The dirty consumer shutdown, due to the consumed count exceed the max-consumed [0]

使用taier框架执行同步kafka到数据库postgre sql的语句，报错。

错误如下：

2023-09-17 20:04:43
org.apache.flink.runtime.JobException: The failure is not recoverable
	at org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.handleFailure(ExecutionFailureHandler.java:107)
	at org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.getFailureHandlingResult(ExecutionFailureHandler.java:80)
	at org.apache.flink.runtime.scheduler.DefaultScheduler.handleTaskFailure(DefaultScheduler.java:233)
	at org.apache.flink.runtime.scheduler.DefaultScheduler.maybeHandleTaskFailure(DefaultScheduler.java:224)
	at org.apache.flink.runtime.scheduler.DefaultScheduler.updateTaskExecutionStateInternal(DefaultScheduler.java:215)
	at org.apache.flink.runtime.scheduler.SchedulerBase.updateTaskExecutionState(SchedulerBase.java:666)
	at org.apache.flink.runtime.scheduler.SchedulerNG.updateTaskExecutionState(SchedulerNG.java:89)
	at org.apache.flink.runtime.jobmaster.JobMaster.updateTaskExecutionState(JobMaster.java:446)
	at sun.reflect.GeneratedMethodAccessor88.invoke(Unknown Source)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcInvocation(AkkaRpcActor.java:305)
	at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcMessage(AkkaRpcActor.java:212)
	at org.apache.flink.runtime.rpc.akka.FencedAkkaRpcActor.handleRpcMessage(FencedAkkaRpcActor.java:77)
	at org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleMessage(AkkaRpcActor.java:158)
	at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:26)
	at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:21)
	at scala.PartialFunction.applyOrElse(PartialFunction.scala:123)
	at scala.PartialFunction.applyOrElse$(PartialFunction.scala:122)
	at akka.japi.pf.UnitCaseStatement.applyOrElse(CaseStatements.scala:21)
	at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:171)
	at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:172)
	at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:172)
	at akka.actor.Actor.aroundReceive(Actor.scala:517)
	at akka.actor.Actor.aroundReceive$(Actor.scala:515)
	at akka.actor.AbstractActor.aroundReceive(AbstractActor.scala:225)
	at akka.actor.ActorCell.receiveMessage(ActorCell.scala:592)
	at akka.actor.ActorCell.invoke(ActorCell.scala:561)
	at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:258)
	at akka.dispatch.Mailbox.run(Mailbox.scala:225)
	at akka.dispatch.Mailbox.exec(Mailbox.scala:235)
	at akka.dispatch.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
	at akka.dispatch.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
	at akka.dispatch.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
	at akka.dispatch.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Caused by: com.dtstack.chunjun.throwable.NoRestartException: The dirty consumer shutdown, due to the consumed count exceed the max-consumed [0]
	at com.dtstack.chunjun.dirty.consumer.DirtyDataCollector.addConsumed(DirtyDataCollector.java:105)
	at com.dtstack.chunjun.dirty.consumer.DirtyDataCollector.offer(DirtyDataCollector.java:79)
	at com.dtstack.chunjun.dirty.manager.DirtyManager.collect(DirtyManager.java:140)
	at com.dtstack.chunjun.sink.format.BaseRichOutputFormat.writeSingleRecord(BaseRichOutputFormat.java:482)
	at com.dtstack.chunjun.sink.format.BaseRichOutputFormat.lambda$writeRecordInternal$1(BaseRichOutputFormat.java:500)
	at java.util.ArrayList.forEach(ArrayList.java:1259)
	at com.dtstack.chunjun.sink.format.BaseRichOutputFormat.writeRecordInternal(BaseRichOutputFormat.java:500)
	at com.dtstack.chunjun.sink.format.BaseRichOutputFormat.writeRecord(BaseRichOutputFormat.java:290)
	at com.dtstack.chunjun.sink.format.BaseRichOutputFormat.writeRecord(BaseRichOutputFormat.java:89)
	at com.dtstack.chunjun.sink.DtOutputFormatSinkFunction.invoke(DtOutputFormatSinkFunction.java:117)
	at org.apache.flink.table.runtime.operators.sink.SinkOperator.processElement(SinkOperator.java:72)
	at org.apache.flink.streaming.runtime.tasks.CopyingChainingOutput.pushToOperator(CopyingChainingOutput.java:71)
	at org.apache.flink.streaming.runtime.tasks.CopyingChainingOutput.collect(CopyingChainingOutput.java:46)
	at org.apache.flink.streaming.runtime.tasks.CopyingChainingOutput.collect(CopyingChainingOutput.java:26)
	at org.apache.flink.streaming.api.operators.CountingOutput.collect(CountingOutput.java:50)
	at org.apache.flink.streaming.api.operators.CountingOutput.collect(CountingOutput.java:28)
	at org.apache.flink.streaming.api.operators.StreamSourceContexts$ManualWatermarkContext.processAndCollectWithTimestamp(StreamSourceContexts.java:322)
	at org.apache.flink.streaming.api.operators.StreamSourceContexts$WatermarkContext.collectWithTimestamp(StreamSourceContexts.java:426)
	at org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher.emitRecordsWithTimestamps(AbstractFetcher.java:365)
	at org.apache.flink.streaming.connectors.kafka.internals.KafkaFetcher.partitionConsumerRecordsHandler(KafkaFetcher.java:183)
	at org.apache.flink.streaming.connectors.kafka.internals.KafkaFetcher.runFetchLoop(KafkaFetcher.java:142)
	at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:826)
	at com.dtstack.chunjun.connector.kafka.source.KafkaConsumerWrapper.run(KafkaConsumerWrapper.java:155)
	at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:110)
	at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:66)
	at org.apache.flink.streaming.runtime.tasks.SourceStreamTask$LegacySourceFunctionThread.run(SourceStreamTask.java:267)

字面意思是消费数量超过最大消费数量，但是我没做相关的限制，网上关于这个错误的资料比较少。

各位大佬：数据同步出现这个异常，怎么样处理呢？ - 袋鼠社区-数栈丨数据中台丨数据治理丨湖仓一体丨数据开发丨基础软件 (dtstack.com)

根据官网这篇文章的提示，应该是插入的sql语句出现了问题。我看了下数据库的日志，果然是最终拼成sql语句出了问题（表只有一个字段时会有问题，这应该算是个bug）：

INSERT INTO "spend_report"("account_id") VALUES (2) ON CONFLICT ("account_id") DO UPDATE SET

因为是测试，我改成两个字段就没这个问题了。

这个错误主要是字面意思容易被误导，查找原因的时候还是要从具体的错误中去确认。