我有一个Flink作业，可将数据写入Kafka。 Kafka主题的最大邮件大小设置为5 MB，因此，如果我尝试写任何大于5 MB的记录，则会引发以下异常并使工作降低。
java.lang.Exception: Failed to send data to Kafka: The request included a message larger than the max message size the server will accept.
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducerBase.checkErroneous(FlinkKafkaProducerBase.java:373)
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer010.invoke(FlinkKafkaProducer010.java:350)
at org.apache.flink.streaming.api.operators.StreamSink.processElement(StreamSink.java:56)
at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:549)
at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:524)
at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:504)
at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:830)
at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:808)
at org.apache.flink.streaming.api.operators.StreamMap.processElement(StreamMap.java:41)
at org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:207)
at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:69)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:264)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:718)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.kafka.common.errors.RecordTooLargeException: The request included a message larger than the max message size the server will accept.
现在，我已在作业中配置检查点，因此，如果作业失败，它将再次重新启动。问题是，每次重新启动时，它对于相同的记录都会失败，并进入无限的失败循环并重新启动。有没有一种方法可以在我的代码中处理这个Kafka异常，从而不会降低整个工作量？