Windows上的Mongodb性能 [英] Mongodb performance on Windows

问题描述

我最近一直在研究可用于.NET的nosql选项，而MongoDB在可用性和支持方面已成为明显的赢家，所以今晚我决定尝试一下.我从mongodb网站下载了1.2.4版本(Windows x64二进制)，并使用以下选项运行它:

I've been researching nosql options available for .NET lately and MongoDB is emerging as a clear winner in terms of availability and support, so tonight I decided to give it a go. I downloaded version 1.2.4 (Windows x64 binary) from the mongodb site and ran it with the following options:

C:\mongodb\bin>mkdir data
C:\mongodb\bin>mongod -dbpath ./data --cpu --quiet

然后，我从 http://github.com/samus/加载了最新的mongodb-csharp驱动程序mongodb-csharp ，然后立即运行基准测试程序.听说MongoDB有多惊人的快"后，我对基准性能不佳感到震惊.

I then loaded up the latest mongodb-csharp driver from http://github.com/samus/mongodb-csharp and immediately ran the benchmark program. Having heard about how "amazingly fast" MongoDB is, I was rather shocked at the poor benchmark performance.

Starting Tests
encode (small).........................................320000 00:00:00.0156250
encode (medium)........................................80000 00:00:00.0625000
encode (large).........................................1818 00:00:02.7500000
decode (small).........................................320000 00:00:00.0156250
decode (medium)........................................160000 00:00:00.0312500
decode (large).........................................2370 00:00:02.1093750
insert (small, no index)...............................2176 00:00:02.2968750
insert (medium, no index)..............................2269 00:00:02.2031250
insert (large, no index)...............................778 00:00:06.4218750
insert (small, indexed)................................2051 00:00:02.4375000
insert (medium, indexed)...............................2133 00:00:02.3437500
insert (large, indexed)................................835 00:00:05.9843750
batch insert (small, no index).........................53333 00:00:00.0937500
batch insert (medium, no index)........................26666 00:00:00.1875000
batch insert (large, no index).........................1114 00:00:04.4843750
find_one (small, no index).............................350 00:00:14.2812500
find_one (medium, no index)............................204 00:00:24.4687500
find_one (large, no index).............................135 00:00:37.0156250
find_one (small, indexed)..............................352 00:00:14.1718750
find_one (medium, indexed).............................184 00:00:27.0937500
find_one (large, indexed)..............................128 00:00:38.9062500
find (small, no index).................................516 00:00:09.6718750
find (medium, no index)................................316 00:00:15.7812500
find (large, no index).................................216 00:00:23.0468750
find (small, indexed)..................................532 00:00:09.3906250
find (medium, indexed).................................346 00:00:14.4375000
find (large, indexed)..................................212 00:00:23.5468750
find range (small, indexed)............................440 00:00:11.3593750
find range (medium, indexed)...........................294 00:00:16.9531250
find range (large, indexed)............................199 00:00:25.0625000
Press any key to continue...

对于初学者，我可以从SQL Server Express获得更好的非批处理插入性能.但是，真正令我震惊的是find_nnnn查询的性能缓慢.为什么从MongoDB检索数据这么慢?我想念什么?

For starters, I can get better non-batch insert performance from SQL Server Express. What really struck me, however, was the slow performance of the find_nnnn queries. Why is retrieving data from MongoDB so slow? What am I missing?

编辑:这一切都在本地计算机上，没有网络延迟或其他任何东西.在测试运行的整个过程中，MongoDB的CPU使用率约为75％.另外，我在基准程序上进行了跟踪，并确认花费了50％的CPU时间正在等待MongoDB返回数据，因此C#驱动程序不是性能问题.

This was all on the local machine, no network latency or anything. MongoDB's CPU usage ran at about 75% the entire time the test was running. Also, I ran a trace on the benchmark program and confirmed that 50% of the CPU time spent was waiting for MongoDB to return data, so it's not a performance issue with the C# driver.

推荐答案

我也确实运行了该基准测试.那段代码有很多错误.例如，创建索引失败，但是吞噬了异常，因此搜索仍然很慢.

I did run that benchmark too. That piece of code has a lot of bugs. The creation of the index for instance fails but the exception is swallowed so the search is still slow.

但也请注意，大对象有很多详细对象".它是一个层次结构，而不是单个记录.一份文件有280条详细的记录".将如此大的文档与来自rdbms表(如sql server)的一行进行比较是不公平的.

But also be aware that the large object has a lot of "detail objects". It is a hierarchy, not a single record. One document has 280 detail 'records'. It is unfair to compare such large document with one row from an rdbms table like sql server.

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