解决spark-submit的There is insufficient memory for the Java Runtime Environment to continue.（老顽固问题） failed; error='Cannot allocate memory' (errno=12)

Q：第一次提交wordcount案例，OK，一切正常。再次提交，出现下述错误。完整错误粘贴如下：

21/01/27 14:55:48 INFO spark.SecurityManager: Changing modify acls groups to: 
21/01/27 14:55:48 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(hadoop); groups with view permissions: Set(); users  with modify permissions: Set(hadoop); groups with modify permissions: Set()
OpenJDK 64-Bit Server VM warning: INFO: os::commit_memory(0x00000000d9a80000, 66060288, 0) failed; error='Cannot allocate memory' (errno=12)
#
# There is insufficient memory for the Java Runtime Environment to continue.
# Native memory allocation (mmap) failed to map 66060288 bytes for committing reserved memory.
# An error report file with more information is saved as:
# /usr/local/spark/spark-2.4.7/bin/hs_err_pid8477.log

A：解决办法

1、按照网上说的 free-m 看一下

hadoop@master:/usr/local/spark/spark-2.4.7/bin$ free -m
              total        used        free      shared  buff/cache   available
Mem:           3757        3467         201           2          87         128
Swap:      

可以看到一共3757M，已经用了3467M，剩下可用的只有128M。这肯定不能运行了

2、
2.1、减小服务中对JVM的内存配置。
2.2、关必一些不必要的且占用内存大的进程。{linux上利用top命令查看所有进程，看哪些进程占用的内存太大，选择性的kill，释放内存，注意：安歇进程是不需要的。}
2.3、扩展内存。

这里采用第二种方法

hadoop@master:/usr/local/spark/spark-2.4.7/bin$ top
top - 15:07:42 up  1:19,  1 user,  load average: 1.30, 1.11, 1.03
Tasks:  90 total,   1 running,  56 sleeping,   0 stopped,   0 zombie
%Cpu(s): 50.4 us,  0.0 sy,  0.0 ni, 49.6 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
KiB Mem :  3847476 total,   183948 free,  3560476 used,   103052 buff/cache
KiB Swap:        0 total,        0 free,        0 used.   115160 avail Mem 

  PID USER      PR  NI    VIRT    RES    SHR S  %CPU %MEM     TIME+ COMMAND                                                                       
 3687 hadoop    20   0 2653672 2.284g      0 S 100.0 62.2  53:00.72 kdevtmpfsi                                                                    
    1 root      20   0   77700   2096      0 S   0.0  0.1   0:00.93 systemd                                                                       
    2 root      20   0       0      0      0 S   0.0  0.0   0:00.00 kthreadd  

罪魁祸首找到了。然后，kill掉占用内存高的java进程。再次提交任务就可以了！

hadoop@master:/usr/local/spark/spark-2.4.7/bin$ kill -9 3687
hadoop@master:/usr/local/spark/spark-2.4.7/bin$ top
top - 15:08:07 up  1:20,  1 user,  load average: 1.04, 1.06, 1.02
Tasks:  91 total,   1 running,  56 sleeping,   0 stopped,   0 zombie
%Cpu(s):  0.2 us,  0.0 sy,  0.0 ni, 99.8 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st
KiB Mem :  3847476 total,  2578636 free,  1161816 used,   107024 buff/cache
KiB Swap:        0 total,        0 free,        0 used.  2511832 avail Mem 

  PID USER      PR  NI    VIRT    RES    SHR S  %CPU %MEM     TIME+ COMMAND                                                                       
  744 root      10 -10  146756   8344      0 S   0.3  0.2   0:15.89 AliYunDun                                                                     
 4113 hadoop    20   0 3540084 391160   8308 S   0.3 10.2   0:11.74 java                                                                          
    1 root      20   0   77700   2096      0 S   0.0  0.1   0:00.93 systemd                                                                       
    2 root      20   0       0      0      0 S   0.0  0.0   0:00.00 kthreadd                                                                      
    4 root       0 -20       0      0      0 I   0.0  0.0   0:00.00 kworker/0:0H  

参考链接：https://blog.csdn.net/jingzi123456789/article/details/83545355