# Vendure Better Search Plugin

[Official documentation here](https://plugins.pinelab.studio/plugin/vendure-plugin-better-search)

This plugin offers more intuitive search than Vendure's `DefaultSearchPlugin` before the need of an external platform like TypeSense or ElasticSearch.

This plug is meant for small to medium sized shops with up to ~10000 variants.

# Goals

1. Performant in memory search, without affecting customer facing API calls.
2. Provide relevant, type-tolerant (fuzzy matching) search results, while still meeting goal 1
3. Extensible with custom fields, custom field weighting.

This plugin is not meant to be a replacement for ElasticSearch or TypeSense, but rather a lightweight alternative for small to medium sized shops. If you want to test if it works for you, give it a try and run the load tests we have included.

Features:

- Search by term or multiple terms, no and/or logic or query syntax.
- Fuzzy matching / type tolerance
- Extendable with custom fields
- Index field weighting
- Filtering by facets (faceted search): Planned feature, not implemented yet.

## Getting started

1. Add the plugin to your `vendure-config.ts`:

```ts
import { BetterSearchPlugin } from '@pinelab/vendure-plugin-better-search';

...
plugins: [
  BetterSearchPlugin,
],
```

2. Run a database migration
3. Start the server
4. Do a search via the new `betterSearch` query. The very first time, this will throw an error, and it will start building the index in the background.

```graphql
query Search {
  betterSearch(input: { term: "dumbbells" }) {
    totalItems
    items {
      productId
      slug
      productName
      productAsset {
        id
        preview
      }
      lowestPrice
      lowestPriceWithTax
      highestPrice
      highestPriceWithTax
      facetValueIds
      collectionIds
      collectionNames
    }
  }
}
```

⚠️ Set the env variable `BETTER_SEARCH_INDEX_COLUMN_TYPE` for your specific database! Without this, `text` is used as default, but this will be too small for most projects. **Run a database migration after setting this env variable!**

```bash
# For MySQL
BETTER_SEARCH_INDEX_COLUMN_TYPE=mediumblob

# For PostgreSQL
BETTER_SEARCH_INDEX_COLUMN_TYPE=bytea
```

Checkout this page on more information on the different column types: https://orkhan.gitbook.io/typeorm/docs/entities#column-types-for-mysql-mariadb

## Custom fields

You can add custom fields by defining a custom `mapToSearchDocument` function together with a custom `indexableFields` object.

For example, we have a custom field `keywords` on our products, and we want to index it, and return it in the search results:

```ts
import {
  BetterSearchResult,
  defaultSearchConfig,
  BetterSearchConfigInput,
} from '@pinelab/vendure-plugin-better-search';

// Define an interface for our custom search result
interface MySearchResult extends BetterSearchResult {
  keywords: string[];
}

export const searchConfig: BetterSearchConfigInput<MySearchResult> = {
  mapToSearchDocument: (product, collections) => {
    // Use the default mapping to get the base document
    const defaultDocument = defaultSearchConfig.mapToSearchDocument(
      product,
      collections
    );
    return {
      ...defaultDocument,
      // Extend the base document with "keywords"
      keywords: product.customFields.keywords,
    };
  },
  indexableFields: {
    ...defaultSearchConfig.indexableFields,
    // Add "keywords" to the index with a weight of 2,
    keywords: {
      weight: 2,
      // Tell the GraphQL schema that "keywords" is a [String!]!
      // If you do not specify the graphqlFieldType, the field will not be returned in the search results
      graphqlFieldType: "[String!]!",
    },
  },
};

// Then in your vendure-config.ts, use the searchConfig:
plugins: [
  BetterSearchPlugin.init({
    searchConfig,
  }),
],
```

Checkout the `defaultSearchConfig.ts` for the default weights of each field.

## Tips

- Add a custom field `keywords` to your products, and make the plugin index it. This is where you'd save keywords, synonyms, etc. This will drastically improve the search experience.
- Don't index descriptions unless you really have to, to save on memory usage. Also, most of the shops will have a better search experience when the description is not indexed, since the descriptions usually also contain a lot of noise.
- Monitor your workers memory usage and database CPU usage. If any of these are high, you can increase the `debounceIndexRebuildMs` to reduce the number of rebuilds. If that doesn't work, your dataset might be too large for this search.

# Load test

// TODO