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我正在尝试创建一个 Kafka 拓扑并将其分解为更具可读性。我有一个按键分组的流，然后我试图像这样窗口化它：

SessionWindowedKStream<byte[], byte[]> windowedTable =
        groupedStream.windowedBy(SessionWindows.with(Duration.ofSeconds(config.joinWindowSeconds)).grace(Duration.ZERO));

KTable<Windowed<byte[]>, byte[]> mergedTable = windowedTable
        .reduce((aggregateValue, newValue) -> {
          try {
            Map<String, String> recentMap = MAPPER.readValue(new String(newValue), HashMap.class);
            Map<String, String> aggregateMap = MAPPER.readValue(new String(newValue), HashMap.class);
            aggregateMap.forEach(recentMap::putIfAbsent);
            newValue = MAPPER.writeValueAsString(recentMap).getBytes();
          } catch (Exception e) {
            LOG.warn("Couldn't aggregate key grouped stream\n", e);
          }
          return newValue;
        }, Materialized.with(Serdes.ByteArray(), Serdes.ByteArray()));

      mergedTable.toStream()
              .foreach((externalId, eventIncidentByteMap) -> {
          ...
}

不幸的是，抛出了以下异常：

00:40:11.344 [main] ERROR o.a.k.s.p.i.ProcessorStateManager - stream-thread [main] task [0_0] Failed to flush state store KSTREAM-REDUCE-STATE-STORE-0000000020: 
org.apache.kafka.streams.errors.ProcessorStateException: Error opening store KSTREAM-REDUCE-STATE-STORE-0000000020.1589846400000 at location /tmp/kafka-streams/test-consumer/0_0/KSTREAM-REDUCE-STATE-STORE-0000000020/KSTREAM-REDUCE-STATE-STORE-0000000020.1589846400000
    at org.apache.kafka.streams.state.internals.RocksDBStore.openRocksDB(RocksDBStore.java:220)
    at org.apache.kafka.streams.state.internals.RocksDBStore.openDB(RocksDBStore.java:191)
    at org.apache.kafka.streams.state.internals.KeyValueSegment.openDB(KeyValueSegment.java:49)
    at org.apache.kafka.streams.state.internals.KeyValueSegments.getOrCreateSegment(KeyValueSegments.java:50)
    at org.apache.kafka.streams.state.internals.KeyValueSegments.getOrCreateSegment(KeyValueSegments.java:25)
    at org.apache.kafka.streams.state.internals.AbstractSegments.getOrCreateSegmentIfLive(AbstractSegments.java:84)
    at org.apache.kafka.streams.state.internals.AbstractRocksDBSegmentedBytesStore.put(AbstractRocksDBSegmentedBytesStore.java:146)
    at org.apache.kafka.streams.state.internals.RocksDBSessionStore.put(RocksDBSessionStore.java:81)
    at org.apache.kafka.streams.state.internals.RocksDBSessionStore.put(RocksDBSessionStore.java:25)
    at org.apache.kafka.streams.state.internals.ChangeLoggingSessionBytesStore.put(ChangeLoggingSessionBytesStore.java:74)
    at org.apache.kafka.streams.state.internals.ChangeLoggingSessionBytesStore.put(ChangeLoggingSessionBytesStore.java:33)
    at org.apache.kafka.streams.state.internals.CachingSessionStore.putAndMaybeForward(CachingSessionStore.java:90)
    at org.apache.kafka.streams.state.internals.CachingSessionStore.lambda$initInternal$0(CachingSessionStore.java:73)
    at org.apache.kafka.streams.state.internals.NamedCache.flush(NamedCache.java:151)
    at org.apache.kafka.streams.state.internals.NamedCache.flush(NamedCache.java:109)
    at org.apache.kafka.streams.state.internals.ThreadCache.flush(ThreadCache.java:124)
    at org.apache.kafka.streams.state.internals.CachingSessionStore.flush(CachingSessionStore.java:230)
    at org.apache.kafka.streams.state.internals.WrappedStateStore.flush(WrappedStateStore.java:84)
    at org.apache.kafka.streams.state.internals.MeteredSessionStore.lambda$flush$5(MeteredSessionStore.java:227)
    at org.apache.kafka.streams.processor.internals.metrics.StreamsMetricsImpl.maybeMeasureLatency(StreamsMetricsImpl.java:806)
    at org.apache.kafka.streams.state.internals.MeteredSessionStore.flush(MeteredSessionStore.java:227)
    at org.apache.kafka.streams.processor.internals.ProcessorStateManager.flush(ProcessorStateManager.java:282)
    at org.apache.kafka.streams.processor.internals.AbstractTask.flushState(AbstractTask.java:177)
    at org.apache.kafka.streams.processor.internals.StreamTask.flushState(StreamTask.java:554)
    at org.apache.kafka.streams.processor.internals.StreamTask.commit(StreamTask.java:490)
    at org.apache.kafka.streams.processor.internals.StreamTask.commit(StreamTask.java:478)
    at org.apache.kafka.streams.TopologyTestDriver.completeAllProcessableWork(TopologyTestDriver.java:517)
    at org.apache.kafka.streams.TopologyTestDriver.pipeRecord(TopologyTestDriver.java:472)
    at org.apache.kafka.streams.TopologyTestDriver.pipeRecord(TopologyTestDriver.java:806)
    at org.apache.kafka.streams.TestInputTopic.pipeInput(TestInputTopic.java:115)
    at org.apache.kafka.streams.TestInputTopic.pipeInput(TestInputTopic.java:137)
    at com.ro.revelon.pub.api.dp.EventConsumerTest.testEventWithIncident(EventConsumerTest.java:63)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50)
    at org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
    at org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47)
    at org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
    at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325)
    at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:78)
    at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:57)
    at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290)
    at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71)
    at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288)
    at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58)
    at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268)
    at org.junit.runners.ParentRunner.run(ParentRunner.java:363)
    at org.junit.runner.JUnitCore.run(JUnitCore.java:137)
    at com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:68)
    at com.intellij.rt.junit.IdeaTestRunner$Repeater.startRunnerWithArgs(IdeaTestRunner.java:33)
    at com.intellij.rt.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:230)
    at com.intellij.rt.junit.JUnitStarter.main(JUnitStarter.java:58)
Caused by: org.rocksdb.RocksDBException: You have to open all column families. Column families not opened: keyValueWithTimestamp
    at org.rocksdb.RocksDB.open(Native Method)
    at org.rocksdb.RocksDB.open(RocksDB.java:286)
    at org.apache.kafka.streams.state.internals.RocksDBStore.openRocksDB(RocksDBStore.java:217)
    ... 53 common frames omitted

我不确定问题是否与未在某处指定的 Serdes 相关。我在.groupByKey(Grouped.with(Serdes.ByteArray(), Serdes.ByteArray()))按键分组时确实使用过。我怀疑我一路上没有正确映射一些东西。

Caused by: org.rocksdb.RocksDBException: You have to open all column families. Column families not opened: keyValueWithTimestamp对我来说也是可疑和神秘的。无论哪种方式，我都不确定如何解决这个问题。

我知道以下代码确实有效：


KTable<byte[], byte[]> mergedTable = groupedStream
        .reduce((aggregateValue, newValue) -> {
          try {
            Map<String, String> recentMap = MAPPER.readValue(new String(newValue), HashMap.class);
            Map<String, String> aggregateMap = MAPPER.readValue(new String(newValue), HashMap.class);
            aggregateMap.forEach(recentMap::putIfAbsent);
            newValue = MAPPER.writeValueAsString(recentMap).getBytes();
          } catch (Exception e) {
            LOG.warn("Couldn't aggregate key grouped stream\n", e);
          }
          return newValue;
        }, Materialized.with(Serdes.ByteArray(), Serdes.ByteArray()));

mergedTable.toStream()
        .foreach((externalId, eventIncidentByteMap) -> {
          ...
  }

如何在不触发rocksdb存储异常的情况下分解它？

4

1 回答 1

2

您是否降级了 Kafka Streams 库？在 2.3.0 中，存储格式发生了变化，这种新的存储格式与旧的 Kafka Streams 版本不兼容。

如果您想从 2.3.0（或更高）版本降级到 2.2.x（或更低）版本，则需要先清除本地状态（例如，手动删除应用程序状态目录或通过KafkaStreams#cleanup()）。重新启动时，将使用旧存储格式从更改日志主题重建状态。

于 2020-05-23T21:53:04.360 回答