从 Kafka 读取

package com.atguigu.source;

import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.connector.file.src.FileSource;
import org.apache.flink.connector.file.src.reader.TextLineInputFormat;
import org.apache.flink.connector.kafka.source.KafkaSource;
import org.apache.flink.connector.kafka.source.enumerator.initializer.OffsetsInitializer;
import org.apache.flink.core.fs.Path;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

import java.time.Duration;

public class KafkaSourceDemo {
    public static void main(String[] args) throws Exception {

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);

        KafkaSource<String> kafkaSource = KafkaSource.<String>builder()
                .setBootstrapServers("192.168.1.6:9092") // 指定kafka节点的地址和端口
                .setGroupId("group-chenhao")  // 指定消费者组的id
                .setTopics("my-topic")   // 指定消费的 Topic
                .setValueOnlyDeserializer(new SimpleStringSchema()) // 指定 反序列化器，这个是反序列化value
                .setStartingOffsets(OffsetsInitializer.latest())  // flink消费kafka的策略
                .build();

        env
//                .fromSource(kafkaSource, WatermarkStrategy.noWatermarks(), "kafkasource")
                .fromSource(kafkaSource, WatermarkStrategy.forBoundedOutOfOrderness(Duration.ofSeconds(3)), "kafkasource")
                .print();

        env.execute();
    }
}
/**
 *   kafka消费者的参数：
 *      auto.reset.offsets
 *          earliest: 如果有offset，从offset继续消费; 如果没有offset，从 最早 消费
 *          latest  : 如果有offset，从offset继续消费; 如果没有offset，从 最新 消费
 *
 *   flink的kafkasource，offset消费策略：OffsetsInitializer，默认是 earliest
 *          earliest: 一定从 最早 消费
 *          latest  : 一定从 最新 消费
 *
 */