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Question

这就是我想要做的：

我正在尝试在5分钟的时间范围内使用邮件，并计算收到的邮件数量。之后，我要复制到达组的最后一条消息，将其复制，编辑其字段“ count”以匹配时间片中的消息数，然后将其发送到主题。

但是，我在窗口部分有麻烦，需要帮助。我已经制作了自己的JSON Serdes（MessageSerde），并且Class Message表示JSON消息，但是我不确定现在应该如何处理窗口过程。

final StreamsBuilder builder = new StreamsBuilder();

    final KStream<String, Message> inputStream = 
    builder

    .stream("users", Consumed.with(Serdes.String(), MessageSerde));

    inputStream
    .filter(new Predicate<String, Message>() {
    @Override
    public boolean test(String s, Message s2) {
        return s2.getPriority().equals("Low");
        }
    })


    KTable<Windowed<String>, Message> fiveMinuteWindowed = inputStream

    .groupByKey(Serialized.with(Serdes.String(), MessageSerde))
    .windowedBy(TimeWindows.of(TimeUnit.MINUTES.toMillis(5)))
    .count()
    .to("test-filter", Produced.with(Serdes.String(), MessageSerde));


    final KafkaStreams streams = new KafkaStreams(builder.build(), props);

更新

根据Matthias的建议，我创建了这段代码，但是在.to方法中遇到了一些编译错误：

   inputStream

     .filter(new Predicate<String, Message>() {
    @Override
    public boolean test(String s, Message s2) {
        return s2.getPriority().equals("Low");
      }
    })
    .groupByKey(Serialized.with(Serdes.String(), MessageSerde))
    .windowedBy(TimeWindows.of(TimeUnit.MINUTES.toMillis(5)))
    .aggregate(
    new Initializer<Message>() { /* initializer */
        @Override
        public Message apply() {
            Message tuple = new Message();
            return tuple;
        }
    },
    new Aggregator<String, Message, Message>() { /* adder */
        @Override
        public Message apply(String aggKey, Message curMsg, Message tuple) {

            tuple.setCount(tuple.getCount() + 1);

            SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd hh:mm:ss.SSS");

            try{
                Date parsedDate_cur = dateFormat.parse(curMsg.getTimestamp());
                Timestamp timestamp_cur = new java.sql.Timestamp(parsedDate_cur.getTime());
                Date parsedDate_agg = dateFormat.parse(tuple.getTimestamp());
                Timestamp timestamp_agg = new java.sql.Timestamp(parsedDate_agg.getTime());

                if(timestamp_cur.after(timestamp_agg)){
                    tuple.setTimestamp(timestamp_cur.toString());
                }

                tuple.setId(curMsg.getId());
                tuple.setSourceip(curMsg.getSourceip());
                tuple.setType(curMsg.getType());
                tuple.setPriority(curMsg.getPriority());
                tuple.setName(curMsg.getName());
                tuple.setMetadata(curMsg.getMetadata());  
            }
            catch(Exception e){
                System.out.println("Error parsing dates"); 
            }    
            return tuple;
        }
    },
    Materialized.with(Serdes.String(), MessageSerde))
    .suppress(untilWindowCloses(unbounded())) 
    .toStream();
    .to("test-filter", Produced.with(Serdes.String(), MessageSerde));

错误包括：

Compilation failure
[ERROR] /home/x/Documents/project/src/main/java/com/streams/app/App.java:[194,9] no suitable method found for to(java.lang.String,org.apache.kafka.streams.kstream.Produced<java.lang.String,Pojo.Message>)
[ERROR]method org.apache.kafka.streams.kstream.KStream.to(java.lang.String,org.apache.kafka.streams.kstream.Produced<org.apache.kafka.streams.kstream.Windowed<java.lang.String>,Pojo.Message>) is not applicable
[ERROR](argument mismatch; inference variable K has incompatible equality constraints org.apache.kafka.streams.kstream.Windowed<java.lang.String>,java.lang.String)
[ERROR]method org.apache.kafka.streams.kstream.KStream.to(org.apache.kafka.streams.processor.TopicNameExtractor<org.apache.kafka.streams.kstream.Windowed<java.lang.String>,Pojo.Message>,org.apache.kafka.streams.kstream.Produced<org.apache.kafka.streams.kstream.Windowed<java.lang.String>,Pojo.Message>) is not applicable
[ERROR](argument mismatch; java.lang.String cannot be converted to org.apache.kafka.streams.processor.TopicNameExtractor<org.apache.kafka.streams.kstream.Windowed<java.lang.String>,Pojo.Message>)

消耗最近5分钟的消息，并将其周期性地转储到另一个主题中

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0 个答案: