>2.10.5</scala.version>  
              
            <test.scala.version>2.11.7</test.scala.version>  
      
            <jackson.version>2.3.0</jackson.version>  
              
            <slf4j-version>1.7.20</slf4j-version>  
              
            <spark.cdh.version>1.6.0-cdh5.8.0</spark.cdh.version>  
            <spark.streaming.cdh.version>1.6.0-cdh5.8.0</spark.streaming.cdh.version>  
            <kafka.spark.cdh.version>1.6.0-cdh5.8.0</kafka.spark.cdh.version>  
              
            <hadoop.cdh.version>2.6.0-cdh5.8.0</hadoop.cdh.version>  
              
            <httpclient.version>4.2.5</httpclient.version>  
      
              
            <httpcore.version>4.2.5</httpcore.version>  
              
            <fastjson.version>1.1.39</fastjson.version>  
      
        </properties>  
      
        <repositories>  
            <repository>  
                <id>scala-tools.org</id>  
                <name>Scala-Tools Maven2 Repository</name>  
                <url>http://scala-tools.org/repo-releases</url>  
            </repository>  
              
            <repository>  
                <id>cloudera</id>  
                <url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>  
            </repository>  
        </repositories>  
      
        <pluginRepositories>  
            <pluginRepository>  
                <id>scala-tools.org</id>  
                <name>Scala-Tools Maven2 Repository</name>  
                <url>http://scala-tools.org/repo-releases</url>  
            </pluginRepository>  
        </pluginRepositories>  
      
        <dependencies>  
      
              
            <dependency>  
                <groupId>com.alibaba</groupId>  
                <artifactId>fastjson</artifactId>  
                <version>${fastjson.version}</version>  
            </dependency>  
              
            <dependency>  
                <groupId>org.apache.httpcomponents</groupId>  
                <artifactId>httpclient</artifactId>  
                <version>${httpclient.version}</version>  
            </dependency>  
      
              
            <dependency>  
                <groupId>org.apache.httpcomponents</groupId>  
                <artifactId>httpcore</artifactId>  
                <version>${httpcore.version}</version>  
            </dependency>  
      
              
            <dependency>  
                <groupId>org.slf4j</groupId>  
                <artifactId>slf4j-log4j12</artifactId>  
                <version>${slf4j-version}</version>  
            </dependency>  
              
            <dependency>  
                <groupId>org.apache.hadoop</groupId>  
                <artifactId>hadoop-client</artifactId>  
                <version>${hadoop.cdh.version}</version>  
                <exclusions>  
                    <exclusion>  
                        <groupId>javax.servlet</groupId>  
                        <artifactId>*</artifactId>  
                    </exclusion>  
                </exclusions>  
            </dependency>  
            <dependency>  
                <groupId>org.apache.hadoop</groupId>  
                <artifactId>hadoop-common</artifactId>  
                <version>${hadoop.cdh.version}</version>  
                <exclusions>  
                    <exclusion>  
                        <groupId>javax.servlet</groupId>  
                        <artifactId>*</artifactId>  
                    </exclusion>  
                </exclusions>  
            </dependency>  
            <dependency>  
                <groupId>org.apache.hadoop</groupId>  
                <artifactId>hadoop-hdfs</artifactId>  
                <version>${hadoop.cdh.version}</version>  
                <exclusions>  
                    <exclusion>  
                        <groupId>javax.servlet</groupId>  
                        <artifactId>*</artifactId>  
                    </exclusion>  
                </exclusions>  
            </dependency>  
              
            <dependency>  
                <groupId>org.scala-lang</groupId>  
                <artifactId>scala-library</artifactId>  
                <version>${scala.version}</version>  
            </dependency>  
            <dependency>  
                <groupId>com.fasterxml.jackson.core</groupId>  
                <artifactId>jackson-databind</artifactId>  
                <version>${jackson.version}</version>  
            </dependency>  
      
              
            <dependency>  
                <groupId>org.apache.spark</groupId>  
                <artifactId>spark-streaming_2.10</artifactId>  
                <version>${spark.streaming.cdh.version}</version>  
            </dependency>  
            <dependency>  
                <groupId>org.apache.spark</groupId>  
                <artifactId>spark-streaming-kafka_2.10</artifactId>  
                <version>${kafka.spark.cdh.version}</version>  
            </dependency>  
            <dependency>  
                <groupId>junit</groupId>  
                <artifactId>junit</artifactId>  
                <version>4.12</version>  
                <scope>test</scope>  
            </dependency>  
      
              
            <dependency>  
            <groupId>org.apache.spark</groupId>  
            <artifactId>spark-assembly_2.10</artifactId>  
            <version>${spark.cdh.version}</version>  
            <scope>system</scope>  
            <systemPath>D:/crt_send_document/spark-assembly-1.6.0-cdh5.8.0-hadoop2.6.0-cdh5.8.0.jar</systemPath>  
            </dependency>  
      
              
              
                  
                  
                  
                  
                  
                  
              
      
              
              
              
              
              
              
      
              
            <dependency>  
                <groupId>org.apache.hadoop</groupId>  
                <artifactId>hadoop-yarn-server-web-proxy</artifactId>  
                <version>2.6.0-cdh5.8.0</version>  
            </dependency>  
      
        </dependencies>  
      
          
        <build>  
            <finalName>test-my</finalName>  
            <sourceDirectory>src/main/scala</sourceDirectory>  
            <testSourceDirectory>src/test/scala</testSourceDirectory>  
            <plugins>  
                <plugin>  
                    <groupId>org.scala-tools</groupId>  
                    <artifactId>maven-scala-plugin</artifactId>  
                    <version>2.15.2</version>  
                    <executions>  
                        <execution>  
                            <goals>  
                                <goal>compile</goal>  
                                <goal>testCompile</goal>  
                            </goals>  
                        </execution>  
                    </executions>  
                    <configuration>  
                        <scalaVersion>${scala.version}</scalaVersion>  
                        <args>  
                            <arg>-target:jvm-1.7</arg>  
                        </args>  
                    </configuration>  
                </plugin>  
                <plugin>  
                    <groupId>org.apache.maven.plugins</groupId>  
                    <artifactId>maven-eclipse-plugin</artifactId>  
                    <configuration>  
                        <downloadSources>true</downloadSources>  
                        <buildcommands>  
                            <buildcommand>ch.epfl.lamp.sdt.core.scalabuilder</buildcommand>  
                        </buildcommands>  
                        <additionalProjectnatures>  
                            <projectnature>ch.epfl.lamp.sdt.core.scalanature</projectnature>  
                        </additionalProjectnatures>  
                        <classpathContainers>  
                            <classpathContainer>org.eclipse.jdt.launching.JRE_CONTAINER</classpathContainer>  
                            <classpathContainer>ch.epfl.lamp.sdt.launching.SCALA_CONTAINER</classpathContainer>  
                        </classpathContainers>  
                    </configuration>  
                </plugin>  
                <plugin>  
                    <artifactId>maven-assembly-plugin</artifactId>  
                    <configuration>  
                        <descriptorRefs>  
                            <descriptorRef>jar-with-dependencies</descriptorRef>  
                        </descriptorRefs>  
                        <archive>  
                            <manifest>  
                                <mainClass></mainClass>  
                            </manifest>  
                        </archive>  
                    </configuration>  
                    <executions>  
                        <execution>  
                            <id>make-assembly</id>  
                            <phase>package</phase>  
                            <goals>  
                                <goal>single</goal>  
                            </goals>  
                        </execution>  
                    </executions>  
                </plugin>  
            </plugins>  
        </build>  
        <reporting>  
            <plugins>  
                <plugin>  
                    <groupId>org.scala-tools</groupId>  
                    <artifactId>maven-scala-plugin</artifactId>  
                    <configuration>  
                        <scalaVersion>${scala.version}</scalaVersion>  
                    </configuration>  
                </plugin>  
            </plugins>  
        </reporting>  
      
    </project>

#### 2. 新建测试类 ####

import kafka.common.TopicAndPartition  
    import kafka.message.MessageAndMetadata  
    import kafka.serializer.StringDecoder  
    import org.apache.log4j.{Level, Logger}  
    import org.apache.spark.{SparkConf, TaskContext}  
    import org.apache.spark.streaming.dstream.InputDStream  
    import org.apache.spark.streaming.kafka.{HasOffsetRanges, KafkaUtils, OffsetRange}  
    import org.apache.spark.streaming.{Seconds, StreamingContext}  
    import org.slf4j.LoggerFactory  
      
    /** 
      * Created by yangjf on 2016/12/18 
      * Update date: 
      * Time: 11:10 
      * Describle :从指定偏移量读取kafka数据 
      * Result of Test: 
      * Command: 
      * Email: jifei.yang@ngaa.com.cn 
      */  
    object ReadBySureOffsetTest {  
      val logger = LoggerFactory.getLogger(ReadBySureOffsetTest.getClass)  
      
      def main(args: Array[String]) {  
        //设置打印日志级别  
        Logger.getLogger("org.apache.kafka").setLevel(Level.ERROR)  
        Logger.getLogger("org.apache.zookeeper").setLevel(Level.ERROR)  
        Logger.getLogger("org.apache.spark").setLevel(Level.ERROR)  
        logger.info("测试从指定offset消费kafka的主程序开始")  
        if (args.length < 1) {  
          System.err.println("Your arguments were " + args.mkString(","))  
          System.exit(1)  
          logger.info("主程序意外退出")  
        }  
        //hdfs://hadoop1:8020/user/root/spark/checkpoint  
        val Array(checkpointDirectory) = args  
        logger.info("checkpoint检查：" + checkpointDirectory)  
        val ssc = StreamingContext.getOrCreate(checkpointDirectory,  
          () => {  
            createContext(checkpointDirectory)  
          })  
        logger.info("streaming开始启动")  
        ssc.start()  
        ssc.awaitTermination()  
      }  
      
      def createContext(checkpointDirectory: String): StreamingContext = {  
        //获取配置  
        val brokers = "hadoop3:9092,hadoop4:9092"  
        val topics = "20161218a"  
      
        //默认为5秒  
        val split_rdd_time = 8  
        // 创建上下文  
        val sparkConf = new SparkConf()  
          .setAppName("SendSampleKafkaDataToApple").setMaster("local[2]")  
          .set("spark.app.id", "streaming_kafka")  
      
        val ssc = new StreamingContext(sparkConf, Seconds(split_rdd_time))  
      
        ssc.checkpoint(checkpointDirectory)  
      
        // 创建包含brokers和topic的直接kafka流  
        val topicsSet: Set[String] = topics.split(",").toSet  
        //kafka配置参数  
        val kafkaParams: Map[String, String] = Map[String, String](  
          "metadata.broker.list" -> brokers,  
          "group.id" -> "apple_sample",  
          "serializer.class" -> "kafka.serializer.StringEncoder"  
    //      "auto.offset.reset" -> "largest"   //自动将偏移重置为最新偏移（默认）  
    //      "auto.offset.reset" -> "earliest"  //自动将偏移重置为最早的偏移  
    //      "auto.offset.reset" -> "none"      //如果没有为消费者组找到以前的偏移，则向消费者抛出异常  
        )  
        /** 
          * 从指定位置开始读取kakfa数据 
          * 注意：由于Exactly  Once的机制，所以任何情况下，数据只会被消费一次！ 
          *      指定了开始的offset后，将会从上一次Streaming程序停止处，开始读取kafka数据 
          */  
        val offsetList = List((topics, 0, 22753623L),(topics, 1, 327041L))                          //指定topic，partition_no，offset  
        val fromOffsets = setFromOffsets(offsetList)     //构建参数  
        val messageHandler = (mam: MessageAndMetadata[String, String]) => (mam.topic, mam.message()) //构建MessageAndMetadata  
       //使用高级API从指定的offset开始消费，欲了解详情，  
       //请进入"http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.streaming.kafka.KafkaUtils$"查看  
        val messages: InputDStream[(String, String)] = KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder, (String, String)](ssc, kafkaParams, fromOffsets, messageHandler)  
      
        //数据操作  
        messages.foreachRDD(mess => {  
          //获取offset集合  
          val offsetsList = mess.asInstanceOf[HasOffsetRanges].offsetRanges  
          mess.foreachPartition(lines => {  
            lines.foreach(line => {  
              val o: OffsetRange = offsetsList(TaskContext.get.partitionId)  
              logger.info("++++++++++++++++++++++++++++++此处记录offset+++++++++++++++++++++++++++++++++++++++")  
              logger.info(s"${o.topic}  ${o.partition}  ${o.fromOffset}  ${o.untilOffset}")  
              logger.info("+++++++++++++++++++++++++++++++此处消费数据操作++++++++++++++++++++++++++++++++++++++")  
              logger.info("The kafka  line is " + line)  
            })  
          })  
        })  
        ssc  
      }  
      
      //构建Map  
      def setFromOffsets(list: List[(String, Int, Long)]): Map[TopicAndPartition, Long] = {  
        var fromOffsets: Map[TopicAndPartition, Long] = Map()  
        for (offset <- list) {  
          val tp = TopicAndPartition(offset._1, offset._2)//topic和分区数  
          fromOffsets += (tp -> offset._3)           // offset位置  
        }  
        fromOffsets  
      }  
    }

### 四. 参考文档： ###

1、spark API  http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.streaming.kafka.KafkaUtils$
    
    2、Kafka官方配置说明：http://kafka.apache.org/documentation.html#configuration
    
    3、Kafka SampleConsumer：https://cwiki.apache.org/confluence/display/KAFKA/0.8.0+SimpleConsumer+Example
    
    4、Spark streaming 消费遍历offset说明：http://spark.apache.org/docs/1.6.0/streaming-kafka-integration.html
    
    5、Kafka官方API说明：http://kafka.apache.org/090/javadoc/index.html?org/apache/kafka/clients/consumer/KafkaConsumer.html

--------------------

##### 转自：[https://blog.csdn.net/high2011/article/details/53706446][https_blog.csdn.net_high2011_article_details_53706446] #####

[https_blog.csdn.net_high2011_article_details_53706446]: https://blog.csdn.net/high2011/article/details/53706446