SparkContext初始化过程

// 用于存储配置信息
private val settings = new ConcurrentHashMap[String, String]()

if (loadDefaults) {
  loadFromSystemProperties(false)
}

// 加载任何以 "spark." 开头的系统属性
private[spark] def loadFromSystemProperties(silent: Boolean): SparkConf = {
  // Load any spark.* system properties
  for ((key, value) <- Utils.getSystemProperties if key.startsWith("spark.")) {
    set(key, value, silent)
  }
  this
}

class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationClient {

  // 存储了线程栈中最靠近栈顶的用户类及靠近栈底的scla或者spark核心类信息
  private val creationSite: CallSite = Utils.getCallSite()
  //用于设置SparkContext是否在一个jvm内保持单例,默认是单例
  private val allowMultipleContexts: Boolean = config.getBoolean("spark.driver.allowMultipleContexts", false)
  //用来确保实例的唯一性,并标记当前实例为正在构建
  SparkContext.markPartiallyConstructed(this, allowMultipleContexts)

private[spark] def conf: SparkConf = _conf

/**
 * Return a copy of this SparkContext‘s configuration. The configuration ‘‘cannot‘‘ be
 * changed at runtime.
 */
def getConf: SparkConf = conf.clone()

def jars: Seq[String] = _jars
def files: Seq[String] = _files
def master: String = _conf.get("spark.master")
def deployMode: String = _conf.getOption("spark.submit.deployMode").getOrElse("client")
def appName: String = _conf.get("spark.app.name")

private[spark] def isEventLogEnabled: Boolean = _conf.getBoolean("spark.eventLog.enabled", false)
private[spark] def eventLogDir: Option[URI] = _eventLogDir
private[spark] def eventLogCodec: Option[String] = _eventLogCodec

def isLocal: Boolean = Utils.isLocalMaster(_conf)

_conf.validateSettings()

if (!_conf.contains("spark.master")) {
  throw new SparkException("A master URL must be set in your configuration")
}
if (!_conf.contains("spark.app.name")) {
  throw new SparkException("An application name must be set in your configuration")
}

// System property spark.yarn.app.id must be set if user code ran by AM on a YARN cluster
if (master == "yarn" && deployMode == "cluster" && !_conf.contains("spark.yarn.app.id")) {
  throw new SparkException("Detected yarn cluster mode, but isn‘t running on a cluster. " +
    "Deployment to YARN is not supported directly by SparkContext. Please use spark-submit.")
}