目录

一：启动脚本解析

二：源码解析

入口

2.execute()核心方法

1.其中 BaseSource、BaseTransform、BaseSink都是接口、都实现Plugin接口。他们的实现类就是对应的插件类型

2.execute()方法向下走，创建一个执行环境。

3. 调用plugin.prepare(env)

4.最后启动 execution.start(sources, transforms, sinks);

5.执行flink 代码程序

6.最后关闭

转载请标明出处：SeaTunnel2.1.1源码解析_Adobee Chen的博客-CSDN博客

一：启动脚本解析

在 /bin/start-seatunnel-flink.sh 

#!/bin/bash

function usage() {
  echo "Usage: start-seatunnel-flink.sh [options]"
  echo "  options:"
  echo "    --config, -c FILE_PATH        Config file"
  echo "    --variable, -i PROP=VALUE     Variable substitution, such as -i city=beijing, or -i date=20190318"
  echo "    --check, -t                   Check config"
  echo "    --help, -h                    Show this help message"
}

if [[ "$@" = *--help ]] || [[ "$@" = *-h ]] || [[ $# -le 1 ]]; then
  usage
  exit 0
fi

is_exist() {
    if [ -z $1 ]; then
      usage
      exit -1
    fi
}

PARAMS=""
while (( "$#" )); do
  case "$1" in
    -c|--config)
      CONFIG_FILE=$2
      is_exist ${CONFIG_FILE}
      shift 2
      ;;

    -i|--variable)
      variable=$2
      is_exist ${variable}
      java_property_value="-D${variable}"
      variables_substitution="${java_property_value} ${variables_substitution}"
      shift 2
      ;;

    *) # preserve positional arguments
      PARAMS="$PARAMS $1"
      shift
      ;;

  esac
done

if [ -z ${CONFIG_FILE} ]; then
  echo "Error: The following option is required: [-c | --config]"
  usage
  exit -1
fi

# set positional arguments in their proper place
eval set -- "$PARAMS"

BIN_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
APP_DIR=$(dirname ${BIN_DIR})
CONF_DIR=${APP_DIR}/config
PLUGINS_DIR=${APP_DIR}/lib
DEFAULT_CONFIG=${CONF_DIR}/application.conf
CONFIG_FILE=${CONFIG_FILE:-$DEFAULT_CONFIG}

assemblyJarName=$(find ${PLUGINS_DIR} -name seatunnel-core-flink*.jar)

if [ -f "${CONF_DIR}/seatunnel-env.sh" ]; then
    source ${CONF_DIR}/seatunnel-env.sh
fi

string_trim() {
    echo $1 | awk '{$1=$1;print}'
}

export JVM_ARGS=$(string_trim "${variables_substitution}")


exec ${FLINK_HOME}/bin/flink run 
    ${PARAMS} 
    -c org.apache.seatunnel.SeatunnelFlink 
    ${assemblyJarName} --config ${CONFIG_FILE}

 其中: 启动脚本能接收的 --config --variable --check(还不支持)  --help 

只要不是 config、variable参数就放到PARAMS参数里，最后执行flink 执行命令，PARAMS当作flink参数执行。

org.apache.seatunnel.SeatunnelFlink 这个类就是主入口

二：源码解析

1. 入口

public class SeatunnelFlink {

    public static void main(String[] args) throws Exception {
        FlinkCommandArgs flinkArgs = CommandLineUtils.parseFlinkArgs(args);
        Seatunnel.run(flinkArgs);
    }

}

FlinkCommandArgs中进行命令行参数解析

    public static FlinkCommandArgs parseFlinkArgs(String[] args) {
        FlinkCommandArgs flinkCommandArgs = new FlinkCommandArgs();
        JCommander.newBuilder()
            .addObject(flinkCommandArgs)
            .build()
            .parse(args);
        return flinkCommandArgs;
    }

进入到Seatunnel.run(flinkArgs);

    public static  void run(T commandArgs) {

        if (!Common.setDeployMode(commandArgs.getDeployMode().getName())) {
            throw new IllegalArgumentException(
                String.format("Deploy mode: %s is Illegal", commandArgs.getDeployMode()));
        }

        try {
            Command command = CommandFactory.createCommand(commandArgs);
            command.execute(commandArgs);
        } catch (ConfigRuntimeException e) {
            showConfigError(e);
            throw e;
        } catch (Exception e) {
            showFatalError(e);
            throw e;
        }
    }

进入到CommandFactory.createCommand(commandArgs);，根据不同的类型选择Command，我们看的是flinkCommand。

    public static  Command createCommand(T commandArgs) {
        switch (commandArgs.getEngineType()) {
            case FLINK:
                return (Command) new FlinkCommandBuilder().buildCommand((FlinkCommandArgs) commandArgs);
            case SPARK:
                return (Command) new SparkCommandBuilder().buildCommand((SparkCommandArgs) commandArgs);
            default:
                throw new RuntimeException(String.format("engine type: %s is not supported", commandArgs.getEngineType()));
        }
    }

进入到 buildCommand，根据是否检查config进入到不同的实现类

    public Command buildCommand(FlinkCommandArgs commandArgs) {
        return commandArgs.isCheckConfig() ? new FlinkConfValidateCommand() : new FlinkTaskExecuteCommand();
    }

FlinkConfValidateCommand和FlinkTaskExecuteCommand两个类都实现了Command类。并且都只有一个execute()方法

public class FlinkConfValidateCommand implements Command
public class FlinkTaskExecuteCommand extends BaseTaskExecuteCommand

在SeaTunnel.run(flinkArgs)进入  command.execute(commandArgs);

我们先看FlinkTaskExecuteCommand 类中的execute方法

2.execute()核心方法

 public void execute(FlinkCommandArgs flinkCommandArgs) {
        //flink
        EngineType engine = flinkCommandArgs.getEngineType();
        // --config
        String configFile = flinkCommandArgs.getConfigFile();
        //将String变成Config类
        Config config = new ConfigBuilder<>(configFile, engine).getConfig();
        //解析执行上下文
        ExecutionContext executionContext = new ExecutionContext<>(config, engine);
        //解析 sources模块
        List> sources = executionContext.getSources();
        //解析 tansform模块
        List> transforms = executionContext.getTransforms();
        //解析 sink模块
        List> sinks = executionContext.getSinks();

        baseCheckConfig(sinks, transforms, sinks);
        showAsciiLogo();

        try (Execution,
                BaseTransform,
                BaseSink,
                FlinkEnvironment> execution = new ExecutionFactory<>(executionContext).createExecution()) {
            //准备
            prepare(executionContext.getEnvironment(), sources, transforms, sinks);
            //启动
            execution.start(sources, transforms, sinks);
            //关闭
            close(sources, transforms, sinks);
        } catch (Exception e) {
            throw new RuntimeException("Execute Flink task error", e);
        }
    }

1.其中 BaseSource、BaseTransform、BaseSink都是接口、都实现Plugin接口。他们的实现类就是对应的插件类型

 如果我们的source、sink是kafka的话那么对应的就是source就是KafkaTableStream、Sink就是KafkaSink

2.execute()方法向下走，创建一个执行环境。

 进入ExecutionFactory种的createExecution()

    public Execution, BaseTransform, BaseSink, ENVIRONMENT> createExecution() {
        Execution execution = null;
        switch (executionContext.getEngine()) {
            case SPARK:
                SparkEnvironment sparkEnvironment = (SparkEnvironment) executionContext.getEnvironment();
                switch (executionContext.getJobMode()) {
                    case STREAMING:
                        execution = new SparkStreamingExecution(sparkEnvironment);
                        break;
                    case STRUCTURED_STREAMING:
                        execution = new StructuredStreamingExecution(sparkEnvironment);
                        break;
                    default:
                        execution = new SparkBatchExecution(sparkEnvironment);
                }
                break;
            case FLINK:
                FlinkEnvironment flinkEnvironment = (FlinkEnvironment) executionContext.getEnvironment();
                switch (executionContext.getJobMode()) {
                    case STREAMING:
                        execution = new FlinkStreamExecution(flinkEnvironment);
                        break;
                    default:
                        execution = new FlinkBatchExecution(flinkEnvironment);
                }
                break;
            default:
                throw new IllegalArgumentException("No suitable engine");
        }
        LOGGER.info("current execution is [{}]", execution.getClass().getName());
        return (Execution, BaseTransform, BaseSink, ENVIRONMENT>) execution;
    }

进入到FlinkStreamExecution中，可以看到最终是创建flink 执行环境。

    private final FlinkEnvironment flinkEnvironment;

    public FlinkStreamExecution(FlinkEnvironment streamEnvironment) {
        this.flinkEnvironment = streamEnvironment;
    }

3. 调用plugin.prepare(env)

    protected final void prepare(E env, List>... plugins) {
        for (List> pluginList : plugins) {
            pluginList.forEach(plugin -> plugin.prepare(env));
        }
    }

例如kafka->kafka

KafkaTableStream  prepare

    public void prepare(FlinkEnvironment env) {
        topic = config.getString(TOPICS);
        PropertiesUtil.setProperties(config, kafkaParams, consumerPrefix, false);
        tableName = config.getString(RESULT_TABLE_NAME);
        if (config.hasPath(ROWTIME_FIELD)) {
            rowTimeField = config.getString(ROWTIME_FIELD);
            if (config.hasPath(WATERMARK_VAL)) {
                watermark = config.getLong(WATERMARK_VAL);
            }
        }
        String schemaContent = config.getString(SCHEMA);
        format = FormatType.from(config.getString(SOURCE_FORMAT).trim().toLowerCase());
        schemaInfo = JSONObject.parse(schemaContent, Feature.OrderedField);
    }

KafkaSink prepare

    public void prepare(FlinkEnvironment env) {
        topic = config.getString("topics");
        if (config.hasPath("semantic")) {
            semantic = config.getString("semantic");
        }
        String producerPrefix = "producer.";
        PropertiesUtil.setProperties(config, kafkaParams, producerPrefix, false);
        kafkaParams.put("key.serializer", "org.apache.kafka.common.serialization.ByteArraySerializer");
        kafkaParams.put("value.serializer", "org.apache.kafka.common.serialization.ByteArraySerializer");
    }

4.最后启动 execution.start(sources, transforms, sinks);

通过步骤2.已经知道execution是根据不同引擎创建不同的执行环境，kafka是FlinkStreamExecution。那么就在FlinkStreamExecution中找到start()方法

5.执行flink 代码程序

其中sorce.getDate在KafkaTableStream中的getDate方法,sink在KafkaSink中的outputStream方法

  public void start(List sources, List transforms, List sinks) throws Exception {
        List> data = new ArrayList<>();

        for (FlinkStreamSource source : sources) {
            DataStream dataStream = source.getData(flinkEnvironment);
            data.add(dataStream);
            registerResultTable(source, dataStream);
        }

        DataStream input = data.get(0);

        for (FlinkStreamTransform transform : transforms) {
            DataStream stream = fromSourceTable(transform.getConfig()).orElse(input);
            input = transform.processStream(flinkEnvironment, stream);
            registerResultTable(transform, input);
            transform.registerFunction(flinkEnvironment);
        }

        for (FlinkStreamSink sink : sinks) {
            DataStream stream = fromSourceTable(sink.getConfig()).orElse(input);
            sink.outputStream(flinkEnvironment, stream);
        }
        try {
            LOGGER.info("Flink Execution Plan:{}", flinkEnvironment.getStreamExecutionEnvironment().getExecutionPlan());
            flinkEnvironment.getStreamExecutionEnvironment().execute(flinkEnvironment.getJobName());
        } catch (Exception e) {
            LOGGER.warn("Flink with job name [{}] execute failed", flinkEnvironment.getJobName());
            throw e;
        }
    }

6.最后关闭

    protected final void close(List>... plugins) {
        PluginClosedException exceptionHolder = null;
        for (List> pluginList : plugins) {
            for (Plugin plugin : pluginList) {
                try (Plugin closed = plugin) {
                    // ignore
                } catch (Exception e) {
                    exceptionHolder = exceptionHolder == null ?
                            new PluginClosedException("below plugins closed error:") : exceptionHolder;
                    exceptionHolder.addSuppressed(new PluginClosedException(
                            String.format("plugin %s closed error", plugin.getClass()), e));
                }
            }
        }
        if (exceptionHolder != null) {
            throw exceptionHolder;
        }
    }