今天,我运行了文件系统索引的脚本来刷新RAID文件索引,4h后它崩溃了,出现以下错误:

[md5:]  241613/241627 97.5%  
[md5:]  241614/241627 97.5%  
[md5:]  241625/241627 98.1%
Creating missing list... (79570 files missing)
Creating new files list... (241627 new files)

<--- Last few GCs --->

11629672 ms: Mark-sweep 1174.6 (1426.5) -> 1172.4 (1418.3) MB, 659.9 / 0 ms [allocation failure] [GC in old space requested].
11630371 ms: Mark-sweep 1172.4 (1418.3) -> 1172.4 (1411.3) MB, 698.9 / 0 ms [allocation failure] [GC in old space requested].
11631105 ms: Mark-sweep 1172.4 (1411.3) -> 1172.4 (1389.3) MB, 733.5 / 0 ms [last resort gc].
11631778 ms: Mark-sweep 1172.4 (1389.3) -> 1172.4 (1368.3) MB, 673.6 / 0 ms [last resort gc].


<--- JS stacktrace --->

==== JS stack trace =========================================

Security context: 0x3d1d329c9e59 <JS Object>
1: SparseJoinWithSeparatorJS(aka SparseJoinWithSeparatorJS) [native array.js:~84] [pc=0x3629ef689ad0] (this=0x3d1d32904189 <undefined>,w=0x2b690ce91071 <JS Array[241627]>,L=241627,M=0x3d1d329b4a11 <JS Function ConvertToString (SharedFunctionInfo 0x3d1d3294ef79)>,N=0x7c953bf4d49 <String[4]\: ,\n  >)
2: Join(aka Join) [native array.js:143] [pc=0x3629ef616696] (this=0x3d1d32904189 <undefin...

FATAL ERROR: CALL_AND_RETRY_LAST Allocation failed - JavaScript heap out of memory
 1: node::Abort() [/usr/bin/node]
 2: 0xe2c5fc [/usr/bin/node]
 3: v8::Utils::ReportApiFailure(char const*, char const*) [/usr/bin/node]
 4: v8::internal::V8::FatalProcessOutOfMemory(char const*, bool) [/usr/bin/node]
 5: v8::internal::Factory::NewRawTwoByteString(int, v8::internal::PretenureFlag) [/usr/bin/node]
 6: v8::internal::Runtime_SparseJoinWithSeparator(int, v8::internal::Object**, v8::internal::Isolate*) [/usr/bin/node]
 7: 0x3629ef50961b

服务器配置16gb RAM和24gb SSD交换盘。我非常怀疑我的脚本内存超过了36gb。至少不应该是这样

脚本创建文件索引存储为对象数组与文件元数据(修改日期,权限等,没有大数据)

以下是完整的脚本代码: http://pastebin.com/mjaD76c3

我已经经历了奇怪的节点问题在过去与这个脚本迫使我eg。分割索引到多个文件作为节点是故障时,工作在这样的大文件字符串。对于庞大的数据集,有什么方法可以改善nodejs的内存管理吗?


当前回答

你可以通过以下方法修复Node.js中的“堆出内存”错误。

Increase the amount of memory allocated to the Node.js process by using the --max-old-space-size flag when starting the application. For example, you can increase the limit to 4GB by running node --max-old-space-size=4096 index.js. Use a memory leak detection tool, such as the Node.js heap dump module, to identify and fix memory leaks in your application. You can also use the node inspector and use chrome://inspect to check memory usage. Optimize your code to reduce the amount of memory needed. This might involve reducing the size of data structures, reusing objects instead of creating new ones, or using more efficient algorithms. Use a garbage collector (GC) algorithm to manage memory automatically. Node.js uses the V8 engine's garbage collector by default, but you can also use other GC algorithms such as the Garbage Collection in Node.js Use a containerization technology like Docker which limits the amount of memory available to the container. Use a process manager like pm2 which allows to automatically restart the node application if it goes out of memory.

其他回答

在我的例子中,我把node.js版本升级到最新版(12.8.0版本),它就像一个魅力。

为了防止任何人在不能直接设置节点属性的环境中遇到这个问题(在我的情况下是构建工具):

NODE_OPTIONS="--max-old-space-size=4096" node ...

如果不能在命令行上传递节点选项,则可以使用环境变量设置节点选项。

如果你想要全局增加节点的内存使用—不仅仅是单个脚本,你可以导出环境变量,像这样: 出口NODE_OPTIONS =——max_old_space_size = 4096

这样在运行构建时就不需要处理文件了 NPM运行构建。

我最近遇到了同样的问题,遇到了这个线程,但我的问题是React应用程序。下面对节点启动命令的更改解决了我的问题。

语法

node --max-old-space-size=<size> path-to/fileName.js

例子

node --max-old-space-size=16000 scripts/build.js

为什么max-old-space-size是16000 ?

基本上,它取决于分配给该线程的内存和您的节点设置。

如何验证和给出正确的尺寸?

这基本上是v8引擎。下面的代码帮助你理解你的本地节点v8引擎的堆大小。

const v8 = require('v8');
const totalHeapSize = v8.getHeapStatistics().total_available_size;
const totalHeapSizeGb = (totalHeapSize / 1024 / 1024 / 1024).toFixed(2);
console.log('totalHeapSizeGb: ', totalHeapSizeGb);

对于angular项目捆绑,我在包中添加了下面这行代码。Json文件在脚本部分。

"build-prod": "node --max_old_space_size=5120 ./node_modules/@angular/cli/bin/ng build --prod --base-href /"

现在,为了捆绑我的代码,我使用npm run build-prod而不是ng build——requiredFlagsHere

希望这能有所帮助!