将Protobuf数据从Flink转发到Kafka和stdout可以通过以下步骤实现:
下面是一个示例代码:
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.streaming.util.serialization.KeyedSerializationSchema;
import org.apache.flink.streaming.util.serialization.KeyedDeserializationSchema;
import org.apache.flink.streaming.util.serialization.SimpleStringSchema;
import org.apache.flink.streaming.api.functions.source.RichSourceFunction;
import org.apache.flink.streaming.api.functions.sink.RichSinkFunction;
import org.apache.flink.api.common.serialization.DeserializationSchema;
import org.apache.flink.api.common.serialization.SerializationSchema;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import java.util.Properties;
public class ProtobufFlinkKafkaExample {
public static void main(String[] args) throws Exception {
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// 设置Kafka相关配置
Properties properties = new Properties();
properties.setProperty("bootstrap.servers", "localhost:9092");
// 从Kafka读取Protobuf数据
FlinkKafkaConsumer<MyProtobufMessage> kafkaConsumer = new FlinkKafkaConsumer<>(
"input-topic",
new ProtobufDeserializationSchema<>(MyProtobufMessage.class),
properties
);
DataStream<MyProtobufMessage> dataStream = env.addSource(kafkaConsumer);
// 将Protobuf数据转发到Kafka
FlinkKafkaProducer<MyProtobufMessage> kafkaProducer = new FlinkKafkaProducer<>(
"output-topic",
new ProtobufSerializationSchema<>(MyProtobufMessage.class),
properties
);
dataStream.addSink(kafkaProducer);
// 将Protobuf数据打印到stdout
dataStream.addSink(new ProtobufPrintSinkFunction<>());
env.execute("Protobuf Flink Kafka Example");
}
// 自定义Protobuf的反序列化器
public static class ProtobufDeserializationSchema<T> implements DeserializationSchema<T> {
private final Class<T> clazz;
public ProtobufDeserializationSchema(Class<T> clazz) {
this.clazz = clazz;
}
@Override
public T deserialize(byte[] bytes) {
// 使用Protobuf的反序列化方法将字节数组转换为Protobuf对象
return ProtobufUtils.deserialize(bytes, clazz);
}
@Override
public boolean isEndOfStream(T t) {
return false;
}
@Override
public TypeInformation<T> getProducedType() {
return TypeInformation.of(clazz);
}
}
// 自定义Protobuf的序列化器
public static class ProtobufSerializationSchema<T> implements SerializationSchema<T> {
private final Class<T> clazz;
public ProtobufSerializationSchema(Class<T> clazz) {
this.clazz = clazz;
}
@Override
public byte[] serialize(T t) {
// 使用Protobuf的序列化方法将Protobuf对象转换为字节数组
return ProtobufUtils.serialize(t);
}
}
// 自定义打印Sink函数
public static class ProtobufPrintSinkFunction<T> extends RichSinkFunction<T> {
@Override
public void invoke(T value) {
System.out.println(value.toString());
}
}
}
在上面的示例代码中,你需要替换以下内容:
这样,你就可以将Protobuf数据从Flink转发到Kafka和stdout了。在实际使用中,你可以根据自己的需求进行修改和扩展。
领取专属 10元无门槛券
手把手带您无忧上云