这是一个可行的子目录系统来存储文件吗？
我读过一些地方说你不能将数百万个文件放入一个文件夹中，而且人们通常使用哈希或其他东西创建子目录...我还读过一些内容与删除数据库有关并且仅使用 NTFS 工作。但我需要数据库。
出于我的需要，以及我对编码的（贫乏）知识的限制，我想向您展示我的想法，并请您告诉我它是否可行。
这就是我使用时间来考虑子目录的方式
-> 我的数据/年（无限子目录）/每年每月（12个子目录）/每月每周（4个子目录）/每周几天（7个子目录）/每天小时（ 24 个子目录）/每小时分钟数（60 个子目录）
我认为它的好处是可以更快地访问新数据（因为过去的数据不会与最新的数据混合在一起）并且文件夹很空，已更新 我发现问题是，如果人们在短时间内发送大量数据，
我不知道，这些只是一些想法，也许我应该花时间完全理解哈希子目录，
感谢您的任何启发
I read somwhere that you cannot put millions of files inside a single folder, and it is usual that people create subdirectories using a hash or somthing... I've read also that there is somthing to do with droping database and work only using NTFS. But i need database.
For my needs, and to the limits of my (poor) knowledge about coding I want to show you what I thought of and please you let me know if its viable.
This is how i thought of subdirectories using time
->my data/Year (infinite subdirectories)/ month per year (12 subdirectories)/ week per month (4 subdirectories) / days of a week (7 subdirectories) / hours per day (24 subdirectories) / minutes per hours (60 subdirectories)
What's good about it i think is that new data in time is faster accessed (because whats in the past dont mix with whats up to date) and the folders are quite empty, renewed
I see that the problem would be if people send a lot of data within few time
i don't know, these are just some thought, maybe i should take time and understand hash subdirectories completly
thanks for any enlightnement
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这个问题让我有点害怕:)我看到一个简单的解决方案，将时间戳添加到数据库表中，以便您可以轻松查询与特定日期或日期范围相关的数据。您可以查询仅在过去或仅在未来的数据，或仅在过去但发生在指定日期之后的数据。
这就是为什么关系数据库很棒并替换您建议的文件系统解决方案的原因。
MySQL 可以处理数亿行。 Oracle 可以处理数万亿美元。这就是它们的用途，詹姆斯:)
This question scares me a little :) I see a simple solution being adding timestamps to your database tables so you can easily query your data relevant to a specific date or date range. You could query data which is only in the past or only in the future, or only in the past but occurred after a specified date.
This is why relational databases are great and REPLACE file system solutions like the one you're suggesting.
MySQL can handle hundreds of millions of rows. Oracle can handle trillions. This is what they are meant for, James :)