Re: flink集群提交任务挂掉

[shimin huang]

增大`taskmanager.memory.task.off-heap.size`配置

bowen li  于2021年4月2日周五 上午10:54写道：

> Hi,大家好：
>  现在我们遇到的场景是这样的,提交任务的时候会报错。我们使用的版本是1.12.1,搭建模式是standalone的。下面是报错信息。
>
>java.lang.OutOfMemoryError: Direct buffer memory. The direct
> out-of-memory error has occurred. This can mean two things: either job(s)
> require(s) a larger size of JVM direct memory or there is a direct memory
> leak. The direct memory can be allocated by user code or some of its
> dependencies. In this case 'taskmanager.memory.task.off-heap.size'
> configuration option should be increased. Flink framework and its
> dependencies also consume the direct memory, mostly for network
> communication. The most of network memory is managed by Flink and should
> not result in out-of-memory error. In certain special cases, in particular
> for jobs with high parallelism, the framework may require more direct
> memory which is not managed by Flink. In this case
> 'taskmanager.memory.framework.off-heap.size' configuration option should be
> increased. If the error persists then there is probably a direct memory
> leak in user code or some of its dependencies
>   这种情况我们需要特别的配置吗？

flink集群提交任务挂掉

[bowen li]

Hi,大家好：
 现在我们遇到的场景是这样的,提交任务的时候会报错。我们使用的版本是1.12.1,搭建模式是standalone的。下面是报错信息。

   java.lang.OutOfMemoryError: Direct buffer memory. The direct out-of-memory 
error has occurred. This can mean two things: either job(s) require(s) a larger 
size of JVM direct memory or there is a direct memory leak. The direct memory 
can be allocated by user code or some of its dependencies. In this case 
'taskmanager.memory.task.off-heap.size' configuration option should be 
increased. Flink framework and its dependencies also consume the direct memory, 
mostly for network communication. The most of network memory is managed by 
Flink and should not result in out-of-memory error. In certain special cases, 
in particular for jobs with high parallelism, the framework may require more 
direct memory which is not managed by Flink. In this case 
'taskmanager.memory.framework.off-heap.size' configuration option should be 
increased. If the error persists then there is probably a direct memory leak in 
user code or some of its dependencies
  这种情况我们需要特别的配置吗？