关于kafka定期清理日志后再消费报错kafka.common.OffsetOutOfRangeException的解决

 环境：

kafka  0.10

spark  2.1.0

zookeeper  3.4.5-cdh5.14.0

公司阿里云测试机，十月一放假前，没有在继续消费，假期过后回来再使用spark streaming消费某个消费组下的kafka时报错如下：

As I regularly kill the servers running Kafka and the producers feeding it (yes, just for fun), things sometimes go a bit crazy, not entirely sure why but I got the error:

kafka.common.OffsetOutOfRangeError: FetchResponse(topic='my_messages', partition=0, error=1, highwaterMark=-1, messages=)
To fix it I added the “seek” setting:

consumer.seek(0,2)

出现问题的原因：

kafka会定时清理日志

当我们的任务开始的时候，如果之前消费过某个topic，那么这个topic会在zk上设置offset,我们一般会去获取这个offset来继续从上次结束的地方继续消费，但是kafka定时清理日志的功能，比如定时一天一清理，那么如果你的offset是前天消费的offset，那么这个时候你再去消费，自然而然的你的offset肯定已经不在有效范围内，所以就报OffsetOutOfRangeException了

解决：

需要在发现zk_offset<earliest_offset>时矫正zk_offset为合法值

前期完整代码

https://www.cnblogs.com/niutao/p/10547831.html

改正后的关键代码：

/**
  * 获取最小offset
  * Returns the earliest (lowest) available offsets, taking new partitions into account.
  *
  * @param kafkaParams kafka客户端配置
  * @param topics      获取获取offset的topic
  */
def getEarliestOffsets(kafkaParams: Map[String, Object], topics: Iterable[String]): Map[TopicPartition, Long] = {
  val newKafkaParams = mutable.Map[String, Object]()
  newKafkaParams ++= kafkaParams
  newKafkaParams.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")
  val consumer: KafkaConsumer[String, Array[Byte]] = new KafkaConsumer[String, Array[Byte]](newKafkaParams)
  consumer.subscribe(topics)
  val notOffsetTopicPartition = mutable.Set[TopicPartition]()
  try {
    consumer.poll(0)
  } catch {
    case ex: NoOffsetForPartitionException =>
      log.warn(s"consumer topic partition offset not found:${ex.partition()}")
      notOffsetTopicPartition.add(ex.partition())
  }
  val parts = consumer.assignment().toSet
  consumer.pause(parts)
  consumer.seekToBeginning(parts)
  consumer.pause(parts)
  val offsets = parts.map(tp => tp -> consumer.position(tp)).toMap
  consumer.unsubscribe()
  consumer.close()
  offsets
}

/**
    * 获取最大offset
    * Returns the latest (highest) available offsets, taking new partitions into account.
    *
    * @param kafkaParams kafka客户端配置
    * @param topics      需要获取offset的topic
    **/
  def getLatestOffsets(kafkaParams: Map[String, Object], topics: Iterable[String]): Map[TopicPartition, Long] = {
    val newKafkaParams = mutable.Map[String, Object]()
    newKafkaParams ++= kafkaParams
    newKafkaParams.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest")
    val consumer: KafkaConsumer[String, Array[Byte]] = new KafkaConsumer[String, Array[Byte]](newKafkaParams)
    consumer.subscribe(topics)
    val notOffsetTopicPartition = mutable.Set[TopicPartition]()
    try {
      consumer.poll(0)
    } catch {
      case ex: NoOffsetForPartitionException =>
        log.warn(s"consumer topic partition offset not found:${ex.partition()}")
        notOffsetTopicPartition.add(ex.partition())
    }
    val parts = consumer.assignment().toSet
    consumer.pause(parts)
    consumer.seekToEnd(parts)
    val offsets = parts.map(tp => tp -> consumer.position(tp)).toMap
    consumer.unsubscribe()
    consumer.close()
    offsets
  }

val earliestOffsets = getEarliestOffsets(kafkaParams , topics)
    val latestOffsets = getLatestOffsets(kafkaParams , topics)
    for((k,v) <- topicPartOffsetMap.toMap){
      val current = v
      val earliest = earliestOffsets.get(k).get
      val latest = latestOffsets.get(k).get
      if (current > latest || current < earliest) {
        log.warn("矫正offset: " + current +" -> "+ earliest);
        topicPartOffsetMap.put(k , earliest)
      }
    }

完整代码，拿去直接用就可以了

import kafka.utils.{ZKGroupTopicDirs, ZkUtils}
import org.apache.kafka.clients.consumer.{ConsumerRecord, KafkaConsumer}
import org.apache.spark.rdd.RDD
import org.apache.spark.streaming.StreamingContext
import org.apache.spark.streaming.dstream.InputDStream
import org.apache.spark.streaming.kafka010.LocationStrategies.PreferConsistent
import org.apache.spark.streaming.kafka010.{ConsumerStrategies, HasOffsetRanges, KafkaUtils}
import org.slf4j.LoggerFactory

import scala.collection.JavaConversions._
import scala.reflect.ClassTag
import scala.util.Try
import org.apache.kafka.clients.consumer.{Consumer, ConsumerConfig, KafkaConsumer, NoOffsetForPartitionException}
import org.apache.kafka.common.TopicPartition
import org.apache.zookeeper.data.Stat

import scala.collection.JavaConversions._
import scala.collection.mutable
/**
  * Kafka的连接和Offset管理工具类
  *
  * @param zkHosts     Zookeeper地址
  * @param kafkaParams Kafka启动参数
  */
class KafkaManager(zkHosts: String, kafkaParams: Map[String, Object]) extends Serializable {
  //Logback日志对象，使用slf4j框架
  @transient private lazy val log = LoggerFactory.getLogger(getClass)
  //建立ZkUtils对象所需的参数
  val (zkClient, zkConnection) = ZkUtils.createZkClientAndConnection(zkHosts, 10000, 10000)
  //  zkClient.setZkSerializer(new MyZkSerializer())
  //ZkUtils对象，用于访问Zookeeper
  val zkUtils = new ZkUtils(zkClient, zkConnection, false)


  /**
    * 获取最小offset
    * Returns the earliest (lowest) available offsets, taking new partitions into account.
    *
    * @param kafkaParams kafka客户端配置
    * @param topics      获取获取offset的topic
    */
  def getEarliestOffsets(kafkaParams: Map[String, Object], topics: Iterable[String]): Map[TopicPartition, Long] = {
    val newKafkaParams = mutable.Map[String, Object]()
    newKafkaParams ++= kafkaParams
    newKafkaParams.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")
    val consumer: KafkaConsumer[String, Array[Byte]] = new KafkaConsumer[String, Array[Byte]](newKafkaParams)
    consumer.subscribe(topics)
    val notOffsetTopicPartition = mutable.Set[TopicPartition]()
    try {
      consumer.poll(0)
    } catch {
      case ex: NoOffsetForPartitionException =>
        log.warn(s"consumer topic partition offset not found:${ex.partition()}")
        notOffsetTopicPartition.add(ex.partition())
    }
    val parts = consumer.assignment().toSet
    consumer.pause(parts)
    consumer.seekToBeginning(parts)
    consumer.pause(parts)
    val offsets = parts.map(tp => tp -> consumer.position(tp)).toMap
    consumer.unsubscribe()
    consumer.close()
    offsets
  }

  /**
    * 获取最大offset
    * Returns the latest (highest) available offsets, taking new partitions into account.
    *
    * @param kafkaParams kafka客户端配置
    * @param topics      需要获取offset的topic
    **/
  def getLatestOffsets(kafkaParams: Map[String, Object], topics: Iterable[String]): Map[TopicPartition, Long] = {
    val newKafkaParams = mutable.Map[String, Object]()
    newKafkaParams ++= kafkaParams
    newKafkaParams.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest")
    val consumer: KafkaConsumer[String, Array[Byte]] = new KafkaConsumer[String, Array[Byte]](newKafkaParams)
    consumer.subscribe(topics)
    val notOffsetTopicPartition = mutable.Set[TopicPartition]()
    try {
      consumer.poll(0)
    } catch {
      case ex: NoOffsetForPartitionException =>
        log.warn(s"consumer topic partition offset not found:${ex.partition()}")
        notOffsetTopicPartition.add(ex.partition())
    }
    val parts = consumer.assignment().toSet
    consumer.pause(parts)
    consumer.seekToEnd(parts)
    val offsets = parts.map(tp => tp -> consumer.position(tp)).toMap
    consumer.unsubscribe()
    consumer.close()
    offsets
  }

  /**
    * 获取消费者当前offset
    *
    * @param consumer   消费者
    * @param partitions topic分区
    * @return
    */
  def getCurrentOffsets(consumer: Consumer[_, _], partitions: Set[TopicPartition]): Map[TopicPartition, Long] = {
    partitions.map(tp => tp -> consumer.position(tp)).toMap
  }
  /**
    * 从Zookeeper读取Kafka消息队列的Offset
    *
    * @param topics  Kafka话题
    * @param groupId Kafka Group ID
    * @return 返回一个Map[TopicPartition, Long]，记录每个话题每个Partition上的offset，如果还没消费，则offset为0
    */
  def readOffsets(topics: Seq[String], groupId: String): Map[TopicPartition, Long] = {
    val topicPartOffsetMap = collection.mutable.HashMap.empty[TopicPartition, Long]
    val partitionMap = zkUtils.getPartitionsForTopics(topics)
    // /consumers/<groupId>/offsets/<topic>/
    partitionMap.foreach(topicPartitions => {
      val zkGroupTopicDirs = new ZKGroupTopicDirs(groupId, topicPartitions._1)
      topicPartitions._2.foreach(partition => {
        val offsetPath = zkGroupTopicDirs.consumerOffsetDir + "/" + partition
        val tryGetKafkaOffset = Try {
          val offsetStatTuple = zkUtils.readData(offsetPath)
          if (offsetStatTuple != null) {
            log.info("查询Kafka消息偏移量详情: 话题:{}, 分区:{}, 偏移量:{}, ZK节点路径:{}", Seq[AnyRef](topicPartitions._1, partition.toString, offsetStatTuple._1, offsetPath): _*)
            topicPartOffsetMap.put(new TopicPartition(topicPartitions._1, Integer.valueOf(partition)), offsetStatTuple._1.toLong)
          }
        }
        if(tryGetKafkaOffset.isFailure){
          //http://kafka.apache.org/0110/javadoc/index.html?org/apache/kafka/clients/consumer/KafkaConsumer.html
          val consumer = new KafkaConsumer[String, Object](kafkaParams)
          val partitionList = List(new TopicPartition(topicPartitions._1, partition))
          consumer.assign(partitionList)
          val minAvailableOffset = consumer.beginningOffsets(partitionList).values.head
          consumer.close()
          log.warn("查询Kafka消息偏移量详情: 没有上一次的ZK节点:{}, 话题:{}, 分区:{}, ZK节点路径:{}, 使用最小可用偏移量:{}", Seq[AnyRef](tryGetKafkaOffset.failed.get.getMessage, topicPartitions._1, partition.toString, offsetPath, minAvailableOffset): _*)
          topicPartOffsetMap.put(new TopicPartition(topicPartitions._1, Integer.valueOf(partition)), minAvailableOffset)
        }
      })
    })
    //TODO  解决kafka中数据还没来得及消费,数据就已经丢失或者过期了#########################
    //Offsets out of range with no configured reset policy for partition
    //获取EarliestOffsets
    val earliestOffsets = getEarliestOffsets(kafkaParams , topics)
    val latestOffsets = getLatestOffsets(kafkaParams , topics)
    for((k,v) <- topicPartOffsetMap.toMap){
      val current = v
      val earliest = earliestOffsets.get(k).get
      val latest = latestOffsets.get(k).get
      if (current > latest || current < earliest) {
        log.warn("矫正offset: " + current +" -> "+ earliest);
        topicPartOffsetMap.put(k , earliest)
      }
    }

    topicPartOffsetMap.toMap
  }

  //#########################################################
  /**
    * 包装createDirectStream方法，支持Kafka Offset，用于创建Kafka Streaming流
    *
    * @param ssc    Spark Streaming Context
    * @param topics Kafka话题
    * @tparam K Kafka消息Key类型
    * @tparam V Kafka消息Value类型
    * @return Kafka Streaming流
    */
  def createDirectStream[K: ClassTag, V: ClassTag](ssc: StreamingContext, topics: Seq[String]): InputDStream[ConsumerRecord[K, V]] = {
    val groupId = kafkaParams("group.id").toString
    //TODO
        val storedOffsets: Map[TopicPartition, Long] = readOffsets(topics, groupId)
//    val storedOffsets: Map[TopicPartition, Long] = getCurrentOffset(kafkaParams , topics)
    log.info("Kafka消息偏移量汇总(格式:(话题,分区号,偏移量)):{}", storedOffsets.map(off => (off._1.topic, off._1.partition(), off._2)))
    val kafkaStream = KafkaUtils.createDirectStream[K, V](ssc, PreferConsistent, ConsumerStrategies.Subscribe[K, V](topics, kafkaParams, storedOffsets))
    kafkaStream
  }

  /**
    * 保存Kafka消息队列消费的Offset
    *
    * @param rdd            SparkStreaming的Kafka RDD，RDD[ConsumerRecord[K, V]
    * @param storeEndOffset true=保存结束offset， false=保存起始offset
    */
  def persistOffsets[K, V](rdd: RDD[ConsumerRecord[K, V]], storeEndOffset: Boolean = true): Unit = {
    val groupId = kafkaParams("group.id").toString
    val offsetsList = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
    offsetsList.foreach(or => {
      val zkGroupTopicDirs = new ZKGroupTopicDirs(groupId, or.topic)
      val offsetPath = zkGroupTopicDirs.consumerOffsetDir + "/" + or.partition
      val offsetVal = if (storeEndOffset) or.untilOffset else or.fromOffset
      zkUtils.updatePersistentPath(zkGroupTopicDirs.consumerOffsetDir + "/" + or.partition, offsetVal + "" /*, JavaConversions.bufferAsJavaList(acls)*/)
      log.debug("保存Kafka消息偏移量详情: 话题:{}, 分区:{}, 偏移量:{}, ZK节点路径:{}", Seq[AnyRef](or.topic, or.partition.toString, offsetVal.toString, offsetPath): _*)
    })
  }


}