Dataloader 是由 Facebook 推出,能大幅降低数据库的访问频次,经常在 Graphql 场景中使用。
主要通过 2 个机制来降低数据库的访问频次:批处理
和 缓存
。
配合 MySQL 批量查询用户(User 表)的示例代码:
const DataLoader = require('dataloader');
// 自行封装
const { query, format } = require('./mysql');
/*
用户信息 存储在 User 表 和 UserMeta 表中, 通过 uid 字段进行关联
*/
const UserLoader = new DataLoader(
(uids) => {
const sql = format('SELECT t1.*,t2.* FROM USERTABLE t1 LEFT JOIN USERMETATABLE t2 ON t1.uid = t2.uid WHERE t1.uid in (?)', [uids]);
return query(sql).then((rows) => uids.map((uid) => rows.find((row) => row.uid === uid) || new Error(`Row not found: ${uid}`)));
},
{ cache: false }
);
// Usage:
const user1 = UserLoader.load(1);
const user2 = UserLoader.load(2);
const user3 = UserLoader.load(3);
Promise.all([user1, user2, user3]).then((users) => {});
// Or
UserLoader.loadMany([1, 2, 3]).then((users) => {});
以上代码就仅会产生以下一条数据库查询语句:
Executing (default): SELECT t1.*,t2.* FROM USERTABLE t1 LEFT JOIN USERMETATABLE t2 ON t1.uid = t2.uid WHERE t1.uid in (1, 2, 3);
Load 一次,DataLoader 就会把数据缓存在内存,下一次再 load 时,就不会再去访问后台。
DataLoader 缓存的是 promise,而不是具体数据。则意味着:
let user1, user2;
await user1 = UserLoader.load(1);
await user2 = UserLoader.load(1);
assert(user1 !== user2);
// true,这个容易理解
assert(UserLoader.load(1) === userLoader.load(1));
// 还是true,因为是缓存promise
基础使用参考: https://www.jianshu.com/p/fbd1257116b0
以一个稍微复杂一点的嵌套分页查询为例(可以参考 Github API v4 进行研究学习)。
{
repository(owner: "octocat", name: "Hello-World") {
pullRequest(number: 1) {
commits(first: 10) {
totalCount
edges {
node {
commit {
oid
message
}
}
}
}
comments(first: 10) {
totalCount
edges {
cursor
node {
body
author {
login
}
}
}
}
reviews(first: 10, before: "Y3Vyc29yOnYyOpHOABRzYg==", after: "Y3Vyc29yOnYyOpHOANFzxQ==") {
totalCount
edges {
node {
state
}
}
}
}
}
}
该查询中包含多个分页(Connection)。
常规查询:
SELECT count(1) as count FROM TABLE WHERE ?;
SELECT * FROM TABLE WHERE ? LIMIT ? OFFSET ?;
需要两条查询完成一次分页,嵌套分页则根据条目(N)再进行 2*N 次查询。
const CountLoader = new DataLoader((args) => {
const arr = args.map(([TABLE, WHERE]) => [md5(TABLE + JSON.stringify(WHERE)), TABLE, parseArgs(WHERE)]);
return query(
arr
.map(([CODE, TABLE, WHERE]) => format(`SELECT ? as code, COUNT(1) as count FROM ??${WHERE ? ' WHERE ? ' : ''}`, [CODE, TABLE, WHERE]))
.join(' UNION ')
).then((rows) =>
arr.map(([CODE]) => {
const { count = 0 } = rows.find((row) => row.code === CODE) || {};
return count;
})
);
});
CountLoader.loadMany([
['TABLE1', { uid: 1 }],
['TABLE2', { oid: 2 }]
// ...
]);
最终会拼成:
SELECT xxx as code, COUNT(1) as count FROM TABLE1 WHERE xxx
UNION SELECT xxx as code, COUNT(1) as count FROM TABLE2 WHERE xxx
-- ...
一条 SQL 查询,然后再分别根据 code 参数进行回填。
复杂数据的 DataLoader 示例:
/**
* TicketsLoader
* Each arg:
* { time: {before, after}, // Int, Int
* where, // obj: {1:1, type:'xxx'}
* order, // 'DESC' / 'ASC'
* limit // Int
* }
*/
exports.TicketsLoader = new DataLoader(
(args) => {
const result = args.map(({ time: { before, after }, where, order, limit }) => {
let time = [];
if (before) {
time.push(format('createdAt < ?', [before]));
}
if (after) {
time.push(format('createdAt > ?', [after]));
}
if (time.length > 0) {
time = `AND ${time.join(' AND ')}`;
} else {
time = '';
}
let sql;
if (where) {
sql = format(`SELECT * from ?? WHERE ?${time} ORDER BY createdAt ${order} LIMIT ?`, [TICKETTABLE, where, limit]);
} else {
sql = format(`SELECT * from ?? WHERE 1=1${time} ORDER BY createdAt ${order} LIMIT ?`, [TICKETTABLE, limit]);
}
return query(sql);
});
return Promise.all(result);
},
{ cache: false }
);