Apache kafka 如何在Spring Cloud Kafka Streams应用程序中执行flatTransform?

Apache kafka 如何在Spring Cloud Kafka Streams应用程序中执行flatTransform?,apache-kafka,apache-kafka-streams,spring-kafka,spring-cloud-stream,spring-cloud-stream-binder-kafka,Apache Kafka,Apache Kafka Streams,Spring Kafka,Spring Cloud Stream,Spring Cloud Stream Binder Kafka,我正在尝试在Spring Cloud Kafka Streams应用程序中执行flatTransform。但我不确定将kafkastreamssstatestore注释放在哪里。目前我收到错误:拓扑无效:尚未添加StateStore activeInstruments。如果有人能给我一些指导,我将非常感激 @SpringBootApplication public class InstrumentsApp { public static void main(String[] args) {

我正在尝试在Spring Cloud Kafka Streams应用程序中执行
flatTransform
。但我不确定将
kafkastreamssstatestore
注释放在哪里。目前我收到错误:
拓扑无效:尚未添加StateStore activeInstruments
。如果有人能给我一些指导,我将非常感激

@SpringBootApplication
public class InstrumentsApp {

  public static void main(String[] args) {
    SpringApplication.run(InstrumentsApp.class, args);
  }

  public static class InstrumentsConsumer {

    @Bean
    public Serde<InstrumentsRes> instrumentsResSerde() {
      ObjectMapper mapper = new ObjectMapper(new MessagePackFactory());
      mapper.registerModule(new JavaTimeModule());
      mapper.configure(DeserializationFeature.READ_DATE_TIMESTAMPS_AS_NANOSECONDS, false);
      return new JsonSerde<>(InstrumentsRes.class, mapper);
    }

    @Bean
    public Serde<Instrument> instrumentSerde() {
      ObjectMapper mapper = new ObjectMapper(new MessagePackFactory());
      mapper.registerModule(new JavaTimeModule());
      mapper.configure(DeserializationFeature.READ_DATE_TIMESTAMPS_AS_NANOSECONDS, false);
      mapper.configure(SerializationFeature.WRITE_DATE_TIMESTAMPS_AS_NANOSECONDS, false);
      return new JsonSerde<>(Instrument.class, mapper);
    }

    @Bean
    @KafkaStreamsStateStore(name = "activeInstruments",
        type = KafkaStreamsStateStoreProperties.StoreType.KEYVALUE)
    public Consumer<KStream<String, InstrumentsRes>> process() {
      return instruments -> instruments.flatTransform(
          new TransformerSupplier<String, InstrumentsRes, Iterable<KeyValue<String, Instrument>>>() {
            public Transformer<String, InstrumentsRes, Iterable<KeyValue<String, Instrument>>> get() {
              return new Transformer<String, InstrumentsRes, Iterable<KeyValue<String, Instrument>>>() {

                private ProcessorContext context;
                private KeyValueStore<String, InstrumentsRes> state;

                @SuppressWarnings("unchecked")
                @Override
                public void init(ProcessorContext context) {
                  this.context = context;
                  this.state = (KeyValueStore<String, InstrumentsRes>) context
                      .getStateStore("activeInstruments");
                }

                @Override
                public Iterable<KeyValue<String, Instrument>> transform(String key,
                    InstrumentsRes value) {
                  List<KeyValue<String, Instrument>> result = new ArrayList<>();
                  for (Instrument instrument : value.result) {
                    result.add(KeyValue.pair(instrument.instrumentName, instrument));
                  }
                  InstrumentsRes prevValue = state.get(key);
                  if (prevValue != null) {
                    HashSet<String> prevInstrumentNames = value.getInstrumentNames();
                    HashSet<String> newInstrumentNames = value.getInstrumentNames();
                    prevInstrumentNames.removeAll(newInstrumentNames);
                    for (String instrumentName : prevInstrumentNames) {
                      result.add(KeyValue.pair(instrumentName, null));
                    }
                  }
                  state.put(key, value);
                  return result;
                }

                public void close() {
                }
              };
            }
          }, "activeInstruments");
    }

  }

}
@springboot应用程序
公共类工具{
公共静态void main(字符串[]args){
run(InstrumentsApp.class,args);
}
公共静态类工具使用者{
@豆子
公共Serde仪器资源数据库(){
ObjectMapper mapper=newObjectMapper(newMessagePackFactory());
registerModule(新的JavaTimeModule());
configure(反序列化功能。读取\u日期\u时间戳\u为\u纳秒,false);
返回新的JsonSerde(InstrumentsRes.class,mapper);
}
@豆子
公共Serde仪器Serde(){
ObjectMapper mapper=newObjectMapper(newMessagePackFactory());
registerModule(新的JavaTimeModule());
configure(反序列化功能。读取\u日期\u时间戳\u为\u纳秒,false);
configure(SerializationFeature.WRITE_DATE_TIMESTAMPS_为_纳秒,false);
返回新的JsonSerde(Instrument.class,mapper);
}
@豆子
@KafkaStreamsStateStore(name=“activeInstruments”,
type=KafkaStreamsStateStoreProperties.StoreType.KEYVALUE)
公共消费者过程(){
返回仪器->仪器.flatTransform(
新的变压器供应商(){
公共变压器get(){
返回新变压器(){
私有处理器上下文上下文;
私钥存储状态;
@抑制警告(“未选中”)
@凌驾
公共void init(ProcessorContext上下文){
this.context=上下文;
this.state=(KeyValueStore)上下文
.getStateStore(“activeInstruments”);
}
@凌驾
公共Iterable转换(字符串键,
仪表(S值){
列表结果=新建ArrayList();
用于(仪器:值。结果){
添加(KeyValue.pair(instrument.instrumentName,instrument));
}
InstrumentsRes prevValue=state.get(键);
if(prevValue!=null){
HashSet-prevInstrumentNames=value.getInstrumentNames();
HashSet newInstrumentNames=value.getInstrumentNames();
prevInstrumentNames.removeAll(newInstrumentNames);
对于(字符串instrumentName:PrevInstrumentName){
add(KeyValue.pair(instrumentName,null));
}
}
state.put(键、值);
返回结果;
}
公众假期结束(){
}
};
}
}“有效工具”);
}
}
}

为了回答我自己的问题,我认为
kafkastreamssstatestore
注释现在已被弃用:

现在我已经创建了一个类型为
StoreBuilder
的bean,正如注释中所建议的那样,一切都按照预期工作