Frequent Async message Send and Receive bug while use Kafka

**Describe the bug**
In version 6.4.0, and in version 6.0. because I read the sourcode both of them.
I use kafka as async job Manager(extends AbstractMessageBaseJobManager) and send message to kafka. The consumer consumes the job message and call ExecuteAsyncRunnable's run method to exeucte asyc job.
I record the log info while send and receive job message called send and receive log.
Occasionally, very frequently send and receive log happened which caused CPU up to 100%. Only suspend the flow can recover the cpu load.
**Expected behavior**
Only once send and receive of job message.

**Code**
In org.flowable.job.service.impl.asyncexecutor.ExecuteAsyncRunnable#run, lockjob() method will be executed.
When lockjob() failed， the bug will be reproduced.
Because in org.flowable.job.service.impl.asyncexecutor.ExecuteAsyncRunnable#lockJob, the catch block whill call unacuqireJob() and this method will resend the job message. Then rotated,circle, repeated send and receive.
But I don't know which Exeception is throwed to cause this bug.
One possible reason is repeated consuming of kafka message. once one message consumed two time at one time. one message can lock the Execution Entity in DB using column LOCK_TIME_ in table act_ru_execution. Then the next same message try to lock the same execution ,but it is failed.
**Additional context**
Add the version of Flowable that you are using, the database vendor and if you are using Flowable within Spring Boot, the Flowable Task application etc.

Beginne mit ExecuteAsyncRunnable#run und lockJob und untersuche dann den catch-Pfad über unacquireJob, bei dem das Issue meldet, dass die Nachricht erneut gesendet wird. Reproduziere das wiederholte Senden und Empfangen mit Kafka, während du die Ausführungssperre in act_ru_execution beobachtest, und erfasse die Exception, die dazu führt, dass lockJob fehlschlägt. Erledigt ist die Aufgabe, wenn die Ursache des Fehlers identifiziert ist und die Schleife mit der wiederholten Nachricht die CPU nicht mehr auf 100 % auslastet.

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