利用redis 来维护消费者偏移量 

  1 package com.it.baizhan.scalacode.Streaming
  2 
  3 import java.util
  4 
  5 import org.apache.kafka.clients.consumer.ConsumerRecord
  6 import org.apache.kafka.common.TopicPartition
  7 import org.apache.kafka.common.serialization.StringDeserializer
  8 import org.apache.spark.rdd.RDD
  9 import org.apache.spark.streaming.dstream.InputDStream
 10 import org.apache.spark.streaming.kafka010.LocationStrategies.PreferConsistent
 11 import org.apache.spark.streaming.kafka010.{ConsumerStrategies, HasOffsetRanges, KafkaUtils, OffsetRange}
 12 import org.apache.spark.streaming.{Durations, StreamingContext}
 13 import org.apache.spark.{SparkConf, TaskContext}
 14 
 15 import scala.collection.mutable
 16 
 17 /**
 18   * 利用redis 来维护消费者偏移量
 19   */
 20 object ManageOffsetUseRedis {
 21   def main(args: Array[String]): Unit = {
 22     val conf = new SparkConf()
 23     conf.setMaster("local")
 24     conf.setAppName("manageoffsetuseredis")
 25     //设置每个分区每秒读取多少条数据
 26     conf.set("spark.streaming.kafka.maxRatePerPartition","10")
 27     val ssc = new StreamingContext(conf,Durations.seconds(5))
 28     //设置日志级别
 29     ssc.sparkContext.setLogLevel("Error")
 30 
 31     val topic = "mytopic"
 32     /**
 33       * 从Redis 中获取消费者offset
 34       */
 35     val dbIndex = 3
 36 
 37     //从Redis中获取存储的消费者offset
 38     val currentTopicOffset: mutable.Map[String, String] = getOffSetFromRedis(dbIndex,topic)
 39 
 40     //初始读取到的topic offset:
 41     currentTopicOffset.foreach(tp=>{println(s" 初始读取到的offset: $tp")})
 42 
 43     //转换成需要的类型
 44     val fromOffsets: Predef.Map[TopicPartition, Long] = currentTopicOffset.map { resultSet =>
 45       new TopicPartition(topic, resultSet._1.toInt) -> resultSet._2.toLong
 46     }.toMap
 47 
 48     val kafkaParams = Map[String, Object](
 49       "bootstrap.servers" -> "mynode1:9092,mynode2:9092,mynode3:9092",
 50       "key.deserializer" -> classOf[StringDeserializer],
 51       "value.deserializer" -> classOf[StringDeserializer],
 52       "group.id" -> "MyGroupId11",
 53       "auto.offset.reset" -> "latest",
 54       "enable.auto.commit" -> (false: java.lang.Boolean)//默认是true
 55     )
 56 
 57     /**
 58       * 将获取到的消费者offset 传递给SparkStreaming
 59       */
 60     val stream: InputDStream[ConsumerRecord[String, String]] = KafkaUtils.createDirectStream[String, String](
 61       ssc,
 62       PreferConsistent,
 63       ConsumerStrategies.Assign[String, String](fromOffsets.keys.toList, kafkaParams, fromOffsets)
 64     )
 65     stream.foreachRDD { (rdd:RDD[ConsumerRecord[String, String]]) =>
 66 
 67       println("**** 业务处理完成  ****")
 68 
 69       val offsetRanges: Array[OffsetRange] = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
 70 
 71       rdd.foreachPartition { iter =>
 72         val o: OffsetRange = offsetRanges(TaskContext.get.partitionId)
 73         println(s"topic:${o.topic}  partition:${o.partition}  fromOffset:${o.fromOffset}  untilOffset: ${o.untilOffset}")
 74       }
 75 
 76       //将当前批次最后的所有分区offsets 保存到 Redis中
 77       saveOffsetToRedis(dbIndex,offsetRanges)
 78     }
 79 
 80     ssc.start()
 81     ssc.awaitTermination()
 82     ssc.stop()
 83 
 84 
 85   }
 86 
 87   /**
 88     * 将消费者offset 保存到 Redis中
 89     *
 90     */
 91   def saveOffsetToRedis(db:Int,offsetRanges:Array[OffsetRange]) = {
 92     val jedis = RedisClient.pool.getResource
 93     jedis.select(db)
 94     offsetRanges.foreach(offsetRange=>{
 95       jedis.hset(offsetRange.topic, offsetRange.partition.toString,offsetRange.untilOffset.toString)
 96     })
 97     println("保存成功")
 98     RedisClient.pool.returnResource(jedis)
 99   }
100 
101 
102   /**
103     * 从Redis中获取保存的消费者offset
104     * @param db
105     * @param topic
106     * @return
107     */
108   def getOffSetFromRedis(db:Int,topic:String)  ={
109     val jedis = RedisClient.pool.getResource
110     jedis.select(db)
111     val result: util.Map[String, String] = jedis.hgetAll(topic)
112     RedisClient.pool.returnResource(jedis)
113     if(result.size()==0){
114       result.put("0","0")
115       result.put("1","0")
116       result.put("2","0")
117     }
118     import scala.collection.JavaConversions.mapAsScalaMap
119     val offsetMap: scala.collection.mutable.Map[String, String] = result
120     offsetMap
121   }
122 }

 

posted @ 2021-04-20 14:13  大数据程序员  阅读(350)  评论(0)    收藏  举报