Spark（十五）SparkCore的源碼解讀

一、啟動腳本分析

獨立部署模式下，主要由master和slaves組成，master可以利用zk實現高可用性，其driver，work，app等信息可以持久化到zk上；slaves由一台至多台主機構成。Driver通過向Master申請資源獲取運行環境。

啟動master和slaves主要是執行/usr/dahua/spark/sbin目錄下的start-master.sh和start-slaves.sh，或者執行

start-all.sh，其中star-all.sh本質上就是調用start-master.sh和start-slaves.sh

1.1　start-all.sh 

#1.判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi

#2.執行${SPARK_HOME}/sbin/spark-config.sh，見以下分析
. "${SPARK_HOME}/sbin/spark-config.sh"

#3.執行"${SPARK_HOME}/sbin"/start-master.sh，見以下分析
"${SPARK_HOME}/sbin"/start-master.sh

#4.執行"${SPARK_HOME}/sbin"/start-slaves.sh，見以下分析
"${SPARK_HOME}/sbin"/start-slaves.sh

其中start-master.sh和start-slave.sh分別調用的是

org.apache.spark.deploy.master.Master和org.apache.spark.deploy.worker.Worker

1.2　start-master.sh

start-master.sh調用了spark-daemon.sh，注意這里指定了啟動的類

#1.判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi

# NOTE: This exact class name is matched downstream by SparkSubmit.
# Any changes need to be reflected there.
#2.設置CLASS="org.apache.spark.deploy.master.Master"
CLASS="org.apache.spark.deploy.master.Master"

#3.如果參數結尾包含--help或者-h則打印幫助信息，並退出
if [[ "$@" = *--help ]] || [[ "$@" = *-h ]]; then
  echo "Usage: ./sbin/start-master.sh [options]"
  pattern="Usage:"
  pattern+="\|Using Spark's default log4j profile:"
  pattern+="\|Registered signal handlers for"

  "${SPARK_HOME}"/bin/spark-class $CLASS --help 2>&1 | grep -v "$pattern" 1>&2
  exit 1
fi

#4.設置ORIGINAL_ARGS為所有參數
ORIGINAL_ARGS="$@"
#5.執行${SPARK_HOME}/sbin/spark-config.sh
. "${SPARK_HOME}/sbin/spark-config.sh"
#6.執行${SPARK_HOME}/bin/load-spark-env.sh
. "${SPARK_HOME}/bin/load-spark-env.sh"
#7.SPARK_MASTER_PORT為空則賦值7077
if [ "$SPARK_MASTER_PORT" = "" ]; then
  SPARK_MASTER_PORT=7077
fi
#8.SPARK_MASTER_HOST為空則賦值本主機名(hostname)
if [ "$SPARK_MASTER_HOST" = "" ]; then
  case `uname` in
      (SunOS)
      SPARK_MASTER_HOST="`/usr/sbin/check-hostname | awk '{print $NF}'`"
      ;;
      (*)
      SPARK_MASTER_HOST="`hostname -f`"
      ;;
  esac
fi
#9.SPARK_MASTER_WEBUI_PORT為空則賦值8080
if [ "$SPARK_MASTER_WEBUI_PORT" = "" ]; then
  SPARK_MASTER_WEBUI_PORT=8080
fi
#10.執行腳本
"${SPARK_HOME}/sbin"/spark-daemon.sh start $CLASS 1 \
  --host $SPARK_MASTER_HOST --port $SPARK_MASTER_PORT --webui-port $SPARK_MASTER_WEBUI_PORT \
  $ORIGINAL_ARGS

其中10肯定是重點，分析之前我們看看5，6都干了些啥，最后直譯出最后一個腳本

1.3　spark-config.sh(1.2的第5步)

#判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi
#SPARK_CONF_DIR存在就用此目錄，不存在用${SPARK_HOME}/conf
export SPARK_CONF_DIR="${SPARK_CONF_DIR:-"${SPARK_HOME}/conf"}"
# Add the PySpark classes to the PYTHONPATH:
if [ -z "${PYSPARK_PYTHONPATH_SET}" ]; then
  export PYTHONPATH="${SPARK_HOME}/python:${PYTHONPATH}"
  export PYTHONPATH="${SPARK_HOME}/python/lib/py4j-0.10.6-src.zip:${PYTHONPATH}"
  export PYSPARK_PYTHONPATH_SET=1
fi

1.4　load-spark-env.sh(1.2的第6步)

#1.判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  source "$(dirname "$0")"/find-spark-home
fi
#2.判斷SPARK_ENV_LOADED是否有值，沒有將其設置為1
if [ -z "$SPARK_ENV_LOADED" ]; then
  export SPARK_ENV_LOADED=1
#3.設置user_conf_dir為SPARK_CONF_DIR或SPARK_HOME/conf
  export SPARK_CONF_DIR="${SPARK_CONF_DIR:-"${SPARK_HOME}"/conf}"
#4.執行"${user_conf_dir}/spark-env.sh" [注：set -/+a含義再做研究]
  if [ -f "${SPARK_CONF_DIR}/spark-env.sh" ]; then
    # Promote all variable declarations to environment (exported) variables
    set -a
    . "${SPARK_CONF_DIR}/spark-env.sh"
    set +a
  fi
fi

# Setting SPARK_SCALA_VERSION if not already set.
#5.選擇scala版本，2.11和2.12都存在的情況下，優先選擇2.11
if [ -z "$SPARK_SCALA_VERSION" ]; then

  ASSEMBLY_DIR2="${SPARK_HOME}/assembly/target/scala-2.11"
  ASSEMBLY_DIR1="${SPARK_HOME}/assembly/target/scala-2.12"

  if [[ -d "$ASSEMBLY_DIR2" && -d "$ASSEMBLY_DIR1" ]]; then
    echo -e "Presence of build for multiple Scala versions detected." 1>&2
    echo -e 'Either clean one of them or, export SPARK_SCALA_VERSION in spark-env.sh.' 1>&2
    exit 1
  fi

  if [ -d "$ASSEMBLY_DIR2" ]; then
    export SPARK_SCALA_VERSION="2.11"
  else
    export SPARK_SCALA_VERSION="2.12"
  fi
fi

1.5　spark-env.sh

列舉很多種模式的選項配置

1.6　spark-daemon.sh

回過頭來看看1.2第10步中需要直譯出的最后一個腳本,如下：

sbin/spark-daemon.sh start org.apache.spark.deploy.master.Master 1 --host hostname --port 7077 --webui-port 8080

上面搞了半天只是設置了變量，最終才進入主角，繼續分析spark-daemon.sh腳本

#1.參數個數小於等於1，打印幫助
if [ $# -le 1 ]; then
  echo $usage
  exit 1
fi
#2.判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi
#3.執行${SPARK_HOME}/sbin/spark-config.sh，見上述分析 [類似腳本是否有重復？原因是有的人是直接用spark-daemon.sh啟動的服務，反正重復設置下變量不需要什么代價]
. "${SPARK_HOME}/sbin/spark-config.sh"

# get arguments

# Check if --config is passed as an argument. It is an optional parameter.
# Exit if the argument is not a directory.

#4.判斷第一個參數是否是--config,如果是取空格后一個字符串，然后判斷該目錄是否存在，不存在則打印錯誤信息並退出，存在設置SPARK_CONF_DIR為該目錄,shift到下一個參數
#[注：--config只能用在第一參數上]
if [ "$1" == "--config" ]
then
  shift
  conf_dir="$1"
  if [ ! -d "$conf_dir" ]
  then
    echo "ERROR : $conf_dir is not a directory"
    echo $usage
    exit 1
  else
    export SPARK_CONF_DIR="$conf_dir"
  fi
  shift
fi
#5.分別設置option、command、instance為后面的三個參數(如：option=start,command=org.apache.spark.deploy.master.Master,instance=1)
#[注：很多人用spark-daemon.sh啟動服務不成功的原因是名字不全]
option=$1
shift
command=$1
shift
instance=$1
shift
#6.日志回滾函數，主要用於更改日志名，如log-->log.1等，略過
spark_rotate_log ()
{
    log=$1;
    num=5;
    if [ -n "$2" ]; then
    num=$2
    fi
    if [ -f "$log" ]; then # rotate logs
    while [ $num -gt 1 ]; do
        prev=`expr $num - 1`
        [ -f "$log.$prev" ] && mv "$log.$prev" "$log.$num"
        num=$prev
    done
    mv "$log" "$log.$num";
    fi
}
#7.執行${SPARK_HOME}/bin/load-spark-env.sh，見上述分析
. "${SPARK_HOME}/bin/load-spark-env.sh"

#8.判斷SPARK_IDENT_STRING是否有值，沒有將其設置為$USER(linux用戶)
if [ "$SPARK_IDENT_STRING" = "" ]; then
  export SPARK_IDENT_STRING="$USER"
fi

#9.設置SPARK_PRINT_LAUNCH_COMMAND=1
export SPARK_PRINT_LAUNCH_COMMAND="1"

# get log directory
#10.判斷SPARK_LOG_DIR是否有值，沒有將其設置為${SPARK_HOME}/logs，並創建改目錄，測試創建文件，修改權限
if [ "$SPARK_LOG_DIR" = "" ]; then
  export SPARK_LOG_DIR="${SPARK_HOME}/logs"
fi
mkdir -p "$SPARK_LOG_DIR"
touch "$SPARK_LOG_DIR"/.spark_test > /dev/null 2>&1
TEST_LOG_DIR=$?
if [ "${TEST_LOG_DIR}" = "0" ]; then
  rm -f "$SPARK_LOG_DIR"/.spark_test
else
  chown "$SPARK_IDENT_STRING" "$SPARK_LOG_DIR"
fi

#11.判斷SPARK_PID_DIR是否有值，沒有將其設置為/tmp
if [ "$SPARK_PID_DIR" = "" ]; then
  SPARK_PID_DIR=/tmp
fi

# some variables
#12.設置log和pid
log="$SPARK_LOG_DIR/spark-$SPARK_IDENT_STRING-$command-$instance-$HOSTNAME.out"
pid="$SPARK_PID_DIR/spark-$SPARK_IDENT_STRING-$command-$instance.pid"

# Set default scheduling priority
#13.判斷SPARK_NICENESS是否有值，沒有將其設置為0 [注：調度優先級，見后面]
if [ "$SPARK_NICENESS" = "" ]; then
    export SPARK_NICENESS=0
fi

#14.execute_command()函數，暫且略過，調用時再作分析
execute_command() {
  if [ -z ${SPARK_NO_DAEMONIZE+set} ]; then
      nohup -- "$@" >> $log 2>&1 < /dev/null &
      newpid="$!"

      echo "$newpid" > "$pid"

      # Poll for up to 5 seconds for the java process to start
      for i in {1..10}
      do
        if [[ $(ps -p "$newpid" -o comm=) =~ "java" ]]; then
           break
        fi
        sleep 0.5
      done

      sleep 2
      # Check if the process has died; in that case we'll tail the log so the user can see
      if [[ ! $(ps -p "$newpid" -o comm=) =~ "java" ]]; then
        echo "failed to launch: $@"
        tail -10 "$log" | sed 's/^/  /'
        echo "full log in $log"
      fi
  else
      "$@"
  fi
}
#15.進入case語句，判斷option值，進入該分支，我們以start為例
#   執行run_command class "$@"，其中$@此時為空，經驗證，啟動帶上此參數后，關閉也需，不然關閉不了，后面再分析此參數作用
#   我們正式進入run_command()函數，分析
#   I.設置mode=class,創建SPARK_PID_DIR，上面的pid文件是否存在，
#   II.SPARK_MASTER不為空，同步刪除某些文件
#   III.回滾log日志
#   IV.進入case，command=org.apache.spark.deploy.master.Master，最終執行
#       nohup nice -n "$SPARK_NICENESS" "${SPARK_HOME}"/bin/spark-class $command "$@" >> "$log" 2>&1 < /dev/null &
#       newpid="$!"
#       echo "$newpid" > "$pid"
#   重點轉向bin/spark-class org.apache.spark.deploy.master.Master
run_command() {
  mode="$1"
  shift

  mkdir -p "$SPARK_PID_DIR"

  if [ -f "$pid" ]; then
    TARGET_ID="$(cat "$pid")"
    if [[ $(ps -p "$TARGET_ID" -o comm=) =~ "java" ]]; then
      echo "$command running as process $TARGET_ID.  Stop it first."
      exit 1
    fi
  fi

  if [ "$SPARK_MASTER" != "" ]; then
    echo rsync from "$SPARK_MASTER"
    rsync -a -e ssh --delete --exclude=.svn --exclude='logs/*' --exclude='contrib/hod/logs/*' "$SPARK_MASTER/" "${SPARK_HOME}"
  fi

  spark_rotate_log "$log"
  echo "starting $command, logging to $log"

  case "$mode" in
    (class)
      execute_command nice -n "$SPARK_NICENESS" "${SPARK_HOME}"/bin/spark-class "$command" "$@"
      ;;

    (submit)
      execute_command nice -n "$SPARK_NICENESS" bash "${SPARK_HOME}"/bin/spark-submit --class "$command" "$@"
      ;;

    (*)
      echo "unknown mode: $mode"
      exit 1
      ;;
  esac

}

case $option in

  (submit)
    run_command submit "$@"
    ;;

  (start)
    run_command class "$@"
    ;;

  (stop)

    if [ -f $pid ]; then
      TARGET_ID="$(cat "$pid")"
      if [[ $(ps -p "$TARGET_ID" -o comm=) =~ "java" ]]; then
        echo "stopping $command"
        kill "$TARGET_ID" && rm -f "$pid"
      else
        echo "no $command to stop"
      fi
    else
      echo "no $command to stop"
    fi
    ;;

  (status)

    if [ -f $pid ]; then
      TARGET_ID="$(cat "$pid")"
      if [[ $(ps -p "$TARGET_ID" -o comm=) =~ "java" ]]; then
        echo $command is running.
        exit 0
      else
        echo $pid file is present but $command not running
        exit 1
      fi
    else
      echo $command not running.
      exit 2
    fi
    ;;

  (*)
    echo $usage
    exit 1
    ;;

esac

1.7　spark-class

#1.判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  source "$(dirname "$0")"/find-spark-home
fi

#2.執行${SPARK_HOME}/bin/load-spark-env.sh，見上述分析
. "${SPARK_HOME}"/bin/load-spark-env.sh

# Find the java binary
#3.判斷JAVA_HOME是否為NULL，不是則設置RUNNER="${JAVA_HOME}/bin/java"，否則找系統自帶，在沒有則報未設置，並退出
if [ -n "${JAVA_HOME}" ]; then
  RUNNER="${JAVA_HOME}/bin/java"
else
  if [ "$(command -v java)" ]; then
    RUNNER="java"
  else
    echo "JAVA_HOME is not set" >&2
    exit 1
  fi
fi

# Find Spark jars.
#4.查找SPARK_JARS_DIR，若${SPARK_HOME}/RELEASE文件存在，則SPARK_JARS_DIR="${SPARK_HOME}/jars"，否則
#SPARK_JARS_DIR="${SPARK_HOME}/assembly/target/scala-$SPARK_SCALA_VERSION/jars"
if [ -d "${SPARK_HOME}/jars" ]; then
  SPARK_JARS_DIR="${SPARK_HOME}/jars"
else
  SPARK_JARS_DIR="${SPARK_HOME}/assembly/target/scala-$SPARK_SCALA_VERSION/jars"
fi

#5.若SPARK_JARS_DIR不存在且$SPARK_TESTING$SPARK_SQL_TESTING有值[注：一般我們不設置這兩變量]，報錯退出，否則LAUNCH_CLASSPATH="$SPARK_JARS_DIR/*"
if [ ! -d "$SPARK_JARS_DIR" ] && [ -z "$SPARK_TESTING$SPARK_SQL_TESTING" ]; then
  echo "Failed to find Spark jars directory ($SPARK_JARS_DIR)." 1>&2
  echo "You need to build Spark with the target \"package\" before running this program." 1>&2
  exit 1
else
  LAUNCH_CLASSPATH="$SPARK_JARS_DIR/*"
fi

# Add the launcher build dir to the classpath if requested.
#6.SPARK_PREPEND_CLASSES不是NULL，則LAUNCH_CLASSPATH="${SPARK_HOME}/launcher/target/scala-$SPARK_SCALA_VERSION/classes:$LAUNCH_CLASSPATH"，
#添加編譯相關至LAUNCH_CLASSPATH
if [ -n "$SPARK_PREPEND_CLASSES" ]; then
  LAUNCH_CLASSPATH="${SPARK_HOME}/launcher/target/scala-$SPARK_SCALA_VERSION/classes:$LAUNCH_CLASSPATH"
fi

# For tests
#7.SPARK_TESTING不是NULL，則unset YARN_CONF_DIR和unset HADOOP_CONF_DIR，暫且當做是為了某種測試
if [[ -n "$SPARK_TESTING" ]]; then
  unset YARN_CONF_DIR
  unset HADOOP_CONF_DIR
fi

#8.build_command函數，略過
build_command() {
  "$RUNNER" -Xmx128m -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$@"
  printf "%d\0" $?
}

# Turn off posix mode since it does not allow process substitution
set +o posix
CMD=()
while IFS= read -d '' -r ARG; do
  CMD+=("$ARG")
  #9.最終調用"$RUNNER" -Xmx128m -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$@"，
  #直譯：java -Xmx128m -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$@"
  #轉向java類org.apache.spark.launcher.Main，這就是java入口類
done < <(build_command "$@")

COUNT=${#CMD[@]}
LAST=$((COUNT - 1))
LAUNCHER_EXIT_CODE=${CMD[$LAST]}

# Certain JVM failures result in errors being printed to stdout (instead of stderr), which causes
# the code that parses the output of the launcher to get confused. In those cases, check if the
# exit code is an integer, and if it's not, handle it as a special error case.
if ! [[ $LAUNCHER_EXIT_CODE =~ ^[0-9]+$ ]]; then
  echo "${CMD[@]}" | head -n-1 1>&2
  exit 1
fi

if [ $LAUNCHER_EXIT_CODE != 0 ]; then
  exit $LAUNCHER_EXIT_CODE
fi

CMD=("${CMD[@]:0:$LAST}")
exec "${CMD[@]}"

1.8　start-slaves.sh

#1.判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi

#2.執行${SPARK_HOME}/sbin/spark-config.sh，見上述分析
. "${SPARK_HOME}/sbin/spark-config.sh"

#3.執行${SPARK_HOME}/bin/load-spark-env.sh，見上述分析
. "${SPARK_HOME}/bin/load-spark-env.sh"

# Find the port number for the master
#4.SPARK_MASTER_PORT為空則設置為7077
if [ "$SPARK_MASTER_PORT" = "" ]; then
  SPARK_MASTER_PORT=7077
fi

#5.SPARK_MASTER_HOST為空則設置為`hostname`
if [ "$SPARK_MASTER_HOST" = "" ]; then
  case `uname` in
      (SunOS)
      SPARK_MASTER_HOST="`/usr/sbin/check-hostname | awk '{print $NF}'`"
      ;;
      (*)
      SPARK_MASTER_HOST="`hostname -f`"
      ;;
  esac
fi

# Launch the slaves
#6.啟動slaves，
#   "${SPARK_HOME}/sbin/slaves.sh" cd "${SPARK_HOME}" \; "${SPARK_HOME}/sbin/start-slave.sh" "spark://$SPARK_MASTER_HOST:$SPARK_MASTER_PORT"
#   遍歷conf/slaves中主機，其中有設置SPARK_SSH_OPTS，ssh每一台機器執行"${SPARK_HOME}/sbin/start-slave.sh" "spark://$SPARK_MASTER_HOST:$SPARK_MASTER_PORT"
"${SPARK_HOME}/sbin/slaves.sh" cd "${SPARK_HOME}" \; "${SPARK_HOME}/sbin/start-slave.sh" "spark://$SPARK_MASTER_HOST:$SPARK_MASTER_PORT"

1.9　轉向start-slave.sh

#1.判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi

#2.設置CLASS="org.apache.spark.deploy.worker.Worker"
CLASS="org.apache.spark.deploy.worker.Worker"

#3.如果參數結尾包含--help或者-h則打印幫助信息，並退出
if [[ $# -lt 1 ]] || [[ "$@" = *--help ]] || [[ "$@" = *-h ]]; then
  echo "Usage: ./sbin/start-slave.sh [options] <master>"
  pattern="Usage:"
  pattern+="\|Using Spark's default log4j profile:"
  pattern+="\|Registered signal handlers for"

  "${SPARK_HOME}"/bin/spark-class $CLASS --help 2>&1 | grep -v "$pattern" 1>&2
  exit 1
fi

#4.執行${SPARK_HOME}/sbin/spark-config.sh，見上述分析
. "${SPARK_HOME}/sbin/spark-config.sh"
#5.執行${SPARK_HOME}/bin/load-spark-env.sh，見上述分析
. "${SPARK_HOME}/bin/load-spark-env.sh"

#6.MASTER=$1,這里MASTER=spark://hostname:7077，然后shift，也就是說單獨啟動單個slave使用start-slave.sh spark://hostname:7077
MASTER=$1
shift

#7.SPARK_WORKER_WEBUI_PORT為空則設置為8081
if [ "$SPARK_WORKER_WEBUI_PORT" = "" ]; then
  SPARK_WORKER_WEBUI_PORT=8081
fi

#8.函數start_instance，略過
function start_instance {
#設置WORKER_NUM=$1
  WORKER_NUM=$1
  shift

  if [ "$SPARK_WORKER_PORT" = "" ]; then
    PORT_FLAG=
    PORT_NUM=
  else
    PORT_FLAG="--port"
    PORT_NUM=$(( $SPARK_WORKER_PORT + $WORKER_NUM - 1 ))
  fi
  WEBUI_PORT=$(( $SPARK_WORKER_WEBUI_PORT + $WORKER_NUM - 1 ))

  #直譯：spark-daemon.sh start org.apache.spark.deploy.worker.Worker 1 --webui-port 7077 spark://hostname:7077
  #代碼再次轉向spark-daemon.sh，見上訴分析
  "${SPARK_HOME}/sbin"/spark-daemon.sh start $CLASS $WORKER_NUM \
     --webui-port "$WEBUI_PORT" $PORT_FLAG $PORT_NUM $MASTER "$@"
}

#9.判斷SPARK_WORKER_INSTANCES(可以認為是單節點Worker進程數)是否為空
#   為空，則start_instance 1 "$@"
#   不為空，則循環
#         for ((i=0; i<$SPARK_WORKER_INSTANCES; i++)); do
#           start_instance $(( 1 + $i )) "$@"
#         done
if [ "$SPARK_WORKER_INSTANCES" = "" ]; then
  start_instance 1 "$@"
else
  for ((i=0; i<$SPARK_WORKER_INSTANCES; i++)); do
  #10.轉向start_instance函數
    start_instance $(( 1 + $i )) "$@"
  done
fi

二、其他腳本

2.1　start-history-server.sh

#1.判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi

#2.執行${SPARK_HOME}/sbin/spark-config.sh，見上述分析
. "${SPARK_HOME}/sbin/spark-config.sh"
#3.執行${SPARK_HOME}/bin/load-spark-env.sh，見上述分析
. "${SPARK_HOME}/bin/load-spark-env.sh"
#4.exec "${SPARK_HOME}/sbin"/spark-daemon.sh start org.apache.spark.deploy.history.HistoryServer 1 $@ ，見上訴分析
exec "${SPARK_HOME}/sbin"/spark-daemon.sh start org.apache.spark.deploy.history.HistoryServer 1 "$@"

2.2　start-shuffle-service.sh

#1.判斷SPARK_HOME是否有值，沒有將其設置為當前文件所在目錄的上級目錄
if [ -z "${SPARK_HOME}" ]; then
  export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi

#2.執行${SPARK_HOME}/sbin/spark-config.sh，見上述分析
. "${SPARK_HOME}/sbin/spark-config.sh"
#3.執行${SPARK_HOME}/bin/load-spark-env.sh，見上述分析
. "${SPARK_HOME}/bin/load-spark-env.sh"
#4.exec "${SPARK_HOME}/sbin"/spark-daemon.sh start org.apache.spark.deploy.ExternalShuffleService 1 ，見上訴分析
exec "${SPARK_HOME}/sbin"/spark-daemon.sh start org.apache.spark.deploy.ExternalShuffleService 1

2.3　start-thriftserver.sh

開啟thriftserver，略

三、spark-submit處理邏輯分析

以上主要是介紹了spark啟動的一些腳本，這里主要分析一下Spark源碼中提交任務腳本的處理邏輯，從spark-submit一步步深入進去看看任務提交的整體流程,首先看一下整體的流程概要圖：

3.1　spark-submit

# -z是檢查后面變量是否為空（空則真） shell可以在雙引號之內引用變量，單引號不可
#這一步作用是檢查SPARK_HOME變量是否為空，為空則執行then后面程序
#source命令： source filename作用在當前bash環境下讀取並執行filename中的命令
#$0代表shell腳本文件本身的文件名，這里即使spark-submit
#dirname用於取得腳本文件所在目錄 dirname $0取得當前腳本文件所在目錄
#$(命令)表示返回該命令的結果
#故整個if語句的含義是：如果SPARK_HOME變量沒有設置值，則執行當前目錄下的find-spark-home腳本文件，設置SPARK_HOME值
if [ -z "${SPARK_HOME}" ]; then
  source "$(dirname "$0")"/find-spark-home
fi

# disable randomized hash for string in Python 3.3+
export PYTHONHASHSEED=0
#執行spark-class腳本，傳遞參數org.apache.spark.deploy.SparkSubmit 和"$@"
#這里$@表示之前spark-submit接收到的全部參數
exec "${SPARK_HOME}"/bin/spark-class org.apache.spark.deploy.SparkSubmit "$@"

所以spark-submit腳本的整體邏輯就是： 
首先 檢查SPARK_HOME是否設置；if 已經設置 執行spark-class文件 否則加載執行find-spark-home文件 

3.2　find-spark-home

#定義一個變量用於后續判斷是否存在定義SPARK_HOME的python腳本文件
FIND_SPARK_HOME_PYTHON_SCRIPT="$(cd "$(dirname "$0")"; pwd)/find_spark_home.py"

# Short cirtuit if the user already has this set.
##如果SPARK_HOME為不為空值，成功退出程序
if [ ! -z "${SPARK_HOME}" ]; then
   exit 0
# -f用於判斷這個文件是否存在並且是否為常規文件，是的話為真，這里不存在為假，執行下面語句，給SPARK_HOME變量賦值
elif [ ! -f "$FIND_SPARK_HOME_PYTHON_SCRIPT" ]; then
  # If we are not in the same directory as find_spark_home.py we are not pip installed so we don't
  # need to search the different Python directories for a Spark installation.
  # Note only that, if the user has pip installed PySpark but is directly calling pyspark-shell or
  # spark-submit in another directory we want to use that version of PySpark rather than the
  # pip installed version of PySpark.
  export SPARK_HOME="$(cd "$(dirname "$0")"/..; pwd)"
else
  # We are pip installed, use the Python script to resolve a reasonable SPARK_HOME
  # Default to standard python interpreter unless told otherwise
  if [[ -z "$PYSPARK_DRIVER_PYTHON" ]]; then
     PYSPARK_DRIVER_PYTHON="${PYSPARK_PYTHON:-"python"}"
  fi
  export SPARK_HOME=$($PYSPARK_DRIVER_PYTHON "$FIND_SPARK_HOME_PYTHON_SCRIPT")
fi

可以看到，如果事先用戶沒有設定SPARK_HOME的值，這里程序也會自動設置並且將其注冊為環境變量，供后面程序使用

當SPARK_HOME的值設定完成之后，就會執行Spark-class文件，這也是我們分析的重要部分，源碼如下：

3.3　spark-class

#!/usr/bin/env bash
#依舊是檢查設置SPARK_HOME的值
if [ -z "${SPARK_HOME}" ]; then
  source "$(dirname "$0")"/find-spark-home
fi
#執行load-spark-env.sh腳本文件，主要目的在於加載設定一些變量值
#設定spark-env.sh中的變量值到環境變量中，供后續使用
#設定scala版本變量值
. "${SPARK_HOME}"/bin/load-spark-env.sh

# Find the java binary
#檢查設定java環境值
#-n代表檢測變量長度是否為0，不為0時候為真
#如果已經安裝Java沒有設置JAVA_HOME,command -v java返回的值為${JAVA_HOME}/bin/java
if [ -n "${JAVA_HOME}" ]; then
  RUNNER="${JAVA_HOME}/bin/java"
else
  if [ "$(command -v java)" ]; then
    RUNNER="java"
  else
    echo "JAVA_HOME is not set" >&2
    exit 1
  fi
fi

# Find Spark jars.
#-d檢測文件是否為目錄，若為目錄則為真
#設置一些關聯Class文件
if [ -d "${SPARK_HOME}/jars" ]; then
  SPARK_JARS_DIR="${SPARK_HOME}/jars"
else
  SPARK_JARS_DIR="${SPARK_HOME}/assembly/target/scala-$SPARK_SCALA_VERSION/jars"
fi

if [ ! -d "$SPARK_JARS_DIR" ] && [ -z "$SPARK_TESTING$SPARK_SQL_TESTING" ]; then
  echo "Failed to find Spark jars directory ($SPARK_JARS_DIR)." 1>&2
  echo "You need to build Spark with the target \"package\" before running this program." 1>&2
  exit 1
else
  LAUNCH_CLASSPATH="$SPARK_JARS_DIR/*"
fi

# Add the launcher build dir to the classpath if requested.
if [ -n "$SPARK_PREPEND_CLASSES" ]; then
  LAUNCH_CLASSPATH="${SPARK_HOME}/launcher/target/scala-$SPARK_SCALA_VERSION/classes:$LAUNCH_CLASSPATH"
fi

# For tests
if [[ -n "$SPARK_TESTING" ]]; then
  unset YARN_CONF_DIR
  unset HADOOP_CONF_DIR
fi

# The launcher library will print arguments separated by a NULL character, to allow arguments with
# characters that would be otherwise interpreted by the shell. Read that in a while loop, populating
# an array that will be used to exec the final command.
#
# The exit code of the launcher is appended to the output, so the parent shell removes it from the
# command array and checks the value to see if the launcher succeeded.
#執行類文件org.apache.spark.launcher.Main，返回解析后的參數
build_command() {
  "$RUNNER" -Xmx128m -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$@"
  printf "%d\0" $?
}

# Turn off posix mode since it does not allow process substitution
#將build_command方法解析后的參數賦給CMD
set +o posix
CMD=()
while IFS= read -d '' -r ARG; do
  CMD+=("$ARG")
done < <(build_command "$@")

COUNT=${#CMD[@]}
LAST=$((COUNT - 1))
LAUNCHER_EXIT_CODE=${CMD[$LAST]}

# Certain JVM failures result in errors being printed to stdout (instead of stderr), which causes
# the code that parses the output of the launcher to get confused. In those cases, check if the
# exit code is an integer, and if it's not, handle it as a special error case.
if ! [[ $LAUNCHER_EXIT_CODE =~ ^[0-9]+$ ]]; then
  echo "${CMD[@]}" | head -n-1 1>&2
  exit 1
fi

if [ $LAUNCHER_EXIT_CODE != 0 ]; then
  exit $LAUNCHER_EXIT_CODE
fi

CMD=("${CMD[@]:0:$LAST}")
#執行CMD中的某個參數類org.apache.spark.deploy.SparkSubmit
exec "${CMD[@]}"

spark-class文件的執行邏輯稍顯復雜，總體上應該是這樣的：

檢查SPARK_HOME的值----》執行load-spark-env.sh文件，設定一些需要用到的環境變量，如scala環境值，這其中也加載了spark-env.sh文件-------》檢查設定java的執行路徑變量值-------》尋找spark jars,設定一些引用相關類的位置變量------》執行類文件org.apache.spark.launcher.Main，返回解析后的參數給CMD-------》判斷解析參數是否正確（代表了用戶設置的參數是否正確）--------》正確的話執行org.apache.spark.deploy.SparkSubmit這個類

3.4　SparkSubmit 

2.1最后提交語句，D:\src\spark-2.3.0\core\src\main\scala\org\apache\spark\deploy\SparkSubmit.scala

exec "${SPARK_HOME}"/bin/spark-class org.apache.spark.deploy.SparkSubmit "$@"

 

override def main(args: Array[String]): Unit = {
    // Initialize logging if it hasn't been done yet. Keep track of whether logging needs to
    // be reset before the application starts.
    val uninitLog = initializeLogIfNecessary(true, silent = true)
    //拿到submit腳本傳入的參數
    val appArgs = new SparkSubmitArguments(args)
    if (appArgs.verbose) {
      // scalastyle:off println
      printStream.println(appArgs)
      // scalastyle:on println
    }
    //根據傳入的參數匹配對應的執行方法
    appArgs.action match {
        //根據傳入的參數提交命令
      case SparkSubmitAction.SUBMIT => submit(appArgs, uninitLog)
        //只有standalone和mesos集群模式才觸發
      case SparkSubmitAction.KILL => kill(appArgs)
      //只有standalone和mesos集群模式才觸發
      case SparkSubmitAction.REQUEST_STATUS => requestStatus(appArgs)
    }
  }

3.4.1　submit十分關鍵，主要分為兩步驟

（1）調用prepareSubmitEnvironment

（2）調用doRunMain