flink学习-数据源-从kafka消费数据

目录

　　1 前置条件

　　　　1.1 需要软件

　　　　1.2 配置pom.xml

　　2 编写代码

 

　　3 运行

1 前置条件

1.1 需要软件

　　需要Kafka环境。

1.2 配置pom.xml

　　配置相关jar。

　　

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_2.12</artifactId><!-- 与Scala大版本号一致--> 
            <version>1.9.2</version><!-- 与Flink版本号一致--> 
        </dependency>

 

2 编写代码

 　　Java版本代码

　　　　

import java.util.Properties;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.streaming.util.serialization.SimpleStringSchema;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.util.Collector;
public class KafkaWordCount {
    private static final String READ_TOPIC = "student";
    public static void main(String[] args) throws Exception {
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        Properties props = new Properties();
        props.put("bootstrap.servers", "localhost:9092");
        props.put("zookeeper.connect", "localhost:2181");
        props.put("group.id", "student-group");
        props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.put("auto.offset.reset", "latest");
        DataStreamSource<String> student = env.addSource(new FlinkKafkaConsumer<>(
                READ_TOPIC,
                new SimpleStringSchema(),
                props)).setParallelism(1);
        DataStream<Tuple2<String, Integer>> counts = student.flatMap(new LineSplitter()).keyBy(0).sum(1);
        counts.print();
        env.execute("flink custom kafka");
    }
    public static final class LineSplitter implements FlatMapFunction<String, Tuple2<String, Integer>> {
        private static final long serialVersionUID = 1L;
        public void flatMap(String value, Collector<Tuple2<String, Integer>> out) {
            String[] tokens = value.toLowerCase().split("\\W+");
            for (String token : tokens) {
                if (token.length() > 0) {
                    out.collect(new Tuple2<String, Integer>(token, 1));
                }
            }
        }
    }
}

 

3 运行

　　1）运行结果