September 2020
Intermediate to advanced
526 pages
8h 23m
Chinese
book
Google SRE工作手册
by Betsy Beyer, Niall Richard Murphy, David K. Rensin, Kent Kawahara, Stephen Thorne
Content preview from Google SRE工作手册
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介绍非抽象大系统设计
｜
279
最后，我们可以使用科学记数法来避免不一致单位造成的运算错误。在
24
小时里生
成的查询日志的数据量为：
（
5
×
10
5
查询
/
秒）×（
8.64
×
10
4
秒
/
天）×（
2
×
10
3
字节）
= 86.4 TB /
天
因为我们获得的点击次数大约是查询数的
2%
，另外我们都知道数据库的索引会增加
一些额外的空间开销，因此，我们可以将
86.4 TB /
天的空间需求，向上舍入为存储
每天的日志数据需要
100 TB
空间。
由于总共的存储需求约为
100 TB
，我们需要做出一些新的假设。这种设计是否仍适
合运行在一台机器上？虽然可以在一台机器上安装
100 TB
的磁盘，但我们可能会受
限于机器读取和写入磁盘的能力。
例如，常见的
4 TB HDD
可能支持每秒
200
次写入
/
读取操作（
IOPS
）。如果每个日
志条目都可以存储下来，并且每一条日志都平均的写入到一个索引磁盘上，我们会
发现
IOPS
是查询日志的限制条件：
（
5
×
10
5
查询
/
秒）
/
（
200 IOPS /
磁盘）
= 2.5
×
10
3
块磁盘或
2,500
块磁盘
即使我们可以用
10
:
1
的比例进行批量查询操作，从而限制查询操作次数，但在最好
的情况下，我们需要数百个
HDD
。考虑到查询日志的写入只是设计输入输出（
IO
）
需求的一个组成部分，我们需要使用比传统
HDD
具有更高
IOPS
处理能力的解决
方案。
为简单起见，我们将直接评估内存（
RAM
）的需求，并跳过其他存储介质的评估，
例如固态硬盘（
SSD
）。单台计算机是无法完全在内存（
RAM
）里处理
100 TB
的存
储空间的：假设我们所使用的标准机器规格为 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.