SparkStreaming-Kafka通过指定偏移量获取数据如何实现

import java.util.Properties
import com.google.gson.{Gson, GsonBuilder}
import org.apache.kafka.clients.producer.{KafkaProducer, ProducerRecord}
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}
/**
  * Date 2022/11/8 9:49
  */
object KafkaEventProducer {
  def main(args: Array[String]): Unit = {
    val conf: SparkConf = new SparkConf().setAppName("KafkaEventProducer").setMaster("local[*]")
    val sc = new SparkContext(conf)
    sc.setLogLevel("ERROR")
    val topic = "ly_test"
    val props = new Properties()
    props.put("bootstrap.servers","node01:9092,node02:9092,node03:9092")
    props.put("key.serializer","org.apache.kafka.common.serialization.StringSerializer")
    props.put("value.serializer","org.apache.kafka.common.serialization.StringSerializer")
    props.put("acks","all")
//    props.put("security.protocol","SASL_PLAINTEXT")
//    props.put("sasl.mechanism","PLAIN")
//    props.put("sasl.jaas.config","org.apache.kafka.common.security.plain.PlainLoginModule required username='sjf' password='123sjf';")
    val kafkaProducer = new KafkaProducer[String,String](props)
    val srcRDD: RDD[String] = sc.textFile("file:///F:\\work\\sun\\lywork\\hbaseoper\\datas\\kafkaproducerdata.txt")
    val records: Array[Array[String]] = srcRDD.filter(!_.startsWith(";")).map(_.split(",")).collect()
    //对数据进行预处理形成json形式
    for(record<-records){
      val trafficInfo = new TrafficInfo(record(0),record(2),record(4),record(6),record(13))
      // 不能用new Gson()   会出现 \u0027
      // val trafficInfoJson: String = new Gson().toJson(trafficInfo)
      //使用Gson gson = new Gson()，进行对象转化json格式时，单引号会被转换成u0027代码。使用以下方法进行替换
      val gson: Gson = new GsonBuilder().disableHtmlEscaping().create()
      val trafficInfoJson: String = gson.toJson(trafficInfo)
      kafkaProducer.send(new ProducerRecord[String,String](topic,trafficInfoJson))
      println("Message Sent:"+trafficInfoJson)
      Thread.sleep(2000)
    }
    sc.stop()
    kafkaProducer.flush()
    kafkaProducer.close()
  }
  //相机编号
  //车牌号
  //时间
  //速度
  //车道编号
  case class TrafficInfo(camer_id:String,car_id:String,event_time:String,car_speed:String,car_code:String)
}

import java.text.SimpleDateFormat
import java.util
import java.util.Date
import org.apache.kafka.clients.consumer.ConsumerRecord
import org.apache.kafka.common.record.TimestampType
import org.apache.kafka.common.serialization.StringDeserializer
import org.apache.spark.rdd.RDD
import org.apache.spark.streaming.dstream.{DStream, InputDStream}
import org.apache.spark.streaming.kafka010.{ConsumerStrategies, KafkaUtils, LocationStrategies, OffsetRange}
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.{SparkConf, SparkContext}
/**
  * Date 2022/11/5 16:38
  */
/**
  * 通过偏移量获取数据
  */
object AttainDataFromOffset {
  def main(args: Array[String]): Unit = {
    val conf: SparkConf = new SparkConf().setAppName("AttainDataFromOffset").setMaster("local[*]")
    val sc = new SparkContext(conf)
    sc.setLogLevel("ERROR")
    val ssc = new StreamingContext(sc,Seconds(5))
    val kafkaParams: Map[String, Object] = Map[String, Object](
      "bootstrap.servers" -> "node01:9092,node02:9092,node03:9092",
      "key.deserializer" -> classOf[StringDeserializer],
      "value.deserializer" -> classOf[StringDeserializer],
      "group.id" -> "ly",
      "auto.offset.reset" -> "earliest",
      "enable.auto.commit" -> (false: java.lang.Boolean)
      // kafka 带有账号密码sasl协议的认证
//      "security.protocol" -> "SASL_PLAINTEXT",
//      "sasl.mechanism" -> "PLAIN",
//      "sasl.jaas.config" -> "org.apache.kafka.common.security.plain.PlainLoginModule required username='sjf' password='123sjf';"
    )
    val topics = Array("ly_test")
    val stream: InputDStream[ConsumerRecord[String, String]] = KafkaUtils.createDirectStream[String, String](
      ssc,
      LocationStrategies.PreferConsistent,
      ConsumerStrategies.Subscribe[String,String](topics, kafkaParams)
    )
    val res: DStream[(String, String, Int, Long)] = stream.map(recoed => {
      val key: String = recoed.key()
      val value: String = recoed.value()
      val partionId: Int = recoed.partition()
      val offset: Long = recoed.offset()
      (key, value, partionId, offset)
      //println(key+"\t"+value+"\t"+partionId+"\t"+offset)
    })
    // 指定偏移量
    val offsetRanges = Array(
      // topic, partition, inclusive starting offset, exclusive ending offset
      OffsetRange("lawyee_test", 0, 1L, 10L)
    )
    // 获取指定偏移量的数据
    import scala.collection.JavaConverters._
    val jkafkaParams: util.Map[String, Object] = kafkaParams.asJava
    val offsetRDD: RDD[ConsumerRecord[String, String]] = KafkaUtils.createRDD[String,String](
      sc,
      jkafkaParams,
      offsetRanges,
      LocationStrategies.PreferConsistent
    )
    val resRDD: RDD[(String, String, Int, Long,String,TimestampType)] = offsetRDD.map(recoed => {
      val key: String = recoed.key()
      val value: String = recoed.value()
      val partionId: Int = recoed.partition()
      val offset: Long = recoed.offset()
      var time: Long = recoed.timestamp()
      val timeStr = timeStampToDate(time)
      val timestampType: TimestampType = recoed.timestampType()
      (key, value, partionId, offset,timeStr,timestampType)
      //println(key+"\t"+value+"\t"+partionId+"\t"+offset)
    })
    resRDD.foreach(println(_))
    res.print()
    ssc.start()
    ssc.awaitTermination()
  }
  // 时间格式时间 转换为字符串时间
  def dateToString(date:Date): String ={
    val simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss")
    val strDate: String = simpleDateFormat.format(date)
    strDate
  }
  // 字符串时间转换为时间格式时间
  def strToDate(str:String):Date = {
    val simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss")
    val date: Date = simpleDateFormat.parse(str)
    date
  }
  // 时间戳转化为字符串时间
  def timeStampToDate(timeStamp:Long): String ={
    val date = new Date(timeStamp)
    val strDate: String = dateToString(date)
    strDate
  }
  //字符串时间转化为时间戳
  def dateToTimeStamp(strDate:String): Long ={
    val date: Date = strToDate(strDate)
    val timeStamp: Long = date.getTime
    timeStamp
  }
}