hi， 感谢大神的回复。看了下是因为我执行的SQL作业，有多个sink，在执行TableEnvironment.executeSQL时，Flink提交了多个job，在本地执行时貌似就走到了这个异常。我将多sink修改为TableEnvironment.createStatementSet来提交，就没有这个问题了。谢谢回复。
在 2020-07-13 13:51:55，"Xintong Song" <[email protected]> 写道： >Local execution 模式下，Flink 是无法实际控制 JVM 的 Xmx, Xms, MaxDirectMemorySize >等参数的，这些参数取决于你的 IDE 设置。 >检查一下 idea 的 run configuration 是否有配置过 -XX:MaxDirectMemorySize。 > >Thank you~ > >Xintong Song > > > >On Sat, Jul 11, 2020 at 3:48 PM Congxian Qiu <[email protected]> wrote: > >> Hi >> >> 这个问题可以看下是否和 releasenote[1] 中 memory configuration >> 相关的修改有关，具体到这个错误，你可以按照提示增加一些内存看看 >> >> [1] >> >> https://flink.apache.org/news/2020/07/06/release-1.11.0.html#other-improvements >> Best, >> Congxian >> >> >> sunfulin <[email protected]> 于2020年7月10日周五 下午11:32写道： >> >> > hi， >> > >> > >> 我在使用1.11版本在本地idea起一个作业时，并发为1，抛出了如下关于内存的异常。。问题是之前从来没有显示配置过taskmanager的memory参数，这是为何？ >> > 感觉由1.10升级到1.11问题还是挺多的。。我尝试增加了JVM参数，增加DirectMemory内存配置，还是没有作用，请教大神帮忙看下。 >> > >> > >> > Exception in thread "main" java.lang.OutOfMemoryError: Could not allocate >> > enough memory segments for NetworkBufferPool (required (Mb): 64, >> allocated >> > (Mb): 63, missing (Mb): 1). Cause: 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 which has to be >> investigated >> > and fixed. The task executor has to be shutdown... >>
