flink的per-job模式自定义脚本

#!/bin/bash

# 参数说明
if [ $# == 1 ] || [ "$1" == "-h" ]; then
  echo "*****************************"
  echo "* 参数说明:                 *"
  echo "*  -cn <class_name>         *"
  echo "*  -jp <jar_path>           *"
  echo "*  [-q <queue>]             *"
  echo "*  [-pa <parallelism>]      *"
  echo "*  [-jm <jobmanager>]       *"
  echo "*  [-tm <taskmanager>]      *"
  echo "*  [-ts <slots>]            *"
  echo "*  [-u <udf>]               *"
  echo "*****************************"
  exit 0
fi
# 默认配置
flink_home=$(whereis bin/flink | cut -d ' ' -f 2-)
class_name=""
jar_path=""
application_name="flink"
queue="root.users.root"
parallelism_default=4
jobmanager_memory="2048mb"
taskmanager_memory="4056mb"
taskmanager_slots=2
env_java_opts="-Dfile.encoding=UTF-8"

# 遍历所有参数进行匹配
while [[ "$#" -gt 0 ]]; do
 case $1 in
    -cn|--class_name)
      class_name=$2
      shift ;;
    -jp|--jar_path)
      jar_path=$2
      shift ;;
    -q|--queue) 
      queue=$2
      shift ;;
    -pa|--parallelism) 
      parallelism_default=$2
      shift ;;
    -jm|--jobmanager)
      jobmanager_memory=$2
      shift ;;
    -tm|--taskmanager)
      taskmanager_memory=$2
      shift ;;
    -ts|--slots)
      taskmanager_slots=$2
      shift ;;
    -u|-U|--UTF|--udf)
      env_java_opts=$2
      shift ;;
  esac
  shift
done

# Flink参数设置
flink_command="$flink_home run -t yarn-per-job -Dyarn.application.name=${class_name##*.} -Dyarn.application.queue=$queue -Dparallelism.default=$parallelism_default -Djobmanager.memory.process.size=$jobmanager_memory -Dtaskmanager.memory.process.size=$taskmanager_memory -Dtaskmanager.numberOfTaskSlots=$taskmanager_slots -Denv.java.opts=$env_java_opts -c $class_name $jar_path"
# 检查必要参数是否存在
if [ -z "$class_name" ] || [ -z "$jar_path" ]; then
  echo "*****************************************************"
  echo "* 传参错误：                                        *"
  echo "*                                                   *"
  echo "* 请传入必要的全类名[-cn ]和jar包路径[-jp ]作为参数 *"
  echo "*****************************************************"
  exit 1
fi

# 启动Flink的per-job模式
echo "export HADOOP_CLASSPATH=\`hadoop classpath\`"
eval "$flink_command"