Question

我想做的是这样

使用某个主题的记录
计算每个1秒窗口的值
检测记录数<4的窗口
将FINAL结果发送到另一个主题

我使用抑制发送最终结果，但是出现了这样的错误。

09:18:07,963 ERROR org.apache.kafka.streams.processor.internals.ProcessorStateManager  
- task [1_0] Failed to flush state store KSTREAM-AGGREGATE-STATE-STORE-0000000002: 
java.lang.ClassCastException: org.apache.kafka.streams.kstream.Windowed cannot be cast to java.lang.String
at org.apache.kafka.common.serialization.StringSerializer.serialize(StringSerializer.java:28)
at org.apache.kafka.streams.kstream.internals.suppress.KTableSuppressProcessor.buffer(KTableSuppressProcessor.java:86)
at org.apache.kafka.streams.kstream.internals.suppress.KTableSuppressProcessor.process(KTableSuppressProcessor.java:78)
at org.apache.kafka.streams.kstream.internals.suppress.KTableSuppressProcessor.process(KTableSuppressProcessor.java:37)
at org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:115)
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:146)
.....

我认为我的代码与开发人员指南中的示例相同。有什么问题？我的代码在这里。

final KStream<String, String> views = builder.stream("fluent-newData");
final KTable<Windowed<String>, Long> anomalousUsers = views
    .map((key, value) -> {
       JSONObject message = JSONObject.fromObject(value);
       String[] strArry = message.getString("detail").split(",");
       return KeyValue.pair(strArry[0], value);
    })
    .groupByKey()
    .windowedBy(TimeWindows.of(Duration.ofSeconds(1))
    .grace(Duration.ofSeconds(20)))
    .count()
    .suppress(Suppressed.untilWindowCloses(unbounded()))
    .filter((windowedUserId, count) -> count < 4);

final KStream<String, String> anomalousUsersForConsole = anomalousUsers
    .toStream()
    .filter((windowedUserId, count) -> count != null)
    .map((windowedUserId, count) -> new KeyValue<>(windowedUserId.toString(), windowedUserId.toString() +" c:" + count.toString()));

anomalousUsersForConsole.to("demo-count-output", Produced.with(stringSerde, stringSerde));

Answer 1

“窗口化不能转换为java.lang.String” 通常在没有直接指定serdes时抛出。

构建stream(..)时，直接指定消耗的实例，如下所示：

builder.stream("fluent-newData", Consumed.with(Serdes.String(), Serdes.String()))

对于groupByKey()，您还需要通过Grouped，如下所示：

 .groupByKey(Grouped.with(Serdes.String(), Serdes.String()))

Kafka Stream如何使用KTable＃Suppress发送最终聚合？

1 个答案: