Redis tutoring

Editor's Notes

1. The Kiss Principle (儉樸原則) 說 ‘Less is more’ (少即是多) 的哲學。KISS is an acronym for the design principle “Keep it simple, Stupid!“ “keep it short and simple” “keep it simple and straightforward“. 簡純 ANSI C 撰寫。 幾乎不依賴第三方函式庫。 memcached 使用 libevent ，程式碼龐大。 Redis 參考 libevent 實現了自己的 epoll event loop 。 KISS 原則 每個數據結構只負責自己應當做的。  簡單 No map-reduce. No indexes. No vector clocks. 單執行緒 No thread context switch. No thread race condition. No other complicated condition  記憶體資料庫，但可永久儲存於硬碟中 記憶體操作資料。 資料可永久儲存於硬碟。 不只是快取伺服器 Queue
2. DevOps.com & ClusterHQ.com所統計 This report is based on the current and planned container usage patterns of 285 respondents. The survey was conducted over the latter half of May 2015.
3. Consider a setup as shown in the preceding image; that is: Master instance with no persistence Slave instance with AOF enabled In this case, the master does not need to perform any background disk operations and is fully dedicated to serve client requests, except for a trivial slave connection. The slave server configured with AOF performs the disk operations. As mentioned before, this file can be used to restore the master in case of a disaster. Persistence in Redis is a matter of configuration, balancing the trade-off between performance, disk I/O, and data durability. If you are looking for more information on persistence in Redis, you will find the article by Salvatore Sanfilippo at http://oldblog.antirez.com/post/redis-persistence-demystified.html interesting.
4. Redis 有很多種移除舊數據的策略，但大多基於「抽樣」。 ✔ 這意謂移除舊數據不是全局最優而是局部最優。 ✔ 當達到 'maxmemory' 上限時，可能造成移除的數據「不 ✔ 夠舊」。 ✔ 使得使用者提前被登出。最糟的是，你可能都不會知道， ✔ 直到使用者開始抱怨 替代方案。 ✔ 使用資料庫為另一儲存後台。 ✔1. 寫入 Session 時，同時寫進 Redis 及資料庫。 ✔2. 讀出 Session 時， Redis 優先，資料庫其次。 ✔ 使用 Redis 3.0 。 ✔ 選擇較大的 'sampling' ( 抽樣數 ) 
5. http://redis.io/commands#string http://redis.io/commands#set http://redis.io/commands#sorted_set http://redis.io/commands#hash http://redis.io/commands#list
6. Teams: SRE (System Reliability Engineering): - 5 people Core Dev (Q&A site) : ~6-7 people Core Dev Mobile: 6 people Careers team that does development solely for the SO Careers product: 7 people
7. 1st: Caching in the browser, CDN, and proxies. 2nd: Using HttpRuntime.Cache. An in-memory, per server cache. 3rd: Redis. 4th: SQL Server Cache. 5th: SSD. For example, every help page is cached. Code to access a page is very terse: Static methods and static classes re used. Really bad from an OOP perspective, but really fast and really friendly towards terse code. All code is directly addressed. Caching is handled by a library layer of Redis and Dapper, a micro ORM. To get around garbage collection problems, only one copy of a class used in templates are created and kept in a cache. Everything is measured, including GC operation, from statistics it is known that layers of indirection increase GC pressure to the point of noticeable slowness. CDN hits vary, since the query string hash is based on file content, it’s only re-fetched on a build. It's typically 30-50 million hits a day for 300 to 600 GB of bandwidth. A CDN is not used for CPU or I/O load, but to help users find answers faster.
8. Why use Redis if you use MS products? gabeech: It's not about OS evangelism. We run things on the platform they run best on. Period. C# runs best on a windows machine, we use IIS. Redis runs best on a *nix machine we use *nix. Overkill as a strategy. Nick Craver on why their network is over provisioned: Is 20 Gb massive overkill? You bet your ass it is, the active SQL servers average around 100-200 Mb out of that 20 Gb pipe. However, things like backups, rebuilds, etc. can completely saturate it due to how much memory and SSD storage is present, so it does serve a purpose. SSDs Rock. The database nodes all use SSD and the average write time is 0 milliseconds. Know your read/write workload. Keeping things very efficient means new machines are not needed often. Only when a new project comes along that needs different hardware for some reason is new hardware added. Typically memory is added, but other than that efficient code and low utilization means it doesn't need replacing. So typically talking about adding a) SSDs for more space, or b) new hardware for new projects. Don’t be afraid to specialize. SO uses complicated queries based on tags, which is why a specialized Tag Engine was developed. Do only what needs to be done. Tests weren’t necessary because an active community did the acceptance testing for them. Add projects only when required. Add a line of code only when necessary. You Aint Gone Need It really works. Reinvention is OK. Typical advice is don’t reinvent the wheel, you’ll just make it worse, by making it square, for example. At SO they don't worry about making a "Square Wheel". If developers can write something more lightweight than an already developed alternative, then go for it. Go down to the bare metal. Go into the IL (assembly language of .Net). Some coding is in IL, not C#. Look at SQL query plans. Take memory dumps of the web servers to see what is actually going on. Discovered, for example, a split call generated 2GB of garbage. No bureaucracy. There’s always some tools your team needs. For example, an editor, the most recent version of Visual Studio, etc. Just make it happen without a lot of process getting in the way. Garbage collection driven programming. SO goes to great lengths to reduce garbage collection costs, skipping practices like TDD, avoiding layers of abstraction, and using static methods. While extreme, the result is highly performing code. When you're doing hundreds of millions of objects in a short window, you can actually measure pauses in the app domain while GC runs. These have a pretty decent impact on request performance. The cost of inefficient code can be higher than you think. Efficient code stretches hardware further, reduces power usage, makes code easier for programmers to understand.
9. Renaming Commands A slightly unusual feature of redis is that you can disable and/or rename individual commands. As per the previous example, this is done via the CommandMap Twemproxy  is a tool that allows multiple redis instances to be used as though it were a single server, with inbuilt sharding and fault tolerance (much like redis cluster, but implemented separately).
10. opserver做了更清晰的展示。 Ops(/sec)  每秒处理量 memory(used)即used_memory_rss(used_memory) used_memory_rss : 从操作系统的角度，返回 Redis 已分配的内存总量（俗称常驻集大小）。这个值和 top 、 ps等命令的输出一致。 used_memory_peak : Redis 的内存消耗峰值（以字节为单位） used_memory : 由 Redis 分配器分配的内存总量，以字节（byte）为单位   Summary是总体概览部分。 Memory是内存使用情况，重要。 persistence 是RDB和AOF的状态。 keyspace key存储的情况，analyze进去可以查看详细分布。 stats  客户端命令的key命中率和处理量 clients 查看有哪个ip(或机器名)过来的连接数多，很方便的定位到那台应用端机器长时间没有释放连接，重要。 slow command log 服务端接受的命令日志。