apache-kafka-streams

来源： https://stackoverflow.com/questions/62480113/how-to-get-partitionid-and-topicname-in-kafkastream-application

来源： https://stackoverflow.com/questions/55236378/can-i-set-kafka-stream-consumer-group-id

来源： https://stackoverflow.com/questions/55236378/can-i-set-kafka-stream-consumer-group-id

来源： https://stackoverflow.com/questions/63468179/the-kafka-stream-is-not-producing-message-to-dlq-topic-from-flat-map-values

来源： https://stackoverflow.com/questions/48251413/how-to-detect-which-side-of-a-ktable-join-has-triggered-an-update

来源： https://stackoverflow.com/questions/48251413/how-to-detect-which-side-of-a-ktable-join-has-triggered-an-update

来源： https://stackoverflow.com/questions/61337436/kafka-streams-window-store-keeping-data-for-much-longer-then-retention-period

问题 We are building an application to get data from sensors. The data is streamed to Kafka from where consumers will publish it to different data stores. Each data point will have multiple attributes representing the state of the sensor. In one of the consumers we want to publish the data to the data store only if the value has changed. for e.g. if there is temperature sensor which is polled for data every 10 secs we expect to receive data like ----------------------------------------------------

问题 We are building an application to get data from sensors. The data is streamed to Kafka from where consumers will publish it to different data stores. Each data point will have multiple attributes representing the state of the sensor. In one of the consumers we want to publish the data to the data store only if the value has changed. for e.g. if there is temperature sensor which is polled for data every 10 secs we expect to receive data like ----------------------------------------------------

问题 I am working on Kafka Streams using Spring Cloud Stream. In the message processing application, there may be a chance that it will produce an error. So the message should not be commited and retried again. My application method - @Bean public Function<KStream<Object, String>, KStream<String, Long>> process() { return (input) -> { KStream<Object, String> kt = input.flatMapValues(v -> Arrays.asList(v.toUpperCase().split("\\W+"))); KGroupedStream<String, String> kgt =kt.map((k, v) -> new