Question

我尝试使用带有scala的spark使用sbt来传输Twitter数据，一切顺利，但我遇到了问题：

这是我的buld.sbt：

import Assembly._
import AssemblyPlugin._

name := "TwitterSparkStreaming"
version := "0.1"
scalaVersion := "2.12.3"

libraryDependencies ++= Seq(
  "org.apache.spark" % "spark-core_2.11" % "1.5.2",
  "org.apache.spark" % "spark-sql_2.11" % "1.5.2",
  "org.apache.spark" % "spark-streaming_2.11" % "1.5.2",
  "org.apache.spark" % "spark-streaming-twitter_2.11" % "1.6.3",
  "joda-time" %% "joda-time" % "2.9.1",
  "org.twitter4j" % "twitter4j-core" % "3.0.3",
  "org.twitter4j" % "twitter4j-stream" % "3.0.3",
  "edu.stanford.nlp" % "stanford-corenlp" % "3.5.2",
  "edu.stanford.nlp" % "stanford-corenlp" % "3.5.2" classifier "models"
)

resolvers += "Akka Repository" at "http://repo.akka.io./releases/"

assemblyMergeStrategy in assembly := {
  case PathList("META-INF", xs @ _*) => MergeStrategy.discard
  case x => MergeStrategy.first
}

这是包含org.apache.spark.Logging的类：

import org.apache.log4j.{Logger, Level}
import org.apache.spark.Logging

object LogUtils extends Logging{
  def setStreamingLogLevels(): Unit ={
    val log4jInitialized = Logger.getRootLogger.getAllAppenders.hasMoreElements
    if(!log4jInitialized)
    {
      logInfo("Setting log level to [WARN] for streaming example." + " To override add a custom log4j.properties to the classpath.")
      Logger.getRootLogger.setLevel(Level.WARN)
    }
  }
}

这是我出现的错误：

Exception in thread "main" java.lang.NoSuchMethodError: org.apache.spark.Logging.$init$(Lorg/apache/spark/Logging;)V
    at LogUtils$.<init>(LogUtils.scala:4)
    at LogUtils$.<clinit>(LogUtils.scala)
    at TwitterStreaming$.main(TwitterStreaming.scala:30)
    at TwitterStreaming.main(TwitterStreaming.scala)

我可以知道如何解决它？

注意：我尝试将org.apache.spark依赖项从2.2.0更改为1.5.2，但问题是相同的

Answer 1

我不确定为什么这段代码会出错。但是有一种更好的方法可以在Spark中设置日志级别。

请参阅链接https://spark.apache.org/docs/latest/api/java/org/apache/spark/SparkContext.html#setLogLevel-java.lang.String-

Spark在sparkContext级别有方法，所以你可以调用，

sparkContext.setLogLevel（ “WARN”）

在线程＆＃34; main＆＃34;中流式Spark异常

1 个答案: