apache-kafka - 卡夫卡流 : How to fix Serde casting error

Question

当我使用聚合函数模拟字数统计时，我遇到了 Serde 转换问题。

Exception in thread "aggregation-transformation-application-43485635-2d3c-4edc-b13c-c6505a793d18-StreamThread-1" org.apache.kafka.streams.errors.StreamsException: Deserialization exception handler is set to fail upon a deserialization error. If you would rather have the streaming pipeline continue after a deserialization error, please set the default.deserialization.exception.handler appropriately.
    at org.apache.kafka.streams.processor.internals.RecordDeserializer.deserialize(RecordDeserializer.java:80)
    at org.apache.kafka.streams.processor.internals.RecordQueue.maybeUpdateTimestamp(RecordQueue.java:160)
    at org.apache.kafka.streams.processor.internals.RecordQueue.poll(RecordQueue.java:115)
    at org.apache.kafka.streams.processor.internals.PartitionGroup.nextRecord(PartitionGroup.java:100)
    at org.apache.kafka.streams.processor.internals.StreamTask.process(StreamTask.java:349)
    at org.apache.kafka.streams.processor.internals.AssignedStreamsTasks.process(AssignedStreamsTasks.java:199)
    at org.apache.kafka.streams.processor.internals.TaskManager.process(TaskManager.java:420)
    at org.apache.kafka.streams.processor.internals.StreamThread.runOnce(StreamThread.java:890)
    at org.apache.kafka.streams.processor.internals.StreamThread.runLoop(StreamThread.java:805)
    at org.apache.kafka.streams.processor.internals.StreamThread.run(StreamThread.java:774)
Caused by: org.apache.kafka.common.errors.SerializationException: Size of data received by IntegerDeserializer is not 4

尽管我为每个任务定义了 Serdes，但它会抛出 SerializationException。

import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.common.utils.Bytes;
import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.Topology;
import org.apache.kafka.streams.kstream.*;
import org.apache.kafka.streams.state.KeyValueStore;

import java.util.Arrays;
import java.util.Properties;
import java.util.concurrent.CountDownLatch;

public class AggregationTransformation {
    public static void main(String[] args) {
        //prepare config
        Properties config = new Properties();
        config.put(StreamsConfig.APPLICATION_ID_CONFIG, "aggregation-transformation-application");
        config.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        config.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
        config.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
        config.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass());

        StreamsBuilder builder = new StreamsBuilder();

        KStream<String, String> kStream = builder.stream("agg-table-source-topic");
        KStream<String, Integer> kStreamFormatted = kStream.flatMapValues((key, value) ->
                Arrays.asList(value.split("\\W+"))).selectKey((key, value) -> value)
                .mapValues(value -> 1);

        kStreamFormatted.groupByKey(Grouped.<String,Integer>as(null)
                .withValueSerde(Serdes.Integer()))
                .aggregate(() -> 0,
                        (aggKey, newValue, aggValue) -> aggValue + newValue,
                        Materialized.<String, Integer, KeyValueStore<Bytes, byte[]>>
                                as("aggregated-stream-store")
                                .withKeySerde(Serdes.String())
                                .withValueSerde(Serdes.Integer())
                ).toStream().to("agg-output-topic", Produced.with(Serdes.String(), Serdes.Integer()));

        Topology topology = builder.build();
        KafkaStreams kafkaStreams = new KafkaStreams(topology, config);

        CountDownLatch countDownLatch = new CountDownLatch(1);

        // attach shutdown handler to catch control-c
        Runtime.getRuntime().addShutdownHook(new Thread("streams-shutdown-hook") {
            @Override
            public void run() {
                kafkaStreams.close();
                countDownLatch.countDown();
            }
        });

        try {
            kafkaStreams.start();
            countDownLatch.await();
        } catch (Throwable e) {
            System.exit(1);
        }
        System.exit(0);
    }
}

对于作为“John Smith”首次进入生产者控制台，我希望输出主题 (agg-output-topic) 应该有

John 1
Smith 1

如果我向生产者输入相同的输入(agg-table-source-topic)，那么输出主题应该进行聚合并且结果应该是

John 2
Smith 2

感谢您的帮助。

Answer 1

SerializationException 表示您的Deserializer(在您的情况下为 IntegerDeserializer)无法反序列化消息 - 无法将字节转换为某个对象(Integer )

您如何在注释中将类型从 Long 更改为 Integer。我认为您首先使用 Long 类型启动您的应用程序并处理多条消息，然后将类型更改为 Integer。您的应用程序将中间结果保存在变更日志主题中，稍后使用新类型和反序列化器 (Serdes)，它无法反序列化并抛出异常。

如果您更改应用程序中的类型，您必须删除在处理过程中创建的所有更改日志主题。否则可能会发生 SerializationException。