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ElastiCache 支援 r4.* 了

每年 AWS re:Invent 要到的時候就會有很多新的消息出來,Amazon ElastiCache 的團隊應該也是配合著這一波放出消息:「Amazon ElastiCache Now Supports the R4 Node Family」。

包括了 memcachedRedis 都支援了:

Amazon ElastiCache now supports R4 node types. R4 nodes are optimized for latency sensitive and memory intensive workloads. They come in six sizes, providing 12.3GiB to 407GiB of available in-memory capacity. By setting up a 15-shard cluster for Redis, you can scale up to 6.1TiB of in-memory capacity. For Memcached, you can set up a 20-node cluster to support up to 8.14 TiB in-memory workloads. Equipped with the Intel Broadwell processor, and improved networking, R4 node family offers superior performance over the popular R3 node family.

這兩個應用都是看記憶體吃飯的...

Reddit 在處理 Page View 的方式

Reddit 說明了他們如何處理 pageview:「View Counting at Reddit」。

以 Reddit 的規模有提到兩個重點,第一個在善用 RedisHyperLogLog 這個資料結構,當量大的時候其實可以允許有微小的誤差:

The amount of memory varies per implementation, but in the case of this implementation, we could count over 1 million IDs using just 12 kilobytes of space, which would be 0.15% of the original space usage!

維基百科上有說明當資料量在 109 這個等級時,用 1.5KB 的記憶體只有 2% 的誤差值:

The HyperLogLog algorithm is able to estimate cardinalities of > 109 with a typical error rate of 2%, using 1.5 kB of memory.

第二個則是寫入允許短時間的誤差 (pageview 不會即時反應),透過批次處理降低對 Cassandra cluster 的負荷:

Writes to Cassandra are batched in 10-second groups per post in order to avoid overloading the cluster.

可以注意到把 Redis 當作 cache 層而非 storage 層。

主要原因應該跟 Redis 定位是 data structure server 而非 data structure storage 有關 (可以從對 Durability 的作法看出來),而使用 Cassandra 存 key-value 非常容易 scale,但讀取很慢。剛好兩個相輔相成。

GitHub 重新定位 Redis 的功能...

GitHub Engineering 說明了他們為什麼改變 Redis 的使用情境:「Moving persistent data out of Redis」。

GitHub 裡面,Redis 有兩種不同的情境,一種叫做 transient Redis,只用做 cache:

We used it as an LRU cache to conveniently store the results of expensive computations over data originally persisted in Git repositories or MySQL. We call this transient Redis.

另外一種則是打開 persistence 功能,叫做 persistent Redis:

We also enabled persistence, which gave us durability guarantees over data that was not stored anywhere else. We used it to store a wide range of values: from sparse data with high read/write ratios, like configuration settings, counters, or quality metrics, to very dynamic information powering core features like spam analysis. We call this persistent Redis.

這邊講的是 persistent Redis 被換成用 MySQL (InnoDB) 儲存:

Recently we made the decision to disable persistence in Redis and stop using it as a source of truth for our data. The main motivations behind this choice were to:

  • Reduce the operational cost of our persistence infrastructure by removing some of its complexity.
  • Take advantage of our expertise operating MySQL.
  • Gain some extra performance, by eliminating the I/O latency during the process of writing big changes on the server state to disk.

For the majority of callsites, we replaced persistent Redis with GitHub::KV, a MySQL key/value store of our own built atop InnoDB, with features like key expiration. We were able to use GitHub::KV almost identically as we used Redis: from trending repositories and users for the explore page, to rate limiting to spammy user detection.

後面講了不少轉換的過程 (還包含了某些功能的改寫),但沒有講的太清楚為什麼不繼續使用 Redis。

目前只能就提到的三點問題來看,persistent 的 i/o 成本可能太高?而且難以再壓榨效能出來?而相反的,InnoDB 已經花了很多力氣在上面,直接拿來用反而可以解決問題?

不過看得出來這個轉換還是花了不少力氣,看得出來有些 application 使用 Redis 的模式不能直接搬到 InnoDB 上,花了時間改寫...

Netflix 開發的 Delayed Queue

原來這個叫做 Delayed Queue,難怪之前用其他關鍵字都找不到什麼資料... (就不講其他關鍵字了 XD)

Netflix 發表了他們自己所開發的 Delayed Queue:「Distributed delay queues based on Dynomite」。

本來的架構是用 Cassandra + Zookeeper 來做:

Traditionally, we have been using a Cassandra based queue recipe along with Zookeeper for distributed locks, since Cassandra is the de facto storage engine at Netflix.

但可以馬上想到不少問題,就如同 Netflix 提到的:

Using Cassandra for queue like data structure is a known anti-pattern, also using a global lock on queue while polling, limits the amount of concurrency on the consumer side as the lock ensures only one consumer can poll from the queue at a time.

所以就改放到 Netflix 另外開發的 Dynamite 上:

Dynomite, inspired by Dynamo whitepaper, is a thin, distributed dynamo layer for different storage engines and protocols. Currently these include Redis and Memcached. Dynomite supports multi-datacenter replication and is designed for high availability.

後端是 RedisMemcached 的系統,可以對抗整個機房從 internet 上消失的狀態。

在設計上則是「保證會跑一次」,也就是有可能會有多次的情況,用 Dyno Queues 系統的人必需要考慮進去:

4. At-least-once delivery semantics

雖然整篇講的頗輕鬆,但實際看起來還是很厚重... 暫時還是不會用吧 :o

對各類 Message Queue 的效能測試

在「Benchmarking Message Queue Latency」這篇看到作者測了一輪 Message Queue 軟體:

RabbitMQ (3.6.0), Kafka (0.8.2.2 and 0.9.0.0), Redis (2.8.4) pub/sub, and NATS (0.7.3)

測試包括了從一個 9 到六個 9 的 latency (i.e. 90%、99%、99.9%、99.99%、99.999%、99.9999%),另外也測了 message 大小帶來的效能差異。

99.9% 表示 1/1000,而 99.99% 表示 1/10000,如果差距跟 90% 很大,表示系統反應時間會很不一致。另外有些 Message Queue 軟體有 disk persistence 的功能,也因為寫入資料,會看到更大的差距。

善用或是避開這些特性去規劃才能減少問題,像是關掉 disk persistence 之類的方法。

Redis 的 Secondary Indexing

Redis 官方說明 Secondary Indexing 的文件:「Secondary indexing with Redis」。

Secondary Indexing 算是 RDBMS 最底層基礎功能,如果有了這個功能已經可以做非常多事情... 查了文章裡提到的 Z* 系列指令是在 3.0.2 支援的 (目前是 3.0.4),看起來這個功能很新,不知道實際上跑起來跟 PostgreSQL 拼的效能如何... (因為 PostgreSQL 也可以自訂 Index 的內容)

真正的 Redis Cluster

也是積了很久的文章,Redis 的其中一位老大 Salvatore Sanfilippo 在第一個公開 Redis Cluster 功能的 3.0.0-rc1 版寫下了 Redis Cluster 的發展過程:「Redis cluster, no longer vaporware.」。

MySQL InnoDB 可以保證極強的 ACID 特性,配合 DRBD 這類的 HA 架構,可以保證 server 回了成功後一定不會掉資料。

memcached 則是 Shared nothing architecture,當初設計就是拿來當 cache,資料隨便掉沒關係。

兩者中間還是有很大的空間,而 Redis Cluster 的出現有機會入場看看情況了,不知道能不能在 InnoDB 與 memcached 中間找到適合的點立足。

測試 GitLab 的方式...

除了在「doc/install/installation.md」有手動安裝的方式外,在「GitLab CE Downloads」有提供 Ubuntu 12.04 LTS 64bits 的 deb 檔可以安裝。

官方在「GitLab Omnibus project」提供的安裝方式是:

apt-get install openssh-server postfix
dpkg -i ooxx.deb
gitlab-ctl reconfigure

不過在 Docker 裡面會卡在設定 redis 的部份而無法成功,卡在:

Recipe: gitlab::redis
  * user[gitlab-redis] action create (up to date)
  * directory[/var/log/gitlab/redis] action create (up to date)
  * directory[/var/opt/gitlab/redis] action create (up to date)
  * template[/var/opt/gitlab/redis/redis.conf] action create (up to date)
  * directory[/opt/gitlab/sv/redis] action create (up to date)
  * directory[/opt/gitlab/sv/redis/log] action create (up to date)
  * directory[/opt/gitlab/sv/redis/log/main] action create (up to date)
  * template[/opt/gitlab/sv/redis/run] action create (up to date)
  * template[/opt/gitlab/sv/redis/log/run] action create (up to date)
  * file[/opt/gitlab/sv/redis/down] action delete (up to date)
  * link[/opt/gitlab/init/redis] action create (up to date)
  * link[/opt/gitlab/service/redis] action create (up to date)
  * ruby_block[supervise_redis_sleep] action run

後來是用 Vagrant (跑 VirtualBox) 才測試成功。就可以看到 PostgreSQLRedis 整包都被放到 /opt 下了...

提供給要玩 GitLab 的人參考看看...

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