Virtual Entities

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.

reflect-metadata

./entities/BookWithAuthor.ts

@Entity({
  expression: `
    select b.title, a.name as author_name,
    (
      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 tags
    from author a
    group by a.id
  `
})
export class BookWithAuthor {

  @Property()
  title!: string;

  @Property()
  authorName!: string;

  @Property()
  tags!: string[];

}

ts-morph

./entities/BookWithAuthor.ts

@Entity({
  expression: `
    select b.title, a.name as author_name,
    (
      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 tags
    from author a
    group by a.id
  `
})
export class BookWithAuthor {

  @Property()
  title!: string;

  @Property()
  authorName!: string;

  @Property()
  tags!: string[];

}

EntitySchema

./entities/BookWithAuthor.ts

export interface IBookWithAuthor{
  title: string;
  authorName: string;
  tags: string[];
}

export const BookWithAuthor = new EntitySchema<IBookWithAuthor>({
  name: 'BookWithAuthor',
  expression: `
    select b.title, a.name as author_name,
    (
      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 tags
    from author a
    group by a.id
  `,
  properties: {
    title: { type: 'string' },
    authorName: { type: 'string' },
    tags: { type: 'string[]' },
  },
});

Or as a callback:

reflect-metadata

./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[];

}

ts-morph

./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[];

}

EntitySchema

./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[]' },
  },
});

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.

@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;

}