spark streaming消费指定的topic和partition并手动更新offset

import kafka.common.TopicAndPartition
import kafka.message.MessageAndMetadata
import kafka.serializer.Decoder
import org.apache.spark.SparkException
import org.apache.spark.rdd.RDD
import org.apache.spark.streaming.StreamingContext
import org.apache.spark.streaming.dstream.InputDStream
import org.apache.spark.streaming.kafka.KafkaCluster.LeaderOffset
import org.apache.spark.streaming.kafka.{HasOffsetRanges, KafkaCluster, KafkaUtils}

import scala.collection.mutable.ArrayBuffer
import scala.reflect.ClassTag

/**
  * Create by shengjk1
  */

class KafkaManager(val kafkaParams: Map[String, String]) extends Serializable {

    private val kc = new KafkaCluster(kafkaParams)

    /**
      * 创建数据流
      */
    def createDirectStream[K: ClassTag, V: ClassTag, KD <: Decoder[K] : ClassTag, VD <: Decoder[V] : ClassTag](
                            ssc: StreamingContext, kafkaParams: Map[String, String], topics: Set[String]): InputDStream[(K, V)] = {
        val groupId = kafkaParams.get("group.id").get
        // 在zookeeper上读取offsets前先根据实际情况更新offsets
        setOrUpdateOffsets(topics, groupId)

        //从zookeeper上读取offset开始消费message
        val messages = {
            val partitionsE = kc.getPartitions(topics)
            if (partitionsE.isLeft)
                throw new SparkException(s"get kafka partition failed: ${partitionsE.left.get}")
            val partitions = partitionsE.right.get

            println("partitions ",partitions);

            val consumerOffsetsE = kc.getConsumerOffsets(groupId, partitions)
            if (consumerOffsetsE.isLeft)
                throw new SparkException(s"get kafka consumer offsets failed: ${consumerOffsetsE.left.get}")
            val consumerOffsets = consumerOffsetsE.right.get
            KafkaUtils.createDirectStream[K, V, KD, VD, (K, V)](
                ssc, kafkaParams, consumerOffsets, (mmd: MessageAndMetadata[K, V]) => (mmd.key, mmd.message))
        }
        messages
    }


    /**
      *
      * @param ssc
      * @param kafkaParams
      * @param topicPartition  Set([test01,0], [test01,1], [test01,2]))
      * @tparam K
      * @tparam V
      * @tparam KD
      * @tparam VD
      * @return
      */
    //update by shengjk1
    def createDirectStreamByAssignPartition[K: ClassTag, V: ClassTag, KD <: Decoder[K] : ClassTag, VD <: Decoder[V] : ClassTag](
                                ssc: StreamingContext, kafkaParams: Map[String, String],topicPartition: Set[TopicAndPartition]): InputDStream[(K, V)] = {
        val groupId = kafkaParams.get("group.id").get
        // 在zookeeper上读取offsets前先根据实际情况更新offsets
        val topics=ArrayBuffer[String]()
        val tpArray=topicPartition.toArray
        for(i<- 0 until tpArray.length){
            topics+=tpArray(i).topic
        }


        setOrUpdateOffsets(topics.toSet, groupId)
        //从zookeeper上读取offset开始消费message
        val messages = {
            val consumerOffsetsE = kc.getConsumerOffsets(groupId, topicPartition)
            if (consumerOffsetsE.isLeft)
                throw new SparkException(s"get kafka consumer offsets failed: ${consumerOffsetsE.left.get}")
            val consumerOffsets = consumerOffsetsE.right.get
            KafkaUtils.createDirectStream[K, V, KD, VD, (K, V)](
                ssc, kafkaParams, consumerOffsets, (mmd: MessageAndMetadata[K, V]) => (mmd.key, mmd.message))
        }
        messages
    }



    /**
      * 创建数据流前，根据实际消费情况更新消费offsets
      *
      * @param topics
      * @param groupId
      */
    private def setOrUpdateOffsets(topics: Set[String], groupId: String): Unit = {
        topics.foreach(topic => {
            var hasConsumed = true
            val partitionsE = kc.getPartitions(Set(topic))
            if (partitionsE.isLeft)
                throw new SparkException(s"get kafka partition failed: ${partitionsE.left.get}")
            val partitions = partitionsE.right.get
            val consumerOffsetsE = kc.getConsumerOffsets(groupId, partitions)
            if (consumerOffsetsE.isLeft) hasConsumed = false
            if (hasConsumed) {
                // 消费过
                /**
                  * 如果streaming程序执行的时候出现kafka.common.OffsetOutOfRangeException，
                  * 说明zk上保存的offsets已经过时了，即kafka的定时清理策略已经将包含该offsets的文件删除。
                  * 针对这种情况，只要判断一下zk上的consumerOffsets和earliestLeaderOffsets的大小，
                  * 如果consumerOffsets比earliestLeaderOffsets还小的话，说明consumerOffsets已过时,
                  * 这时把consumerOffsets更新为earliestLeaderOffsets
                  */
                val earliestLeaderOffsetsE = kc.getEarliestLeaderOffsets(partitions)
                if (earliestLeaderOffsetsE.isLeft)
                    throw new SparkException(s"get earliest leader offsets failed: ${earliestLeaderOffsetsE.left.get}")
                val earliestLeaderOffsets = earliestLeaderOffsetsE.right.get
                val consumerOffsets = consumerOffsetsE.right.get

                // 可能只是存在部分分区consumerOffsets过时，所以只更新过时分区的consumerOffsets为earliestLeaderOffsets
                var offsets: Map[TopicAndPartition, Long] = Map()
                consumerOffsets.foreach({ case (tp, n) =>
                    val earliestLeaderOffset = earliestLeaderOffsets(tp).offset
                    if (n < earliestLeaderOffset) {
                        println("consumer group:" + groupId + ",topic:" + tp.topic + ",partition:" + tp.partition +
                                " offsets已经过时，更新为" + earliestLeaderOffset)
                        offsets += (tp -> earliestLeaderOffset)
                    }
                })
                if (!offsets.isEmpty) {
                    kc.setConsumerOffsets(groupId, offsets)
                }
            } else {
                // 没有消费过
                val reset = kafkaParams.get("auto.offset.reset").map(_.toLowerCase)
                var leaderOffsets: Map[TopicAndPartition, LeaderOffset] = null
                if (reset == Some("smallest")) {
                    val leaderOffsetsE = kc.getEarliestLeaderOffsets(partitions)
                    if (leaderOffsetsE.isLeft)
                        throw new SparkException(s"get earliest leader offsets failed: ${leaderOffsetsE.left.get}")
                    leaderOffsets = leaderOffsetsE.right.get
                } else {
                    val leaderOffsetsE = kc.getLatestLeaderOffsets(partitions)
                    if (leaderOffsetsE.isLeft)
                        throw new SparkException(s"get latest leader offsets failed: ${leaderOffsetsE.left.get}")
                    leaderOffsets = leaderOffsetsE.right.get
                }
                val offsets = leaderOffsets.map {
                    case (tp, offset) => (tp, offset.offset)
                }
                kc.setConsumerOffsets(groupId, offsets)
            }
        })
    }

    /**
      * 更新zookeeper上的消费offsets
      *
      * @param rdd
      */
    def updateZKOffsets(rdd: RDD[(String, String)]): Unit = {
        val groupId = kafkaParams.get("group.id").get
        val offsetsList = rdd.asInstanceOf[HasOffsetRanges].offsetRanges

        for (offsets <- offsetsList) {
            val topicAndPartition = TopicAndPartition(offsets.topic, offsets.partition)
            val o = kc.setConsumerOffsets(groupId, Map((topicAndPartition, offsets.untilOffset)))
            if (o.isLeft) {
                println(s"Error updating the offset to Kafka cluster: ${o.left.get}")
            }
        }
    }
}