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TypeScript ORM for Node.js based on Data Mapper, Unit of Work and Identity Map patterns. Supports MongoDB, MySQL, PostgreSQL and SQLite databases as well as usage with vanilla JavaScript.

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--- title: Virtual Entities --- import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; Virtual entities don't represent any database table. Instead, they dynamically resolve to an SQL query (or an aggregation in MongoDB), allowing to map any kind of results onto an entity. Such entities are meant for read purposes, they don't have a primary key and therefore cannot be tracked for changes. In a way they are similar to (currently unsupported) database views, and you can use them to proxy your native views already. > Virtual entities can contain scalar properties as well as to-one relations (M:1 and 1:1 owners). Such relations are always populated via `select-in` strategy. To define a virtual entity, provide an `expression`, either as a string (SQL query): > You need to use the virtual column names based on current naming strategy. Note the `authorName` property being represented as `author_name` column. <Tabs groupId="entity-def" defaultValue="reflect-metadata" values={[ {label: 'reflect-metadata', value: 'reflect-metadata'}, {label: 'ts-morph', value: 'ts-morph'}, {label: 'EntitySchema', value: 'entity-schema'}, ] }> <TabItem value="reflect-metadata"> ```ts title="./entities/BookWithAuthor.ts" @Entity({ expression: 'select name, age, ' + '(select count(*) from book b where b.author_id = a.id) as total_books, ' + '(select group_concat(distinct t.name) from book b ' + 'join tags_ordered bt on bt.book_id = b.id ' + 'join book_tag t on t.id = bt.book_tag_id ' + 'where b.author_id = a.id ' + 'group by b.author_id) as used_tags ' + 'from author a group by a.id', }) export class BookWithAuthor { @Property() title!: string; @Property() authorName!: string; @Property() tags!: string[]; } ``` </TabItem> <TabItem value="ts-morph"> ```ts title="./entities/BookWithAuthor.ts" @Entity({ expression: 'select name, age, ' + '(select count(*) from book b where b.author_id = a.id) as total_books, ' + '(select group_concat(distinct t.name) from book b ' + 'join tags_ordered bt on bt.book_id = b.id ' + 'join book_tag t on t.id = bt.book_tag_id ' + 'where b.author_id = a.id ' + 'group by b.author_id) as used_tags ' + 'from author a group by a.id', }) export class BookWithAuthor { @Property() title!: string; @Property() authorName!: string; @Property() tags!: string[]; } ``` </TabItem> <TabItem value="entity-schema"> ```ts title="./entities/BookWithAuthor.ts" export interface IBookWithAuthor{ title: string; authorName: string; tags: string[]; } export const BookWithAuthor = new EntitySchema<IBookWithAuthor>({ name: 'BookWithAuthor', expression: 'select name, age, ' + '(select count(*) from book b where b.author_id = a.id) as total_books, ' + '(select group_concat(distinct t.name) from book b ' + 'join tags_ordered bt on bt.book_id = b.id ' + 'join book_tag t on t.id = bt.book_tag_id ' + 'where b.author_id = a.id ' + 'group by b.author_id) as used_tags ' + 'from author a group by a.id', properties: { title: { type: 'string' }, authorName: { type: 'string' }, tags: { type: 'string[]' }, }, }); ``` </TabItem> </Tabs> Or as a callback: <Tabs groupId="entity-def" defaultValue="reflect-metadata" values={[ {label: 'reflect-metadata', value: 'reflect-metadata'}, {label: 'ts-morph', value: 'ts-morph'}, {label: 'EntitySchema', value: 'entity-schema'}, ] }> <TabItem value="reflect-metadata"> ```ts title="./entities/BookWithAuthor.ts" @Entity({ expression: (em: EntityManager) => { return em.createQueryBuilder(Book, 'b') .select(['b.title', 'a.name as author_name', 'group_concat(t.name) as tags']) .join('b.author', 'a') .join('b.tags', 't') .groupBy('b.id'); }, }) export class BookWithAuthor { @Property() title!: string; @Property() authorName!: string; @Property() tags!: string[]; } ``` </TabItem> <TabItem value="ts-morph"> ```ts title="./entities/BookWithAuthor.ts" @Entity({ expression: (em: EntityManager) => { return em.createQueryBuilder(Book, 'b') .select(['b.title', 'a.name as author_name', 'group_concat(t.name) as tags']) .join('b.author', 'a') .join('b.tags', 't') .groupBy('b.id'); }, }) export class BookWithAuthor { @Property() title!: string; @Property() authorName!: string; @Property() tags!: string[]; } ``` </TabItem> <TabItem value="entity-schema"> ```ts title="./entities/BookWithAuthor.ts" export interface IBookWithAuthor{ title: string; authorName: string; tags: string[]; } export const BookWithAuthor = new EntitySchema<IBookWithAuthor>({ name: 'BookWithAuthor', expression: (em: EntityManager) => { return em.createQueryBuilder(Book, 'b') .select(['b.title', 'a.name as author_name', 'group_concat(t.name) as tags']) .join('b.author', 'a') .join('b.tags', 't') .groupBy('b.id'); }, properties: { title: { type: 'string' }, authorName: { type: 'string' }, tags: { type: 'string[]' }, }, }); ``` </TabItem> </Tabs> In MongoDB, you can use aggregations, although it is not very ergonomic due to their nature. Following example is a rough equivalent of the previous SQL ones. > The `where` query as well as the options like `orderBy`, `limit` and `offset` needs to be explicitly handled in your pipeline. ```ts @Entity({ expression: (em: EntityManager, where, options) => { const $sort = { ...options.orderBy } as Dictionary; $sort._id = 1; const pipeline: Dictionary[] = [ { $project: { _id: 0, title: 1, author: 1 } }, { $sort }, { $match: where ?? {} }, { $lookup: { from: 'author', localField: 'author', foreignField: '_id', as: 'author', pipeline: [{ $project: { name: 1 } }] } }, { $unwind: '$author' }, { $set: { authorName: '$author.name' } }, { $unset: ['author'] }, ]; if (options.offset != null) { pipeline.push({ $skip: options.offset }); } if (options.limit != null) { pipeline.push({ $limit: options.limit }); } return em.aggregate(Book, pipeline); }, }) export class BookWithAuthor { @Property() title!: string; @Property() authorName!: string; } ```