【发布时间】：2017-02-09 01:26:27
【问题描述】：
我正在尝试使用 sbt 包构建 Spark 流应用程序，但我无法发现此错误的原因。
这是一些错误
scala.reflect.internal.MissingRequirementError: 对象 未找到编译器镜像中的 java.lang.Object。在 scala.reflect.internal.MissingRequirementError$.signal(MissingRequirementError.scala:16) 在 scala.reflect.internal.MissingRequirementError$.notFound(MissingRequirementError.scala:17) 在 scala.reflect.internal.Mirrors$RootsBase.getModuleOrClass(Mirrors.scala:48) 在 scala.reflect.internal.Mirrors$RootsBase.getModuleOrClass(Mirrors.scala:40) 在 scala.reflect.internal.Mirrors$RootsBase.getModuleOrClass(Mirrors.scala:40)
这是代码
import org.apache.spark.SparkContext
import org.apache.spark._
import org.apache.spark.streaming._
import org.apache.spark.streaming.twitter._
import twitter4j.Status
object TrendingHashTags {
def main(args: Array[String]): Unit = {
val Array(consumerKey, consumerSecret, accessToken, accessTokenSecret,
lang, batchInterval, minThreshold, showCount ) = args.take(8)
val filters = args.takeRight(args.length - 8)
System.setProperty("twitter4j.oauth.consumerKey", consumerKey)
System.setProperty("twitter4j.oauth.consumerSecret", consumerSecret)
System.setProperty("twitter4j.oauth.accessToken", accessToken)
System.setProperty("twitter4j.oauth.accessTokenSecret", accessTokenSecret)
val conf = new SparkConf().setAppName("TrendingHashTags")
val ssc = new StreamingContext(conf, Seconds(batchInterval.toInt))
val tweets = TwitterUtils.createStream(ssc, None, filters)
val tweetsFilteredByLang = tweets.filter{tweet => tweet.getLang() == lang}
val statuses = tweetsFilteredByLang.map{ tweet => tweet.getText()}
val words = statuses.flatMap{status => status.split("""\s+""")}
val hashTags = words.filter{word => word.startsWith("#")}
val hashTagPairs = hashTags.map{hashtag => (hashtag, 1)}
val tagsWithCounts = hashTagPairs.updateStateByKey(
(counts: Seq[Int], prevCount: Option[Int]) =>
prevCount.map{c => c + counts.sum}.orElse{Some(counts.sum)}
)
val topHashTags = tagsWithCounts.filter{ case(t, c) =>
c > minThreshold.toInt
}
val sortedTopHashTags = topHashTags.transform{ rdd =>
rdd.sortBy({case(w, c) => c}, false)
}
sortedTopHashTags.print(showCount.toInt)
ssc.start()
ssc.awaitTermination()
}
}
【问题讨论】：
标签： scala apache-spark bigdata