Full Text Search

Postgres has rich support for full text search functionality, which can be a replacement for more dedicated solutions such as Elasticsearch.

One of the challenges of implementing a Postgres tsvector search index is keeping the index data in sync with changes, especially across tables. Consider a search endpoint for Books, in addition to being able to search for the Book by title, we may also want to search for the Book by the related Author name.

The conventional approach would be to use triggers to react to updates and keep the index in sync, but Joist can improve on the ergonomics of this approach through the use of Reactive Fields.

Adding Search Index Columns

First, we’ll start by creating 2 columns:

A plain text column to derive the search string.
A tsvector type DERIVED column that will cast our text search column to_tsvector.

import { addColumns } from "joist-migration-utils";
import { MigrationBuilder } from "node-pg-migrate";

export async function up(b: MigrationBuilder): Promise<void> {
  addColumns(b, "books", { search: { type: "text" } });

  // Then create a "generated" column, allowing postgres to handle the `to_tsvector` word stemming.
  b.sql(`
    ALTER TABLE books
    ADD COLUMN ts_search tsvector
    GENERATED ALWAYS AS (to_tsvector('english', coalesce(search, ''))) STORED;

    CREATE INDEX ts_search_index ON books USING GIN (ts_search);
  `);
}

Configuring the Reactive Field

We’ll now set up the Book.search field as an Reactive Field within joist-config.json:

{
  "entities": {
    "Book": {
      "fields": {
        "search": { "derived": "async" }
      }
    }
  }
}

And then implement our logic in the Book domain model. This will keep the values we want indexed for search for the Book in sync:

import { ReactiveField, hasReactiveField } from "joist-orm";

readonly search: ReactiveField<Book, string> = hasReactiveField(
  "search",
  { author: ["firstName", "lastName"], title: {} },
  (book) => {
    const author = book.author.get;
    return `${book.title} ${author.firstName} ${author.lastName}`
  },
);

Querying the `tsvector` type `ts_search` Column

// Use the buildQuery method to create a base query to build off of
const query = buildQuery(knex, Book, {});

// Use knex raw methods to craft the search query against the `ts_search` generated column
// and (optionally) sort by the rank
void query
  .whereRaw(`ts_search @@ plainto_tsquery('english', '${searchTerm}')`)
  .orderByRaw(`ts_rank(ts_search, plainto_tsquery('english', '${searchTerm}')) DESC`);

// Then load the books for the custom search query
const books = await em.loadFromQuery(Book, query);