Spark升级到2.0后测试stream-kafka测试报java.lang.NoClassDefFoundError: org/apache/spark/Logging错误

在使用spark读取kafka数据时，当spark升级到2.0之后，出现如上问题：之前遇到了，当时在工程里面添加了org.apache.spark.Logging类，能够运行。

但是在后期使用过程中，又遇到了相同的问题，为了一劳永逸，今天彻底把问题解决。

开发环境：Idea intelligent14 + spark-2.1.0 + kafka

在Idea中安装scala

新建maven-scala工程

在工程中新建org.apche.spark包

新建Logging.scala类

将Logging源码拷贝到类中

package org.apache.spark

import org.apache.log4j.{LogManager, PropertyConfigurator}
import org.slf4j.{Logger, LoggerFactory}
import org.slf4j.impl.StaticLoggerBinder

import org.apache.spark.annotation.DeveloperApi
import org.apache.spark.util.Utils
/**
 * Created by Administrator on 2017/8/11.
 */


/**
 * :: DeveloperApi ::
 * Utility trait for classes that want to log data. Creates a SLF4J logger for the class and allows
 * logging messages at different levels using methods that only evaluate parameters lazily if the
 * log level is enabled.
 *
 * NOTE: DO NOT USE this class outside of Spark. It is intended as an internal utility.
 *       This will likely be changed or removed in future releases.
 */
@DeveloperApi
trait Logging {
  // Make the log field transient so that objects with Logging can
  // be serialized and used on another machine
  @transient private var log_ : Logger = null

  // Method to get the logger name for this object
  protected def logName = {
    // Ignore trailing $'s in the class names for Scala objects
    this.getClass.getName.stripSuffix("$")
  }

  // Method to get or create the logger for this object
  protected def log: Logger = {
    if (log_ == null) {
      initializeIfNecessary()
      log_ = LoggerFactory.getLogger(logName)
    }
    log_
  }

  // Log methods that take only a String
  protected def logInfo(msg: => String) {
    if (log.isInfoEnabled) log.info(msg)
  }

  protected def logDebug(msg: => String) {
    if (log.isDebugEnabled) log.debug(msg)
  }

  protected def logTrace(msg: => String) {
    if (log.isTraceEnabled) log.trace(msg)
  }

  protected def logWarning(msg: => String) {
    if (log.isWarnEnabled) log.warn(msg)
  }

  protected def logError(msg: => String) {
    if (log.isErrorEnabled) log.error(msg)
  }

  // Log methods that take Throwables (Exceptions/Errors) too
  protected def logInfo(msg: => String, throwable: Throwable) {
    if (log.isInfoEnabled) log.info(msg, throwable)
  }

  protected def logDebug(msg: => String, throwable: Throwable) {
    if (log.isDebugEnabled) log.debug(msg, throwable)
  }

  protected def logTrace(msg: => String, throwable: Throwable) {
    if (log.isTraceEnabled) log.trace(msg, throwable)
  }

  protected def logWarning(msg: => String, throwable: Throwable) {
    if (log.isWarnEnabled) log.warn(msg, throwable)
  }

  protected def logError(msg: => String, throwable: Throwable) {
    if (log.isErrorEnabled) log.error(msg, throwable)
  }

  protected def isTraceEnabled(): Boolean = {
    log.isTraceEnabled
  }

  private def initializeIfNecessary() {
    if (!Logging.initialized) {
      Logging.initLock.synchronized {
        if (!Logging.initialized) {
          initializeLogging()
        }
      }
    }
  }

  private def initializeLogging() {
    // Don't use a logger in here, as this is itself occurring during initialization of a logger
    // If Log4j 1.2 is being used, but is not initialized, load a default properties file
    val binderClass = StaticLoggerBinder.getSingleton.getLoggerFactoryClassStr
    // This distinguishes the log4j 1.2 binding, currently
    // org.slf4j.impl.Log4jLoggerFactory, from the log4j 2.0 binding, currently
    // org.apache.logging.slf4j.Log4jLoggerFactory
    val usingLog4j12 = "org.slf4j.impl.Log4jLoggerFactory".equals(binderClass)

    lazy val isInInterpreter: Boolean = {
      try {
        val interpClass = classForName("org.apache.spark.repl.Main")
        interpClass.getMethod("interp").invoke(null) != null
      } catch {
        case _: ClassNotFoundException => false
      }
    }
    def classForName(className: String): Class[_] = {
      Class.forName(className, true, getContextOrSparkClassLoader)
      // scalastyle:on classforname
    }
    def getContextOrSparkClassLoader: ClassLoader =
      Option(Thread.currentThread().getContextClassLoader).getOrElse(getSparkClassLoader)
    def getSparkClassLoader: ClassLoader = getClass.getClassLoader

    if (usingLog4j12) {
      val log4j12Initialized = LogManager.getRootLogger.getAllAppenders.hasMoreElements
      if (!log4j12Initialized) {
        // scalastyle:off println
        if (isInInterpreter) {
          val replDefaultLogProps = "org/apache/spark/log4j-defaults-repl.properties"
          Option(Utils.getSparkClassLoader.getResource(replDefaultLogProps)) match {
            case Some(url) =>
              PropertyConfigurator.configure(url)
              System.err.println(s"Using Spark's repl log4j profile: $replDefaultLogProps")
              System.err.println("To adjust logging level use sc.setLogLevel(\"INFO\")")
            case None =>
              System.err.println(s"Spark was unable to load $replDefaultLogProps")
          }
        } else {
          val defaultLogProps = "org/apache/spark/log4j-defaults.properties"
          Option(Utils.getSparkClassLoader.getResource(defaultLogProps)) match {
            case Some(url) =>
              PropertyConfigurator.configure(url)
              System.err.println(s"Using Spark's default log4j profile: $defaultLogProps")
            case None =>
              System.err.println(s"Spark was unable to load $defaultLogProps")
          }
        }
        // scalastyle:on println
      }
    }
    Logging.initialized = true

    // Force a call into slf4j to initialize it. Avoids this happening from multiple threads
    // and triggering this: http://mailman.qos.ch/pipermail/slf4j-dev/2010-April/002956.html
    log
  }
}

private object Logging {
  @volatile private var initialized = false
  val initLock = new Object()
  try {
    // We use reflection here to handle the case where users remove the
    // slf4j-to-jul bridge order to route their logs to JUL.
    val bridgeClass = Utils.classForName("org.slf4j.bridge.SLF4JBridgeHandler")
    bridgeClass.getMethod("removeHandlersForRootLogger").invoke(null)
    val installed = bridgeClass.getMethod("isInstalled").invoke(null).asInstanceOf[Boolean]
    if (!installed) {
      bridgeClass.getMethod("install").invoke(null)
    }
  } catch {
    case e: ClassNotFoundException => // can't log anything yet so just fail silently
  }
}

打包运行

将生成的jar包放到spark的jar包文件夹下，然后在使用spark-submit-2.1.0就不会出现问题了。