Spark源码分析之Spark-submit和Spark-class
有了前面spark-shell的经验，看这两个脚本就容易多啦。前面总结的Spark-shell的分析可以参考：
Spark-submit
if [ -z "${SPARK_HOME}" ]; then
export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi
# disable randomized hash for string in Python 3.3+
export PYTHONHASHSEED=0
exec "${SPARK_HOME}"/bin/spark-class org.apache.spark.deploy.SparkSubmit "$@"
跟Spark-shell一样，先检查是否设置了${SPARK_HOME},然后启动spark-class，并传递了org.apache.spark.deploy.SparkSubmit作为第一个参数，然后把前面Spark-shell的参数都传给spark-class
Spark-class
if [ -z "${SPARK_HOME}" ]; then
export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi
. "${SPARK_HOME}"/bin/load-spark-env.sh
# Find the java binary
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 assembly jar
SPARK_ASSEMBLY_JAR=
if [ -f "${SPARK_HOME}/RELEASE" ]; then
ASSEMBLY_DIR="${SPARK_HOME}/lib"
else
ASSEMBLY_DIR="${SPARK_HOME}/assembly/target/scala-$SPARK_SCALA_VERSION"
fi
GREP_OPTIONS=
num_jars="$(ls -1 "$ASSEMBLY_DIR" | grep "^spark-assembly.*hadoop.*\.jar$" | wc -l)"
if [ "$num_jars" -eq "0" -a -z "$SPARK_ASSEMBLY_JAR" -a "$SPARK_PREPEND_CLASSES" != "1" ]; then
echo "Failed to find Spark assembly in $ASSEMBLY_DIR." 1>&2
echo "You need to build Spark before running this program." 1>&2
exit 1
fi
if [ -d "$ASSEMBLY_DIR" ]; then
ASSEMBLY_JARS="$(ls -1 "$ASSEMBLY_DIR" | grep "^spark-assembly.*hadoop.*\.jar$" || true)"
if [ "$num_jars" -gt "1" ]; then
echo "Found multiple Spark assembly jars in $ASSEMBLY_DIR:" 1>&2
echo "$ASSEMBLY_JARS" 1>&2
echo "Please remove all but one jar." 1>&2
exit 1
fi
fi
SPARK_ASSEMBLY_JAR="${ASSEMBLY_DIR}/${ASSEMBLY_JARS}"
LAUNCH_CLASSPATH="$SPARK_ASSEMBLY_JAR"
# Add the launcher build dir to the classpath if requested.
if [ -n "$SPARK_PREPEND_CLASSES" ]; then
LAUNCH_CLASSPATH="${SPARK_HOME}/launcher/target/scala-$SPARK_SCALA_VERSION/classes:$LAUNCH_CLASSPATH"
fi
export _SPARK_ASSEMBLY="$SPARK_ASSEMBLY_JAR"
# For tests
if [[ -n "$SPARK_TESTING" ]]; then
unset YARN_CONF_DIR
unset HADOOP_CONF_DIR
fi
# The launcher library will print arguments separated by a NULL character, to allow arguments with
# characters that would be otherwise interpreted by the shell. Read that in a while loop, populating
# an array that will be used to exec the final command.
CMD=()
while IFS= read -d '' -r ARG; do
CMD+=("$ARG")
done < <("$RUNNER" -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$@")
exec "${CMD[@]}"
这个类是真正的执行者,我们好好看看这个真正的入口在哪里？
首先，依然是设置项目主目录：
if [ -z "${SPARK_HOME}" ]; then
export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi
然后，配置一些环境变量:
. "${SPARK_HOME}"/bin/load-spark-env.sh
在spark-env中设置了assembly相关的信息。
然后寻找java,并赋值给RUNNER变量
# Find the java binary
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
中间是一大坨跟assembly相关的内容。
最关键的就是下面这句了：
CMD=()
while IFS= read -d '' -r ARG; do
CMD+=("$ARG")
done < <("$RUNNER" -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$@")
exec "${CMD[@]}"
首先循环读取ARG参数，加入到CMD中。然后执行了"$RUNNER" -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$@ 这个是真正执行的第一个spark的类。
该类在launcher模块下，简单的浏览下代码：
public static void main(String[] argsArray) throws Exception {
...
List<String> args = new ArrayList<String>(Arrays.asList(argsArray));
String className = args.remove(0);
...
//创建命令解析器
AbstractCommandBuilder builder;
if (className.equals("org.apache.spark.deploy.SparkSubmit")) {
try {
builder = new SparkSubmitCommandBuilder(args);
} catch (IllegalArgumentException e) {
...
}
} else {
builder = new SparkClassCommandBuilder(className, args);
}
List<String> cmd = builder.buildCommand(env);//解析器解析参数
...
//返回有效的参数
if (isWindows()) {
System.out.println(prepareWindowsCommand(cmd, env));
} else {
List<String> bashCmd = prepareBashCommand(cmd, env);
for (String c : bashCmd) {
System.out.print(c);
System.out.print('\0');
}
}
}
launcher.Main返回的数据存储到CMD中。
然后执行命令:
exec "${CMD[@]}"
这里开始真正执行某个Spark的类。
最后来说说这个exec命令，想要理解它跟着其他几个命令一起学习：
source命令，在执行脚本的时候，会在当前的shell中直接把source执行的脚本给挪到自己的shell中执行。换句话说，就是把目标脚本的任务拿过来自己执行。exec命令，是创建一个新的进程，只不过这个进程与前一个进程的ID是一样的。这样，原来的脚本剩余的部分就不能执行了，因为相当于换了一个进程。另外，创建新进程并不是说把所有的东西都直接复制，而是采用写时复制，即在新进程使用到某些内容时，才拷贝这些内容sh命令则是开启一个新的shell执行，相当于创建一个新进程
举个简单的例子,下面有三个脚本:
xingoo-test-1.sh
exec -c sh /home/xinghl/test/xingoo-test-2.sh
xingoo-test-2.sh
while true
do
echo "a2"
sleep 3
done
xingoo-test-3.sh
sh /home/xinghl/test/xingoo-test-2.sh
xingoo-test-4.sh
source /home/xinghl/test/xingoo-test-2.sh
在执行xingoo-test-1.sh和xingoo-test-4.sh的效果是一样的，都只有一个进程。
在执行xingoo-test-3.sh的时候会出现两个进程。
