Spark自定义维护kafka的offset到zk
import kafka.common.TopicAndPartition import kafka.message.MessageAndMetadata import kafka.serializer.StringDecoder import kafka.utils.ZkUtils import org.I0Itec.zkclient.ZkClient import org.apache.spark.SparkConf import org.apache.spark.rdd.RDD import org.apache.spark.streaming.dstream.InputDStream import org.apache.spark.streaming.kafka.{HasOffsetRanges, KafkaUtils} import org.apache.spark.streaming.{Seconds, StreamingContext} object DirectKafkaExample { def main(args: Array[String]) { val ssc = setupSsc ssc.start() ssc.awaitTermination() } def setupSsc(): StreamingContext ={ val conf = new SparkConf().setAppName("CustomDirectKafkaExample").setMaster("local") val kafkaParams:Map[String,String] = Map("metadata.broker.list" -> "slave1:9092,slave2:9092,slave3:9092") val topicsSet = Set("testha") val ssc = new StreamingContext(conf, Seconds(5)) val messages = createCustomDirectKafkaStream(ssc,kafkaParams,"master0:2181,slave1:2181,slave3:2181","/mysefloffset", topicsSet).map(_._2) messages.foreachRDD{rdd => { rdd.foreachPartition { partitionOfRecords => if(partitionOfRecords.isEmpty) { println("此分区数据为空.") } else { partitionOfRecords.foreach(println(_)) } } } } ssc } def createCustomDirectKafkaStream(ssc: StreamingContext, kafkaParams: Map[String, String], zkHosts: String , zkPath: String, topics: Set[String]): InputDStream[(String, String)] = { val topic = topics.last val zkClient = new ZkClient(zkHosts, 30000, 30000) val storedOffsets = readOffsets(zkClient,zkHosts, zkPath, topic) val kafkaStream = storedOffsets match { case None => //最新的offset KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder](ssc, kafkaParams, topics) case Some(fromOffsets) => // offset从上次继续开始 val messageHandler = (mmd: MessageAndMetadata[String, String]) => (mmd.key, mmd.message) KafkaUtils.createDirectStream[String, String, StringDecoder, StringDecoder,(String, String)](ssc, kafkaParams, fromOffsets, messageHandler) } // save the offsets kafkaStream.foreachRDD(rdd => saveOffsets(zkClient,zkHosts, zkPath, rdd)) kafkaStream } private def readOffsets(zkClient: ZkClient,zkHosts:String, zkPath: String, topic: String):Option[Map[TopicAndPartition, Long]] = { println("开始读取从zk中读取offset") val stopwatch = new Stopwatch() val (offsetsRangesStrOpt, _) = ZkUtils.readDataMaybeNull(zkClient, zkPath) offsetsRangesStrOpt match { case Some(offsetsRangesStr) => println(s"读取到的offset范围: ${offsetsRangesStr}") val offsets = offsetsRangesStr.split(",") .map(s => s.split(":")) .map { case Array(partitionStr, offsetStr) => (TopicAndPartition(topic, partitionStr.toInt) -> offsetStr.toLong) } .toMap println("读取offset结束: " + stopwatch) Some(offsets) case None => println("读取offset结束: " + stopwatch) None } } private def saveOffsets(zkClient: ZkClient,zkHosts:String, zkPath: String, rdd: RDD[_]): Unit = { println("开始保存offset到zk中去") val stopwatch = new Stopwatch() val offsetsRanges = rdd.asInstanceOf[HasOffsetRanges].offsetRanges //分区,offset offsetsRanges.foreach(offsetRange => println(s"Using ${offsetRange}")) val offsetsRangesStr = offsetsRanges.map(offsetRange => s"${offsetRange.partition}:${offsetRange.fromOffset}").mkString(",") println("保存的偏移量范围:"+ offsetsRangesStr) ZkUtils.updatePersistentPath(zkClient, zkPath, offsetsRangesStr) println("保存结束,耗时 :" + stopwatch) } class Stopwatch { private val start = System.currentTimeMillis() override def toString() = (System.currentTimeMillis() - start) + " ms" } }
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