Flink源码篇【2】Flink提交流程之脚本运行过程解析和IDEA本地调试debug

1. Flink脚本运行过程解析

当我们通过命令/root/flink-1.15.0/bin/flink run /root/flink-1.15.0/examples/batch/WordCount.jar提交一个Flink的应用程序。看看Flink脚本的运行过程

这里我们直接给出Flink脚本的源码，然后在里面看各个变量的具体值，并给出说明

#!/usr/bin/env bash
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#  regarding copyright ownership.  The ASF licenses this file
#  to you under the Apache License, Version 2.0 (the
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#      http://www.apache.org/licenses/LICENSE-2.0
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# 获取Linux执行命令的第一个参数，即Flink脚本
# target=/root/flink-1.15.0/bin/flink
target="$0"
# For the case, the executable has been directly symlinked, figure out
# the correct bin path by following its symlink up to an upper bound.
# Note: we can't use the readlink utility here if we want to be POSIX
# compatible.
iteration=0
# 如果target是软链接，则查看软链接的详细信息，然后用正则表达式匹配出软链接指向的路径
# 如果软链接指向的路径还是一个软链接，则重复的一层层进行解析
# 如果解析超过一百次，则跳出循环。可能会导致后面运行config.sh脚本报找不到文件的错误
while [ -L "$target" ]; do
    if [ "$iteration" -gt 100 ]; then
        echo "Cannot resolve path: You have a cyclic symlink in $target."
        break
    fi
    ls=`ls -ld -- "$target"`
    target=`expr "$ls" : '.* -> \(.*\)$'`
    iteration=$((iteration + 1))
done

# 获取bin目录的路径
# bin=/root/flink-1.15.0/bin
# Convert relative path to absolute path
bin=`dirname "$target"`

# 运行config.sh脚本，这个脚本会设置很多变量，和定义了很多函数。我们可以在当前脚本引用
# get flink config
. "$bin"/config.sh

# 获取运行Flink脚本的Linux用户
# FLINK_IDENT_STRING=root
if [ "$FLINK_IDENT_STRING" = "" ]; then
        FLINK_IDENT_STRING="$USER"
fi

# 调用config.sh中的函数constructFlinkClassPath，获取Flink的classpath
# CC_CLASSPATH=/root/flink-1.15.0/lib/flink-cep-1.15.0.jar:/root/flink-1.15.0/lib/flink-connector-files-1.15.0.jar:......省略部分......:/root/flink-1.15.0/lib/flink-dist-1.15.0.jar
CC_CLASSPATH=`constructFlinkClassPath`

# 定义log文件，定义Java运行的日志参数
log=$FLINK_LOG_DIR/flink-$FLINK_IDENT_STRING-client-$HOSTNAME.log
log_setting=(-Dlog.file="$log" -Dlog4j.configuration=file:"$FLINK_CONF_DIR"/log4j-cli.properties -Dlog4j.configurationFile=file:"$FLINK_CONF_DIR"/log4j-cli.properties -Dlogback.configurationFile=file:"$FLINK_CONF_DIR"/logback.xml)

# Flink客户端指定的JVM参数，本示例为空字符串
# Add Client-specific JVM options
FLINK_ENV_JAVA_OPTS="${FLINK_ENV_JAVA_OPTS} ${FLINK_ENV_JAVA_OPTS_CLI}"

# -classpath设置了Flink的classpath和hadoop的classpath
# 执行的Java类是：org.apache.flink.client.cli.CliFrontend
# $@是Linux执行命令除一个参数，后面的所有参数
# $@=run /root/flink-1.15.0/examples/batch/WordCount.jar
# Add HADOOP_CLASSPATH to allow the usage of Hadoop file systems
exec "${JAVA_RUN}" $JVM_ARGS $FLINK_ENV_JAVA_OPTS "${log_setting[@]}" -classpath "`manglePathList "$CC_CLASSPATH:$INTERNAL_HADOOP_CLASSPATHS"`" org.apache.flink.client.cli.CliFrontend "$@"

可以看到最终执行的是Java类：org.apache.flink.client.cli.CliFrontend。我们下面接着看这个类

2. CliFrontend客户端入口类查看

在IDEA按下Ctrl + Shift + n，弹出文件搜索框，输入CliFrontend，就可以看到我们需要的CliFrontend.java类文件，点击跳转到CliFrontend.java

按下Ctrl + F12，弹出当前类CliFrontend的文件结构，找到main方法然后点击，就可以跳转到main方法

还可以按ctrl + h查看一个抽象方法的具体实现

main方法的代码如下：

    /** Submits the job based on the arguments. */
    public static void main(final String[] args) {
        EnvironmentInformation.logEnvironmentInfo(LOG, "Command Line Client", args);

        // 1. find the configuration directory
        final String configurationDirectory = getConfigurationDirectoryFromEnv();

        // 2. load the global configuration
        final Configuration configuration =
                GlobalConfiguration.loadConfiguration(configurationDirectory);

        // 3. load the custom command lines
        final List customCommandLines =
                loadCustomCommandLines(configuration, configurationDirectory);

        int retCode = 31;
        try {
            final CliFrontend cli = new CliFrontend(configuration, customCommandLines);

            SecurityUtils.install(new SecurityConfiguration(cli.configuration));
            retCode = SecurityUtils.getInstalledContext().runSecured(() -> cli.parseAndRun(args));
        } catch (Throwable t) {
            final Throwable strippedThrowable =
                    ExceptionUtils.stripException(t, UndeclaredThrowableException.class);
            LOG.error("Fatal error while running command line interface.", strippedThrowable);
            strippedThrowable.printStackTrace();
        } finally {
            System.exit(retCode);
        }
    }

3. 在IDEA本地运行CliFrontend程序

为了方便，我们会选择在IDEA本地调试Debug，运行CliFrontend需要进行配置

进行程序运行的Configuration设置，设置flink命令运行的自定义参数和环境变量就可以了。这里我们使用local的方式进行程序的运行，会在本地启动一个MiniCluster集群，application运行完成，集群关闭