如何高效地遍历超大MongoDB集合 · Fundebug博客

- GitHub 仓库：[Fundebug/loop-mongodb-big-collection](https://github.com/Fundebug/loop-mongodb-big-collection) ![](https://image.fundebug.com/2019-03-21-mongodb.jpg) 本文使用的编程语言是 Node.js，连接 MongoDB 的模块用的是[mongoose](https://mongoosejs.com/)。但是，本文介绍的方法适用于其他编程语言及其对应的 MongoDB 模块。 ### 错误方法：find() 也许，在遍历 MongoDB 集合时，我们会这样写： ```javascript const Promise = require("bluebird"); function findAllMembers() { return Member.find(); } async function test() { const members = await findAllMembers(); let N = 0; await Promise.mapSeries(members, member => { N++; console.log(`name of the ${N}th member: ${member.name}`); }); console.log(`loop all ${N} members success`); } test(); ``` 注意，我们使用的是 Bluebird 的[mapSeries](http://bluebirdjs.com/docs/api/promise.mapseries.html)而非[map](http://bluebirdjs.com/docs/api/promise.map.html)，members 数组中的元素是一个一个处理的。这样就够了吗？当 Member 集合中的 document 不多时，比如只有 1000 个时，那确实没有问题。但是当 Member 集合中有 1000 万个 document 时，会发生什么呢？如下： ```javascript <--- Last few GCs ---> rt of marking 1770 ms) (average mu = 0.168, current mu = 0.025) finalize [5887:0x43127d0] 33672 ms: Mark-sweep 1398.3 (1425.2) -> 1398.0 (1425.7) MB, 1772.0 / 0.0 ms (+ 0.1 ms in 12 steps since start of marking, biggest step 0.0 ms, walltime since start of marking 1775 ms) (average mu = 0.088, current mu = 0.002) finalize [5887:0x43127d0] 35172 ms: Mark-sweep 1398.5 (1425.7) -> 1398.4 (1428.7) MB, 1496.7 / 0.0 ms (average mu = 0.049, current mu = 0.002) allocation failure scavenge might not succeed <--- JS stacktrace ---> FATAL ERROR: Ineffective mark-compacts near heap limit Allocation failed - JavaScript heap out of memory 1: 0x8c02c0 node::Abort() [node] 2: 0x8c030c [node] 3: 0xad15de v8::Utils::ReportOOMFailure(v8::internal::Isolate*, char const*, bool) [node] 4: 0xad1814 v8::internal::V8::FatalProcessOutOfMemory(v8::internal::Isolate*, char const*, bool) [node] 5: 0xebe752 [node] 6: 0xebe858 v8::internal::Heap::CheckIneffectiveMarkCompact(unsigned long, double) [node] 7: 0xeca982 v8::internal::Heap::PerformGarbageCollection(v8::internal::GarbageCollector, v8::GCCallbackFlags) [node] 8: 0xecb2b4 v8::internal::Heap::CollectGarbage(v8::internal::AllocationSpace, v8::internal::GarbageCollectionReason, v8::GCCallbackFlags) [node] 9: 0xecba8a v8::internal::Heap::FinalizeIncrementalMarkingIfComplete(v8::internal::GarbageCollectionReason) [node] 10: 0xecf1b7 v8::internal::IncrementalMarkingJob::Task::RunInternal() [node] 11: 0xbc1796 v8::internal::CancelableTask::Run() [node] 12: 0x935018 node::PerIsolatePlatformData::FlushForegroundTasksInternal() [node] 13: 0x9fccff [node] 14: 0xa0dbd8 [node] 15: 0x9fd63b uv_run [node] 16: 0x8ca6c5 node::Start(v8::Isolate*, node::IsolateData*, int, char const* const*, int, char const* const*) [node] 17: 0x8c945f node::Start(int, char**) [node] 18: 0x7f84b6263f45 __libc_start_main [/lib/x86_64-linux-gnu/libc.so.6] 19: 0x885c55 [node] Aborted (core dumped) ``` 可知，内存不足了。打印[find()](https://mongoosejs.com/docs/api.html#model_Model.find)返回的 members 数组可知，集合中所有元素都返回了，**哪个数组放得下 1000 万个 Object?** ### 正确方法：find().cursor()与 eachAsync() 将整个集合 find()全部返回，这种操作应该避免，正确的方法应该是这样的： ```javascript function findAllMembersCursor() { return Member.find().cursor(); } async function test() { const membersCursor = await findAllMembersCursor(); let N = 0; await membersCursor.eachAsync(member => { N++; console.log(`name of the ${N}th member: ${member.name}`); }); console.log(`loop all ${N} members success`); } test(); ``` 使用[cursor()](https://mongoosejs.com/docs/api.html#query_Query-cursor)方法返回 QueryCursor，然后再使用[eachAsync()](https://mongoosejs.com/docs/api.html#querycursor_QueryCursor-eachAsync)就可以遍历整个集合了，而且不用担心内存不够。 [QueryCursor](https://mongoosejs.com/docs/api.html#QueryCursor)是什么呢？不妨看一下 mongoose 文档： > A QueryCursor is a concurrency primitive for processing query results one document at a time. A QueryCursor fulfills the Node.js streams3 API, in addition to several other mechanisms for loading documents from MongoDB one at a time. 总之，QueryCursor 可以每次从 MongoDB 中取一个 document，这样显然极大地减少了内存使用。 ### 如何测试？这篇博客介绍的内容很简单，但是也很容易被忽视。如果大家测试一下，印象会更加深刻一些。测试代码很简单，大家可以查看[Fundebug/loop-mongodb-big-collection](https://github.com/Fundebug/loop-mongodb-big-collection)。我的测试环境是这样的： - ubuntu 14.04 - mongodb 3.2 - nodejs 10.9.0 **1. 使用 Docker 运行 MongoDB** ```bash sudo docker run --net=host -d --name mongodb daocloud.io/library/mongo:3.2 ``` **2. 使用[mgodatagen](https://github.com/feliixx/mgodatagen)生成测试数据** 使用 mgodatagen，1000 万个 document 可以在 1 分多钟生成！下载 mgodatagen：[https://github.com/feliixx/mgodatagen/releases/download/0.7.3/mgodatagen_linux_x86_64.tar.gz](https://github.com/feliixx/mgodatagen/releases/download/0.7.3/mgodatagen_linux_x86_64.tar.gz) 解压之后，复制到/usr/local/bin 目录即可： ```bash sudo mv mgodatagen /usr/local/bin ``` mgodatagen 的配置文件[mgodatagen-config.json](https://github.com/Fundebug/loop-mongodb-big-collection/blob/master/mgodatagen-config.json)如下： ```json [ { "database": "test", "collection": "members", "count": 10000000, "content": { "name": { "type": "string", "minLength": 2, "maxLength": 8 }, "city": { "type": "string", "minLength": 2, "maxLength": 8 }, "country": { "type": "string", "minLength": 2, "maxLength": 8 }, "company": { "type": "string", "minLength": 2, "maxLength": 8 }, "email": { "type": "string", "minLength": 2, "maxLength": 8 } } } ] ``` 执行`mgodatagen -f mgodatagen-config.json`命令，即可生成 10000 万测试数据。 ```bash mgodatagen -f mgodatagen-config.json Connecting to mongodb://127.0.0.1:27017 MongoDB server version 3.2.13 collection members: done [====================================================================] 100% +------------+----------+-----------------+----------------+ | COLLECTION | COUNT | AVG OBJECT SIZE | INDEXES | +------------+----------+-----------------+----------------+ | members | 10000000 | 108 | _id_ 95368 kB | +------------+----------+-----------------+----------------+ run finished in 1m12.82s ``` 查看 MongoDB，可知新生成的数据有 0.69GB，其实很小，但是使用 find()方法遍历会报错。 ```bash show dbs local 0.000GB test 0.690GB ``` **3. 执行测试代码** 两种不同遍历方法的代码分别位于[test1.js](https://github.com/Fundebug/loop-mongodb-big-collection/blob/master/test1.js)和[test2.js](https://github.com/Fundebug/loop-mongodb-big-collection/blob/master/test2.js)。 ### 参考 - [如何使用 mongoose 对一个 100 万+的 mongodb 的表进行遍历操作](https://cnodejs.org/topic/51508570604b3d512113f1b3) - [Cursors in Mongoose 4.5](https://thecodebarbarian.com/cursors-in-mongoose-45) ### 关于Fundebug [Fundebug](https://www.fundebug.com/)专注于JavaScript、微信小程序、微信小游戏、支付宝小程序、React Native、Node.js和Java线上应用实时BUG监控。自从2016年双十一正式上线，Fundebug累计处理了10亿+错误事件，付费客户有Google、360、金山软件、百姓网等众多品牌企业。欢迎大家[免费试用](https://www.fundebug.com/team/create)！ ![](https://static.fundebug.cn/wechat_slogan.png) ### 版权声明转载时请注明作者[Fundebug](https://www.fundebug.com/)以及本文地址： [https://blog.fundebug.com/2019/03/21/how-to-visit-all-documents-in-a-big-collection-of-mongodb/](https://blog.fundebug.com/2019/03/21/how-to-visit-all-documents-in-a-big-collection-of-mongodb/)