如何正确设置参数

很多人在应用flink DataStream 或者是Flinksql 的时候对于一些参数设置知道的不是很清晰，本文带领大家彻底搞定这一块。

1. 在flink的配置文件中设置，这个就不多说了，缺点就是不够灵活
2. 在代码层面设置

flink Table模式下的参数

public class SingleTableMain {
public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        StreamTableEnvironment  tEnv = StreamTableEnvironment.create(env);
 }

    public static void setStateBackendAndCheckpoint(StreamExecutionEnvironment env, String checkpointPath) {
        env.setStateBackend(new EmbeddedRocksDBStateBackend(true));   // 设置状态后端
        //每30秒启动一个检查点
        env.enableCheckpointing(60000);
        //允許几次檢查點失敗
        env.getCheckpointConfig().setTolerableCheckpointFailureNumber(3);

        // 设置状态后端
        env.setStateBackend(new EmbeddedRocksDBStateBackend(true));

        env.getCheckpointConfig().setCheckpointStorage(new FileSystemCheckpointStorage(checkpointPath));

        //检查点保存模式
        env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);

        //设置最小间隔
        env.getCheckpointConfig().setMinPauseBetweenCheckpoints(TimeUnit.MINUTES.toMillis(2));

        //设置超时时长
        env.getCheckpointConfig().setCheckpointTimeout(TimeUnit.MINUTES.toMillis(5));

        // 最大并发检查点数量,如果上面设置了 最小间隔，其实这个参数已经不起作用了
        env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);

        //可恢复
        env.getCheckpointConfig().setExternalizedCheckpointCleanup(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);

        //重试机制
        env.setRestartStrategy(RestartStrategies.fixedDelayRestart(3, org.apache.flink.api.common.time.Time.of(30, TimeUnit.SECONDS)));
    }


    public static void enableMiniBatch(StreamTableEnvironment tEnv, Duration duration, Long size) {
        //The maximum number of input records can
        // be buffered for MiniBatch.
        // MiniBatch is an optimization to buffer input records to reduce state access.
        // MiniBatch is triggered with the allowed latency interval and when the maximum number of buffered records reached.
        // NOTE: MiniBatch only works for non-windowed aggregations currently.
        // If table.exec.mini-batch.enabled is set true, its value must be positive.
        Configuration configuration = new Configuration();
        configuration.set(ExecutionConfigOptions.TABLE_EXEC_MINIBATCH_ENABLED, true);
        configuration.set(ExecutionConfigOptions.TABLE_EXEC_MINIBATCH_ALLOW_LATENCY, duration);
        configuration.set(ExecutionConfigOptions.TABLE_EXEC_MINIBATCH_SIZE, size);
        tEnv.getConfig().addConfiguration(configuration);

    }

    public static void setTTL(StreamTableEnvironment tEnv, Duration duration) {
        Configuration configuration = new Configuration();
        configuration.set(ExecutionConfigOptions.IDLE_STATE_RETENTION, duration);
        tEnv.getConfig().addConfiguration(configuration);
    }

    public static void enableSqlOptimizer(StreamTableEnvironment tEnv) {
        Configuration configuration = new Configuration();
        // 设置两阶段聚合
        configuration.set(OptimizerConfigOptions.TABLE_OPTIMIZER_AGG_PHASE_STRATEGY, "TWO_PHASE");
        //开启 Split Distinct
        configuration.set(OptimizerConfigOptions.TABLE_OPTIMIZER_DISTINCT_AGG_SPLIT_ENABLED, true);
        configuration.set(OptimizerConfigOptions.TABLE_OPTIMIZER_DISTINCT_AGG_SPLIT_BUCKET_NUM, 2048);
        tEnv.getConfig().addConfiguration(configuration);
    }

    public static void setIdleTimeout(StreamTableEnvironment tEnv, Duration duration) {
        Configuration configuration = new Configuration();
        configuration.set(ExecutionConfigOptions.TABLE_EXEC_SOURCE_IDLE_TIMEOUT, duration);
        tEnv.getConfig().addConfiguration(configuration);
    }

    public static void setJobName(StreamTableEnvironment tEnv, String jobName) {
        Configuration configuration = new Configuration();
        configuration.set(PipelineOptions.NAME, jobName);
        tEnv.getConfig().addConfiguration(configuration);
    }

    public static void enableDynamicParam(StreamTableEnvironment tEnv){
        Configuration configuration = new Configuration();
        configuration.set(TableConfigOptions.TABLE_DYNAMIC_TABLE_OPTIONS_ENABLED,true);
        tEnv.getConfig().addConfiguration(configuration);
        logger.info("[SqlUntil] 开启动态table参数");

    }


}       

Table 模式下参数类相关

上面的代码对应下方的内部类，正好对应Table SQL模式下的：执行参数，优化参数，表参数

DataStream 模式下怎么设置参数？

        Configuration configuration = new Configuration();
        configuration.set(CheckpointingOptions.CHECKPOINTS_DIRECTORY,"hdfs://xxx:8020/remote-default-checkpoints/penggan/");
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(configuration);

上面这种只是举了个例子，感兴趣的请看下图：

总结

上面是最为原始的设置参数的方式，支持的参数对应的其实就是：flink官网核心参数
flink tablesql 参数

所谓的参数就是控制程序的执行行为的， 参数分为

1. 动态传参（启动程序在cmd传入）
2. 程序代码设置
3. 读取默认配置文件（flink-conf.yml）
   上文讲的是代码设置， 其实参数底层解析的就是截图中的类， 可以看到根据参数的行为flink内部用不通的类去解析，这些类我们也可以直接拿来修改参数， 这就是本文的意义。