Percona 對 MongoDB 的建議

看到「5 Things DBAs Should Know Before Deploying MongoDB」這篇,裡面給了五個建議,其中第五點頗有趣:

5) Whenever Possible, Working Set < RAM

As with any database, fitting your data into RAM will allow for faster reads than from disk. MongoDB is no different. Knowing how much data MongoDB has to read in for your queries can help you determine how much RAM you should allocate to your database.

這樣的設計邏輯很奇怪啊,你不要扯其他 database 啊,你們家主力的 InnoDB 一直都沒有推薦要 Working Set < RAM 啊,反過來才是用 InnoDB 的常態吧,而且在 PostgreSQL 上也是這樣吧 XDDD

現在上面的文章真的是挑著看了... XD

MongoDB 的欺騙性廣告

Jepsen 最近丟出了一篇新的測試報告在測新版的 MongoDB 4.2.6,而且語氣看起來比以前兇很多,翻了一下前因後果,看起來起因是出自 Twitter 上的這則推,提到了 MongoDB 拿 Jepsen 宣傳的頁面:

然後 Jepsen 的官方帳號這邊也回應,覺得不可置信:

過兩個禮拜後 Jepsen 就丟出由老大 Kyle Kingsbury 發表的「Jepsen: MongoDB 4.2.6」,這篇測試 MongoDB 4.2.6 最新版的測試報告了。

在這篇報告裡面提到了很多不道德的行為,首先是在之前的測試發現有很多會掉資料的問題,但在 MongoDB 官方的宣傳文件「MongoDB and Jepsen」裡面則是完全沒提到,而且還宣稱有業界最強的資料一致性與正確性 (與 Jepsen 報告所提供的資料不符),所以 Jepsen 建議把這些問題列到這個頁面上,以避免使用者受到「誤解」:

Curiously, MongoDB omitted any mention of these findings in their MongoDB and Jepsen page. Instead, that page discusses only passing results, makes no mention of read or write concern, buries the actual report in a footnote, and goes on to claim:

MongoDB offers among the strongest data consistency, correctness, and safety guarantees of any database available today.

We encourage MongoDB to report Jepsen findings in context: while MongoDB did appear to offer per-document linearizability and causal consistency with the strongest settings, it also failed to offer those properties in most configurations. We think users might want to be aware that their database could lose data by default, but MongoDB’s summary of our work omits any mention of this behavior.

另外當然就是重測 MongoDB 4.2.6 版,沒時間看內容的人可以先瞄一下標題,裡面就已經點出不少東西了:

3 Results
3.1 Sometimes, Programs That Use Transactions… Are Worse
3.2 How ACID is Snapshot Isolation, Anyway
3.3 Indeterminate Errors
3.4 Duplicate Effects
3.5 Read Skew
3.6 Cyclic Information Flow
3.7 Read Your (Future) Writes

不過在最後面的 Discussion 比較清楚。

首先是批評 snapshot isolation 不是 ACID:

MongoDB 4.2.6 claims to offer “full ACID transactions” via snapshot isolation. However, the use of these transactions is complicated by weak defaults, confusing APIs, and undocumented error codes. Snapshot isolation is questionably compatible with the marketing phrase “full ACID”. Even at the highest levels of read and write concern, MongoDB’s transaction mechanism exhibited various anomalies which violate snapshot isolation.

Snapshot isolation is a reasonably strong consistency model, but claiming that snapshot isolation is “full ACID” is questionable.

而且即使把所有的資料安全性相關的設定都調到最高,也根本就做不到宣稱的 snapshot isolation:

Finally, even with the strongest levels of read and write concern for both single-document and transactional operations, we observed cases of G-single (read skew), G1c (cyclic information flow), duplicated writes, and a sort of retrocausal internal consistency anomaly: within a single transaction, reads could observe that transaction’s own writes from the future. MongoDB appears to allow transactions to both observe and not observe prior transactions, and to observe one another’s writes. A single write could be applied multiple times, suggesting an error in MongoDB’s automatic retry mechanism. All of these behaviors are incompatible with MongoDB’s claims of snapshot isolation.

過程中也發現就算設定了 snapshot 層級,MongoDB 在讀取時也不會遵守 snapshot isolation:

MongoDB’s default read and write concern for single-document operations remains local, which can observe uncommitted data, and w: 1, which can lose committed writes. Even when users select safer settings in their clients at the database or collection level, transactions ignore these settings and default again to local and w: 1. The snapshot read concern does not actually guarantee snapshot isolation, and must always be used in conjunction with write concern majority. This holds even for transactions which perform no writes.

然後所有的官方文件都沒有教 snapshot isolation 要怎麼設定,你必須在第三方的文件上才有機會找到:

Nor can users rely on examples to demonstrate snapshot isolated behavior. MongoDB’s transaction documentation and tutorial blog posts show only write-only transactions, using read concern local rather than snapshot. Other examples from MongoDB don’t specify a read concern or run entirely with defaults. Learn MongoDB The Hard Way uses read concern snapshot but write concern local, despite performing writes. Tutorials from DZone, Several Nines, Percona, The Code Barbarian, and Spring.io all claim that transactions are either ACID or offer snapshot isolation, but none set either read or write concern. There are some examples of MongoDB transactions which are snapshot isolated—for instance, from BMC, +N Consulting, and Maciej Zgadzaj, but most uses of MongoDB transactions we found ran—either intentionally or inadvertently—with settings that would (in general) allow write loss and aborted reads.

基本上就是一個老大被惹怒了,丟出來炸,而且看他的語氣還有很多東西沒測,打算要再炸一篇?

在 SQL 裡面避免大量刪除資料的方式

看到 Percona 的「An Overview of Sharding in PostgreSQL and How it Relates to MongoDB’s」這篇,雖然是在講 PostgreSQL 上的 sharding (以及 partition),突然想到好像沒寫過要怎麼避免大量刪除資料的操作...

一個常見的情境是,想要讓某個表格只保留這一個月的資料,所以每個月開頭都會跑一隻 cron job 負責刪掉上個月的資料,像是 DELETE FROM xxx WHERE timestamp < yyy; 這樣的指令。

這個方式無論是在 PostgreSQL 或是 MySQL 都需要很多時間與 I/O 資源,而透過 partition 將不同時間區段切開到不同的表格,再用 TRUNCATE 直接清空表格剛好可以解這樣的問題。

Percona 的文章裡說了一些 PostgreSQL 的歷史與目前的進展。

在 PostgreSQL 9 或更早以前的版本,一個常見的作法是透過 table inheritance 實做 partition,然後用再用 function 實做 INSERT

CREATE TABLE temperature (
  id BIGSERIAL PRIMARY KEY NOT NULL,
  city_id INT NOT NULL,
  timestamp TIMESTAMP NOT NULL,
  temp DECIMAL(5,2) NOT NULL
);

CREATE TABLE temperature_201901 (CHECK (timestamp >= DATE '2019-01-01' AND timestamp <= DATE '2019-01-31')) INHERITS (temperature);
CREATE TABLE temperature_201902 (CHECK (timestamp >= DATE '2019-02-01' AND timestamp <= DATE '2019-02-28')) INHERITS (temperature);
CREATE TABLE temperature_201903 (CHECK (timestamp >= DATE '2019-03-01' AND timestamp <= DATE '2019-03-31')) INHERITS (temperature);

CREATE OR REPLACE FUNCTION temperature_insert_trigger()
RETURNS TRIGGER AS $$
BEGIN
    IF ( NEW.timestamp >= DATE '2019-01-01' AND NEW.timestamp <= DATE '2019-01-31' ) THEN INSERT INTO temperature_201901 VALUES (NEW.*);
    ELSIF ( NEW.timestamp >= DATE '2019-02-01' AND NEW.timestamp <= DATE '2019-02-28' ) THEN INSERT INTO temperature_201902 VALUES (NEW.*);
    ELSIF ( NEW.timestamp >= DATE '2019-03-01' AND NEW.timestamp <= DATE '2019-03-31' ) THEN INSERT INTO temperature_201903 VALUES (NEW.*);
    ELSE RAISE EXCEPTION 'Date out of range!';
    END IF;
    RETURN NULL;
END;
$$
LANGUAGE plpgsql;

在 PostgreSQL 10 之後,就直接支援一些與 partition 相關的設計,像是這樣:

CREATE TABLE temperature (
  id BIGSERIAL NOT NULL,
  city_id INT NOT NULL,
  timestamp TIMESTAMP NOT NULL,
  temp DECIMAL(5,2) NOT NULL
) PARTITION BY RANGE (timestamp);

CREATE TABLE temperature_201901 PARTITION OF temperature FOR VALUES FROM ('2019-01-01') TO ('2019-02-01');
CREATE TABLE temperature_201902 PARTITION OF temperature FOR VALUES FROM ('2019-02-01') TO ('2019-03-01');
CREATE TABLE temperature_201903 PARTITION OF temperature FOR VALUES FROM ('2019-03-01') TO ('2019-04-01');

雖然還是有些限制,但可以看出比起以前簡單不少。

而有了 partition 後,文章的後續就在討論這跟 MongoDB 的 sharding 有什麼關係,但這就不是我關注的事情了...

大家在猜 Amazon DocumentDB 的底層是不是 PostgreSQL...

Amazon DocumentDB 的出現讓人驚訝的倒不是 AWS 推出這塊服務,而是 AWS 對於這類對 PaaS 有攻擊性的 license model 的反擊姿態。這也導致了在 AWS 推出後 MongoDB 的股價掉了 13%。

另外一方面,大家也都想要知道 AWS 怎麼堆底層的系統,畢竟要從頭開發一個所需要的功夫應該不小... (雖然 AWS 應該有這個能力)

從「Is DocumentDB really PostgreSQL?」這邊看到 Hacker News 上的「My bet is that it is built on top of Aurora PostgreSQL.」這篇討論,透過目前 DocumentDB 的限制,大家在猜 Amazon DocumentDB 是不是拿 PostgreSQL 改出來的...

目前看起來 Identifiers 的 63 chars 限制,單一 collection 的 32TB 限制 (對應到表格),以及 UTF-8 null character 限制,都跟 PostgreSQL 一樣。

也許過一陣子 AWS 的人會找個地方透漏,不過目前看起來只能猜...

AWS 推出 MongoDB 服務:Amazon DocumentDB

AWS 推出了 Amazon DocumentDB 服務,相容於 MongoDB 3.4 3.6 的界面:「New – Amazon DocumentDB (with MongoDB Compatibility): Fast, Scalable, and Highly Available」。

這個新聞其實引起不少關注,不單純是 AWS 支援了 MongoDB service,而是 AWS 對去年一系列 license issue 的態度。

先講 license 的事情,後面再提技術上的差異。

背景是 MongoDB 在去年十月的時候決定換 license,決定從 GNU AGPL 換成他們自己定義的 SSPL:「MongoDB now released under the Server Side Public License」。

相關的報導可以參考 TechCrunch 當時寫的「MongoDB switches up its open-source license」,主要的重點在於:

[T]he SSPL explicitly states that anybody who wants to offer MongoDB as a service — or really any other software that uses this license — needs to either get a commercial license or open source the service to give back the community.

而 AWS 在三個月後的回應也意外的清楚,他直接照著 MongoDB 3.6 版的 API 刻一個出來,不需要用你的軟體提供服務 (所以就不用照你的 license 走):

Amazon DocumentDB implements the Apache 2.0 open source MongoDB 3.6 API by emulating the responses that a MongoDB client expects from a MongoDB server, allowing you to use your existing MongoDB drivers and tools with Amazon DocumentDB.

TechCrunch 下的標題也頗直接,認為 AWS 對這套搞法不怎麼認同:「AWS gives open source the middle finger」。

回到技術上的層面來看,可以看到 Amazon DocumentDB 提供的技術資料看起來跟 Amazon Aurora 很像,都是六份三區:

Amazon DocumentDB uses a purpose-built SSD-based storage layer, with 6x replication across 3 separate Availability Zones.

連 read replica 的限制也都是 15 份,可以「猜測」後面應該是用同一套技術在運作...:

In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and developers can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

看了一下價錢,最小台是 db.r4.large,需要 USD$0.277/hr,相當於一個月要 USD$200 左右,而且 storage 與 i/o 要另外計算,門檻不算低。

目前主要還是歐美區先上:

Amazon DocumentDB (with MongoDB compatibility) is available now and you can start using it today in the US East (N. Virginia), US East (Ohio), US West (Oregon), and Europe (Ireland) Regions.

隔壁棚的 Redis 不知道有什麼感想...

MongoDB 的 Index 種類

Percona 的人寫了一篇簡單的文章介紹 MongoDB 的 Index:「MongoDB Indexing Types: How, When and Where Should They Be Used?」。

官方文件的「Indexes」算清楚,不過有些地雷沒講,像是 Unique Indexes 只這樣說:

The unique property for an index causes MongoDB to reject duplicate values for the indexed field. Other than the unique constraint, unique indexes are functionally interchangeable with other MongoDB indexes.

但 Percona 的人就有說出「地雷」,算是不錯的補充教材 XDDD

Unique indexes work as in relational databases. They guarantee that the value doesn’t repeat and raise an error when we try to insert a duplicated value. Unique doesn’t work across shards.

話說前陣子聽到傳言抱怨,MongoDB 的文件是行銷 & 團隊寫出來的,一堆限制都沒寫在明顯的地方... XD

MongoDB 的 consistent backup

PerconaGitHub 上放出 MongoDB 的 consistent backup 工具:「Percona-Lab/mongodb_consistent_backup: 1.0 Release Explained」。

程式碼在「Percona-Lab/mongodb_consistent_backup」這邊,首頁也講了對應的條件。

Percona 在 MongoDB 上投入愈來愈多資源了... (但我還是沒很想用 XD)

eBay 把 MongoDB 當 cache layer 的用法...

在「How eBay’s Shopping Cart used compression techniques to solve network I/O bottlenecks」這邊 eBay 描述了他們怎麼解決在 MongoDB 上遇到的問題,不過我看的是他們怎麼用 MongoDB,而不是這次解決的問題:

It’s easier to think of the MongoDB layer as a “cache” and the Oracle store as the persistent copy. If there’s a cache miss (that is, missing data in MongoDB), the services fall back to recover the data from Oracle and make further downstream calls to recompute the cart.

把 MongoDB 當作 cache layer,當 cache miss 的時候還是會回去底層的 Oracle 撈資料計算,這用法頗有趣的...

不拿 memcached 出來用的原因不知道是為什麼,是要找個有 HA 方案的 cache layer 嗎?還是有針對 JSON document 做判斷操作?

vm.swappiness 設成 1 或是 0 的差異

在「MongoDB System Tuning Best Practices」這份投影片裡面看到:

To avoid disk-based swap: 1 (not zero!)

以及:

‘0’ can cause unpredicted behaviour

在 kernel 的說明文件是這樣描述,設成 0 時表示只有在避免 oom 時才會 swap:

This control is used to define how aggressive the kernel will swap memory pages. Higher values will increase agressiveness, lower values decrease the amount of swap. A value of 0 instructs the kernel not to initiate swap until the amount of free and file-backed pages is less than the high water mark in a zone.

設成 1 的想法頗有趣的,來看看在 MySQL 上是不是也有同樣的情況要注意...

MongoDB 的 replica-set 設定

Percona 的人寫了一份文件,以 MySQL DBA 的角度說明兩者在 replication 上的差異,然後示範怎麼在單機上架起三個 MongoDB 並且設定 replica-set:「First MongoDB replica-set Configuration for MySQL DBAs」。

這邊文章拿的是 Percona Server for MongoDB,不過應該也還行,並竟是拿 MongoDB 3.2 改的,而不是完全重寫,所以裡面的步驟拿到原版的 MongoDB 上應該也行...

可以拿 Docker 或是在 AWS 開一台 t2.medium 測試玩看看...