Spark中常用工具类Utils的简明介绍-阿里云开发者社区

《深入理解Spark：核心思想与源码分析》一书前言的内容请看链接《深入理解SPARK：核心思想与源码分析》一书正式出版上市

《深入理解Spark：核心思想与源码分析》一书第一章的内容请看链接《第1章环境准备》

《深入理解Spark：核心思想与源码分析》一书第二章的内容请看链接《第2章 SPARK设计理念与基本架构》

《深入理解Spark：核心思想与源码分析》一书第三章第一部分的内容请看链接《深入理解Spark：核心思想与源码分析》——SparkContext的初始化（伯篇）》

《深入理解Spark：核心思想与源码分析》一书第三章第二部分的内容请看链接《深入理解Spark：核心思想与源码分析》——SparkContext的初始化（仲篇）》

《深入理解Spark：核心思想与源码分析》一书第三章第三部分的内容请看链接《深入理解Spark：核心思想与源码分析》——SparkContext的初始化（叔篇）》

《深入理解Spark：核心思想与源码分析》一书第三章第四部分的内容请看链接《深入理解Spark：核心思想与源码分析》——SparkContext的初始化（季篇）》

Utils是Spark中最常用的工具类之一，如果不关心其实现，也不会对理解Spark有太多影响。但是对于Scala或者Spark的初学者来说，通过了解Utils工具类的实现，也是个不错的入门途径。下面将逐个介绍Utils工具类提供的常用方法。

1.localHostName

功能描述：获取本地机器名。

def localHostName(): String = {
    customHostname.getOrElse(localIpAddressHostname)
  }

2.getDefaultPropertiesFile

功能描述：获取默认的Spark属性文件。

  def getDefaultPropertiesFile(env: Map[String, String] = sys.env): String = {
    env.get("SPARK_CONF_DIR")
      .orElse(env.get("SPARK_HOME").map{ t => s"$t${File.separator}conf"})
      .map { t => new File(s"$t${File.separator}spark-defaults.conf")}
      .filter(_.isFile)
      .map(_.getAbsolutePath)
      .orNull
  }

3.loadDefaultSparkProperties

功能描述：加载指定文件中的Spark属性，如果没有指定文件，则加载默认Spark属性文件的属性。

  def loadDefaultSparkProperties(conf:SparkConf, filePath: String = null):String = {
    val path =Option(filePath).getOrElse(getDefaultPropertiesFile())
    Option(path).foreach { confFile =>
      getPropertiesFromFile(confFile).filter{ case (k,v) =>
        k.startsWith("spark.")
      }.foreach { case (k, v) =>
       conf.setIfMissing(k, v)
       sys.props.getOrElseUpdate(k, v)
      }
    }
    path
  }

4.getCallSite

功能描述：获取当前SparkContext的当前调用堆栈，将栈里最靠近栈底的属于spark或者Scala核心的类压入callStack的栈顶，并将此类的方法存入lastSparkMethod；将栈里最靠近栈顶的用户类放入callStack，将此类的行号存入firstUserLine，类名存入firstUserFile，最终返回的样例类CallSite存储了最短栈和长度默认为20的最长栈的样例类。在JavaWordCount例子中，获得的数据如下：

最短栈：JavaSparkContext at JavaWordCount.java:44；
最长栈：org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:61)org.apache.spark.examples.JavaWordCount.main(JavaWordCount.java:44)。

def getCallSite(skipClass: String => Boolean =coreExclusionFunction): CallSite = {
    val trace =Thread.currentThread.getStackTrace().filterNot { ste: StackTraceElement=>
      ste == null || ste.getMethodName == null || ste.getMethodName.contains("getStackTrace")
    }
    var lastSparkMethod= "<unknown>"
    var firstUserFile= "<unknown>"
    var firstUserLine= 0
    var insideSpark= true
    var callStack= new ArrayBuffer[String]() :+ "<unknown>"
 
    for (el<- trace) {
      if (insideSpark){
        if (skipClass(el.getClassName)){
          lastSparkMethod = if(el.getMethodName == "<init>") {
            el.getClassName.substring(el.getClassName.lastIndexOf('.') + 1)
          } else {
            el.getMethodName
          }
          callStack(0) = el.toString // Putlast Spark method on top of the stack trace.
        } else {
          firstUserLine = el.getLineNumber
          firstUserFile = el.getFileName
          callStack += el.toString
          insideSpark = false
        }
      } else {
        callStack += el.toString
      }
    }
    val callStackDepth= System.getProperty("spark.callstack.depth","20").toInt
    CallSite(
      shortForm = s"$lastSparkMethod at $firstUserFile:$firstUserLine",
      longForm = callStack.take(callStackDepth).mkString("\n"))
  }

5.startServiceOnPort

功能描述：Scala跟其它脚本语言一样，函数也可以传递，此方法正是通过回调startService这个函数来启动服务，并最终返回startService返回的service地址及端口。如果启动过程有异常，还会多次重试，直到达到maxRetries表示的最大次数。

 def startServiceOnPort[T](
      startPort:Int,
      startService:Int => (T, Int),
      conf:SparkConf,
      serviceName:String = ""): (T, Int) = {
   require(startPort == 0 || (1024 <= startPort && startPort < 65536),
      "startPort should be between 1024 and 65535(inclusive), or 0 for a random free port.")
    val serviceString= if (serviceName.isEmpty) "" elses" '$serviceName'"
    val maxRetries= portMaxRetries(conf)
    for (offset<- 0 to maxRetries){
      val tryPort= if (startPort == 0) {
        startPort
      } else {
        ((startPort+ offset - 1024)% (65536 - 1024))+ 1024
      }
      try {
        val (service,port) = startService(tryPort)
        logInfo(s"Successfullystarted service$serviceString on port $port.")
        return (service,port)
      } catch {
        case e:Exception if isBindCollision(e) =>
          if (offset>= maxRetries) {
            val exceptionMessage=
              s"${e.getMessage}:Service$serviceString failed after $maxRetries retries!"
            val exception= new BindException(exceptionMessage)
            exception.setStackTrace(e.getStackTrace)
            throw exception
          }
         logWarning(s"Service$serviceString couldnot bind on port $tryPort. " +
            s"Attempting port ${tryPort+ 1}.")
      }
    }
    throw newSparkException(s"Failed to start service$serviceString on port$startPort")
  }

6.createDirectory

功能描述：用spark+UUID的方式创建临时文件目录，如果创建失败会多次重试，最多重试10次。

  def createDirectory(root: String, namePrefix: String = "spark"): File = {
    var attempts = 0
    val maxAttempts = MAX_DIR_CREATION_ATTEMPTS
    var dir: File = null
    while (dir == null){
      attempts += 1
      if (attempts > maxAttempts) {
        throw newIOException("Failed to create a temp directory(under " + root + ") after "+
         maxAttempts + " attempts!")
      }
      try {
        dir = new File(root, "spark-"+ UUID.randomUUID.toString)
        if (dir.exists() || !dir.mkdirs()) {
          dir = null
        }
      } catch { casee: SecurityException => dir = null;}
    }
 
    dir
  }

7.getOrCreateLocalRootDirs

功能描述：根据spark.local.dir的配置，作为本地文件的根目录，在创建一、二级目录之前要确保根目录是存在的。然后调用createDirectory创建一级目录。

  private[spark] defgetOrCreateLocalRootDirs(conf: SparkConf): Array[String] = {
    if (isRunningInYarnContainer(conf)) {
     getYarnLocalDirs(conf).split(",")
    } else {
     Option(conf.getenv("SPARK_LOCAL_DIRS"))
       .getOrElse(conf.get("spark.local.dir",System.getProperty("java.io.tmpdir")))
        .split(",")
        .flatMap {root =>
          try {
            val rootDir = newFile(root)
            if (rootDir.exists || rootDir.mkdirs()) {
              val dir = createDirectory(root)
             chmod700(dir)
             Some(dir.getAbsolutePath)
            } else {
             logError(s"Failed to create dir in $root. Ignoring this directory.")
              None
            }
          } catch {
            case e: IOException =>
           logError(s"Failed to create local rootdir in $root. Ignoring this directory.")
            None
          }
        }
        .toArray
    }
  }

8.getLocalDir

功能描述：查询Spark本地文件的一级目录。

  def getLocalDir(conf: SparkConf): String = {
   getOrCreateLocalRootDirs(conf)(0)
  }

9.createTempDir

功能描述：在Spark一级目录下创建临时目录，并将目录注册到shutdownDeletePaths：scala.collection.mutable.HashSet[String]中。

  def createTempDir(
      root: String= System.getProperty("java.io.tmpdir"),
      namePrefix:String = "spark"): File = {
    val dir =createDirectory(root, namePrefix)
   registerShutdownDeleteDir(dir)
    dir
  }

10.RegisterShutdownDeleteDir

功能描述：将目录注册到shutdownDeletePaths：scala.collection.mutable.HashSet[String]中，以便在进程退出时删除。

  def registerShutdownDeleteDir(file: File) {
    val absolutePath =file.getAbsolutePath()
    shutdownDeletePaths.synchronized{
      shutdownDeletePaths += absolutePath
    }
  }

11.hasRootAsShutdownDeleteDir

功能描述：判断文件是否匹配关闭时要删除的文件及目录，shutdownDeletePaths：scala.collection.mutable.HashSet[String]存储在进程关闭时要删除的文件及目录。

  def hasRootAsShutdownDeleteDir(file: File): Boolean = {
    val absolutePath= file.getAbsolutePath()
    val retval= shutdownDeletePaths.synchronized {
      shutdownDeletePaths.exists { path =>
        !absolutePath.equals(path) && absolutePath.startsWith(path)
      }
    }
    if (retval){
      logInfo("path = " + file + ", already present as root for deletion.")
    }
    retval
  }

12.deleteRecursively

功能描述：用于删除文件或者删除目录及其子目录、子文件，并且从shutdownDeletePaths：scala.collection.mutable.HashSet[String]中移除此文件或目录。

  def deleteRecursively(file: File) {
    if (file != null){
      try {
        if (file.isDirectory &&!isSymlink(file)) {
          var savedIOException:IOException = null
          for (child<- listFilesSafely(file)) {
            try {
             deleteRecursively(child)
            } catch {
              case ioe:IOException => savedIOException = ioe
            }
          }
          if (savedIOException!= null) {
            throw savedIOException
          }
          shutdownDeletePaths.synchronized {
            shutdownDeletePaths.remove(file.getAbsolutePath)
          }
        }
      } finally {
        if (!file.delete()) {
          if (file.exists()) {
            throw newIOException("Failed to delete: " +file.getAbsolutePath)
          }
        }
      }
    }
  }

13.getSparkClassLoader

功能描述：获取加载当前class的ClassLoader。

def getSparkClassLoader = getClass.getClassLoader

14.getContextOrSparkClassLoader

功能描述：用于获取线程上下文的ClassLoader，没有设置时获取加载Spark的ClassLoader。

 def getContextOrSparkClassLoader =
   Option(Thread.currentThread().getContextClassLoader).getOrElse(getSparkClassLoader)

15.newDaemonCachedThreadPool

功能描述：使用Executors.newCachedThreadPool创建的缓存线程池。

  def newDaemonCachedThreadPool(prefix: String): ThreadPoolExecutor = {
    val threadFactory =namedThreadFactory(prefix)
   Executors.newCachedThreadPool(threadFactory).asInstanceOf[ThreadPoolExecutor]
  }

16.doFetchFile

功能描述：使用URLConnection通过http协议下载文件。

  private defdoFetchFile(url: String, targetDir: File, filename: String, conf: SparkConf,
      securityMgr:SecurityManager, hadoopConf: Configuration) {
    val tempFile= File.createTempFile("fetchFileTemp",null, newFile(targetDir.getAbsolutePath))
    val targetFile= new File(targetDir, filename)
    val uri = new URI(url)
    val fileOverwrite= conf.getBoolean("spark.files.overwrite",defaultValue = false)
    Option(uri.getScheme).getOrElse("file")match {
      case "http"| "https" | "ftp" =>
        logInfo("Fetching " + url + " to " + tempFile)
        var uc:URLConnection = null
        if (securityMgr.isAuthenticationEnabled()) {
          logDebug("fetchFile with security enabled")
          val newuri= constructURIForAuthentication(uri,securityMgr)
          uc = newuri.toURL().openConnection()
          uc.setAllowUserInteraction(false)
        } else {
          logDebug("fetchFile not using security")
          uc = newURL(url).openConnection()
        }
        valtimeout = conf.getInt("spark.files.fetchTimeout", 60) * 1000
        uc.setConnectTimeout(timeout)
        uc.setReadTimeout(timeout)
        uc.connect()
        val in = uc.getInputStream()
       downloadFile(url, in, tempFile, targetFile,fileOverwrite)
      case "file"=>
        val sourceFile= if (uri.isAbsolute)new File(uri)else newFile(url)
       copyFile(url, sourceFile, targetFile, fileOverwrite)
      case _ =>
        val fs =getHadoopFileSystem(uri, hadoopConf)
        val in = fs.open(newPath(uri))
       downloadFile(url, in, tempFile, targetFile,fileOverwrite)
    }
  }

17.fetchFile

功能描述：如果文件在本地有缓存，则从本地获取，否则通过HTTP远程下载。最后对.tar、.tar.gz等格式的文件解压缩后，调用shell命令行的chmod命令给文件增加a+x的权限。

  def fetchFile(
      url: String,
      targetDir:File,
      conf:SparkConf,
      securityMgr:SecurityManager,
      hadoopConf:Configuration,
      timestamp:Long,
      useCache:Boolean) {
    val fileName= url.split("/").last
    val targetFile= new File(targetDir, fileName)
    val fetchCacheEnabled= conf.getBoolean("spark.files.useFetchCache",defaultValue = true)
    if (useCache && fetchCacheEnabled) {
      val cachedFileName= s"${url.hashCode}${timestamp}_cache"
      val lockFileName= s"${url.hashCode}${timestamp}_lock"
      val localDir= new File(getLocalDir(conf))
      val lockFile= new File(localDir,lockFileName)
      val raf = new RandomAccessFile(lockFile,"rw")
      val lock = raf.getChannel().lock()
      val cachedFile= new File(localDir,cachedFileName)
      try {
        if (!cachedFile.exists()){
         doFetchFile(url, localDir, cachedFileName, conf, securityMgr, hadoopConf)
        }
      } finally {
        lock.release()
      }
      copyFile(
        url,
        cachedFile,
        targetFile,
       conf.getBoolean("spark.files.overwrite",false)
      )
    } else {
     doFetchFile(url, targetDir, fileName,conf, securityMgr, hadoopConf)
    }
    if (fileName.endsWith(".tar.gz") || fileName.endsWith(".tgz")) {
      logInfo("Untarring " + fileName)
     Utils.execute(Seq("tar", "-xzf", fileName),targetDir)
    } else if(fileName.endsWith(".tar")){
      logInfo("Untarring " + fileName)
     Utils.execute(Seq("tar", "-xf", fileName),targetDir)
    }
    FileUtil.chmod(targetFile.getAbsolutePath, "a+x")
  }

18.executeAndGetOutput

功能描述：执行一条command命令，并且获取它的输出。调用stdoutThread的join方法，让当前线程等待stdoutThread执行完成。

  def executeAndGetOutput(
      command:Seq[String],
      workingDir:File = new File("."),
     extraEnvironment: Map[String, String] = Map.empty): String = {
    val builder= new ProcessBuilder(command: _*)
       .directory(workingDir)
    val environment= builder.environment()
    for ((key, value) <- extraEnvironment) {
      environment.put(key,value)
    }
    val process= builder.start()
    new Thread("readstderr for " + command(0)) {
      override defrun() {
        for (line<- Source.fromInputStream(process.getErrorStream).getLines()){
          System.err.println(line)
        }
      }
    }.start()
    val output= new StringBuffer
    val stdoutThread= new Thread("readstdout for " + command(0)) {
      override defrun() {
        for (line<- Source.fromInputStream(process.getInputStream).getLines()){
          output.append(line)
        }
      }
    }
    stdoutThread.start()
    val exitCode= process.waitFor()
    stdoutThread.join()   // Wait for itto finish reading output
    if (exitCode!= 0) {
      logError(s"Process $commandexited with code $exitCode: $output")
      throw newSparkException(s"Process $command exited with code $exitCode")
    }
    output.toString
  }

19.memoryStringToMb

功能描述：将内存大小字符串转换为以MB为单位的整型值。

  def memoryStringToMb(str: String): Int = {
    val lower =str.toLowerCase
    if (lower.endsWith("k")) {
      (lower.substring(0,lower.length-1).toLong/ 1024).toInt
    } else if(lower.endsWith("m")){
      lower.substring(0,lower.length-1).toInt
    } else if(lower.endsWith("g")){
      lower.substring(0,lower.length-1).toInt* 1024
    } else if(lower.endsWith("t")){
      lower.substring(0,lower.length-1).toInt* 1024 * 1024
    } else {// nosuffix, so it's just a number in bytes
      (lower.toLong / 1024/ 1024).toInt
    }
  }

Spark中常用工具类Utils的简明介绍