Meteor 的订阅和同步很慢 [英] Meteor's subscription and sync are slow

问题描述

我有一个包含 6000 只股票的 10M 文档的集合，股票名称已编入索引.当我订阅一个新股票时，meteor 挂了10多秒，得到了这个股票的大约3000个文件.同样在订阅了几只股票后，meteor 以 100% 的 CPU 使用率挂起.Meteor 在同步大"集合时看起来真的很慢.实际上我的应用程序只是只读的.我想知道是否有办法为只读客户端加速流星?我还想知道为每只股票创建一个单独的集合是否有帮助?

I have a collection with 10M documents of 6000 stocks, stock name is indexed. When I subscribe to a new stock, meteor hangs more than 10 seconds to get about 3000 documents of this stock. Also after several stocks are subscribed, meteor hangs with 100% cpu usage. Meteor looks really slow with syncing "big" collection. Actually my app just read only. I am wondering if there is way to speed up meteor for read-only client? I am also wondering if creating a separate collection for each stock helps?

推荐答案

虽然这是一个规模问题，可能可以改进；应该注意的是，您的任务使用了错误的技术，因为 Meteor 用于客户端之间的交互，而不是用于检索大量只读时间敏感数据.虽然状态跟踪屏幕可能仍然有些意义，但大量的时间关键数据肯定不会......

While this is a scale issue and probably can be improved; it should be noted that you are using the wrong technology for your task, because Meteor is meant for interaction between clients and not for retrieving tons of read-only time sensitive data. While a status tracking screen might still somewhat make sense, time critical data in huge amounts certainly does not...

整个 Meteor 堆栈比任何原生堆栈中的简单实现都引入了极大的开销；老实说，我什至会考虑 Java 或 C# 引入的开销，并在选择 Java 或 C# 和 PHP 和 C++ 等低级语言时三思而后行.Ruby、Python、Node.js 等语言确实是另一回事；它们是为快速原型设计而设计的，但在延迟/吞吐量方面，由于 JIT 所需的开销，它们落后了，不要忘记增加一些非本地方法的开销.

The whole Meteor stack introduces an extreme overhead over a simple implementation in any native stack; honestly, I would even take into account the overheads Java or C# would introduce and think twice when choosing between that and low level languages like PHP and C++. Languages like Ruby, Python, Node.js and more are really a different story; they're made for rapid prototyping but in terms of latency / throughput they are behind due to the overhead it takes to JIT them, not to forget at the overhead some non-native approaches to doing things add.

TL;DR:使用正确的工具来完成这项工作，否则你会割伤手指...

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