Introducing: A search & relevancy assessment from engineers, not theorists. Learn more
Sep 16, 2024
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25
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In this post, we’ll walk through a NestJS application that tracks your favorite movie titles, which also happen to be the set of movie titles uploaded to Kaggle by Cornell University in their Movie Dialog Corpus.
Throughout this series, we'll walk through some of the problems that you'll encounter as you deploy and manage a growing search database: things like keeping your search database in-sync with your relational database, creating pipelines, and more.
If you're here, you already know that search is essential to delivering a fast and intuitive experience for your users. Whether you're handling product catalogs, user-generated content, or large datasets, adding search to your NestJS application can take your app to the next level. Finding the right tools to get started can be a little time-consuming, though, so we're working on a series of tutorials to help navigate the path from zero to one.
We're going to start at day 0: demonstrating how to easily integrate Elasticsearch or OpenSearch into your NestJS app and seed it with a static dataset from your application.
Today, we'll be working with a back-end Node.js application built with the progressive NestJS framework. For those unfamiliar, NestJS has grown in popularity in-part due to its opinionated and modular nature. While we'll cover other back-end frameworks in the future, Nest's opinionated nature also lends itself to being a fantastic starting point for our series.
To get started, you'll need to clone our example code repository at https://github.com/omc/bonsai-examples!
Once you've cloned the repository, check out the <span class="inline-code"><pre><code>nestjs/pre-search</code></pre></span> branch - we'll work our way forwards to parity with the `nestjs/with-elasticsearch branch in the coming sections!
# Fetch the remote git branches
git fetch
# Switch to the nestjs/pre-search branch
git switch nestjs/pre-search
Finally, enter the <span class="inline-code"><pre><code>back-end/nestjs</code></pre></span> directory: this appropriately named directory is where we'll spend the duration of the tutorial in!
Our simple application is primarily, and only, responsible for serving up details about our favorite movies. We can find an individual movie's metadata if we know its exact title, or we can see all of the movies' data if we paginate over a series of responses.
The code responsible for handling this functionality lives within the movies module.
# src/movies/
src/movies/
├── domain
│ └── movie.ts
├── dto
│ ├── create-movie.dto.ts
│ ├── query-movie.dto.ts
│ └── update-movie.dto.ts
├── infrastructure
│ └── persistence
│ ├── movie.repository.ts
│ └── relational
│ ├── entities
│ │ └── movie.entity.ts
│ ├── mappers
│ │ └── movie.mapper.ts
│ ├── relational-persistence.module.ts
│ └── repositories
│ └── movie.repository.ts
├── movies.controller.ts
├── movies.module.ts
└── movies.service.ts
What we're interested in, specifically, is the fact that our <span class="inline-code"><pre><code>movies.controller.ts</code></pre></span> currently only supports two actions to fetch our movies:
Our goal is simple, yet powerful: augment our application to allow us to search for a partial title match!
Now that we've got a little familiarity with the application's structure, let's go ahead and configure our development environment and start running the development server.
cp ./env-example ./.env
npm install
# To run this detached, run `docker compose up -d postgres`, but beware of silent failures!
docker compose up postgres
npm run migration:run
npm run seed:run:relational
npm run start:dev
Phew! After all of that, you should see terminal output similar to:
To confirm that your application is serving up the data we expect, try issuing a request to list a page of all of our favorite movies:
curl localhost:3000/api/v1/movies
You should see a response like the following:
Which is great, because I need to pull up the details on a really great movie. But, I just can't seem to find it via exact-search. I think it's called, "The Third Element":
curl -I localhost:3000/api/v1/movies/the%third%20element
We'll see that it's either not there (unlikely), or I've misremembered the name (likely):
If only there was a way to get a search integrated into my application to help me remember some of my favorite movie titles...
With our application running, it's time to supercharge our application with a bit of search magic.
We'll be using Docker again to host the latest addition to our application stack: Elasticsearch.
From the following snippet of code, add the Elasticsearch service definition to your <span class="inline-code"><pre><code>docker-compose.yml</code></pre></span> file:
# Apache License v2.0, January 2004
# Courtesy of the CNCF project, Jaeger @ https://github.com/jaegertracing/jaeger
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:7.10.2
environment:
- discovery.type=single-node
- http.host=0.0.0.0
- transport.host=127.0.0.1
- xpack.security.enabled=false # Disable security features
- xpack.security.http.ssl.enabled=false # Disable HTTPS
- action.destructive_requires_name=false
- xpack.monitoring.collection.enabled=false # Disable monitoring features
ports:
- "9200:9200"
Once you've saved that file, start both the <span class="inline-code"><pre><code>postgres</code></pre></span> and <span class="inline-code"><pre><code>elasticsearch</code></pre></span> services:
docker compose up postgres elasticsearch
And add these environment variables to your <span class="inline-code"><pre><code>.env</code></pre></span> file:
ELASTICSEARCH_NODE=http://localhost:9200
ELASTICSEARCH_USERNAME=elastic
ELASTICSEARCH_PASSWORD=
Since, at this stage of our application, we know all of our favorite movies ahead-of-time, we're going to pursue a straight-forward approach to synchronizing our search and relational databases: after we've inserted all of our favorite movies into the relational database, we'll turn-around and insert them into our search database as well - the catch being that they'll hold the same <span class="inline-code"><pre><code>id</code></pre></span> attribute in both databases, making our search query results directly referential in our relational database!
Before we move into code, let's add a couple of relevant dependencies to our application:
npm add @nestjs/elasticsearch @elastic/elasticsearch@7.13.0
And, we'll add relevant Elasticsearch connection configuration in <span class="inline-code"><pre><code>src/database/</code></pre></span>, alongside our PostgreSQL configuration, by creating a few files:
// src/database/config/search-config.type.ts
export type SearchAuth = {
username?: string;
password?: string;
};
export type SearchConfig = {
node?: string;
auth: SearchAuth;
};
// src/database/config/search.config.ts
import { ConfigModule, ConfigService, registerAs } from '@nestjs/config';
import { ElasticsearchModuleAsyncOptions } from '@nestjs/elasticsearch';
import { IsOptional, IsString, ValidateIf } from 'class-validator';
import validateConfig from '../../utils/validate-config';
import { SearchConfig } from './search-config.type';
class EnvironmentVariablesValidator {
@ValidateIf((envValues) => !envValues.ELASTICSEARCH_NODE)
@IsString()
ELASTICSEARCH_NODE: string;
@IsString()
@IsOptional()
ELASTICSEARCH_PASSWORD: string;
@IsString()
@IsOptional()
ELASTICSEARCH_USERNAME: string;
}
export const elasticSearchModuleOptions: ElasticsearchModuleAsyncOptions = {
imports: [ConfigModule],
inject: [ConfigService],
useFactory: (configService: ConfigService) => {
const username = configService.get('elasticSearch.auth.username', {
infer: true,
});
const opts = {
node: configService.get('elasticSearch.node', { infer: true }),
};
if (username) {
const authOpts = {
auth: {
username: username,
password: configService.get('elasticSearch.auth.password', {
infer: true,
}),
},
};
return { ...opts, ...authOpts };
}
return opts;
},
};
export default registerAs('elasticSearch', () => {
validateConfig(process.env, EnvironmentVariablesValidator);
return {
node: process.env.ELASTICSEARCH_NODE,
auth: {
username: process.env.ELASTICSEARCH_USERNAME,
password: process.env.ELASTICSEARCH_PASSWORD,
},
};
});
// src/database/search/search.module.ts
import { Module } from '@nestjs/common';
import { ConfigModule } from '@nestjs/config';
import { ElasticsearchModule } from '@nestjs/elasticsearch';
import { elasticSearchModuleOptions } from '../config/search.config';
@Module({
imports: [
ConfigModule,
ElasticsearchModule.registerAsync(elasticSearchModuleOptions),
],
exports: [ElasticsearchModule],
})
export class SearchModule {}
And, last but not least for configuration, we'll need to add the search configuration to our App's module:
// src/app.module.ts
import { Module } from '@nestjs/common';
import { MoviesModule } from './movies/movies.module';
import databaseConfig from './database/config/database.config';
import searchConfig from './database/config/search.config';
import appConfig from './config/app.config';
import { ConfigModule } from '@nestjs/config';
import { TypeOrmModule } from '@nestjs/typeorm';
import { TypeOrmConfigService } from './database/typeorm-config.service';
import { HomeModule } from './home/home.module';
import { DataSource, DataSourceOptions } from 'typeorm';
import { SearchModule } from './database/search/search.module';
const infrastructureDatabaseModule = TypeOrmModule.forRootAsync({
useClass: TypeOrmConfigService,
dataSourceFactory: async (options: DataSourceOptions) => {
return new DataSource(options).initialize();
},
});
@Module({
imports: [
ConfigModule.forRoot({
isGlobal: true,
load: [databaseConfig, searchConfig, appConfig],
envFilePath: ['.env'],
}),
infrastructureDatabaseModule,
MoviesModule,
HomeModule,
SearchModule,
],
})
export class AppModule {}
Now that our application is configured to use Elasticsearch, we can get start writing in our search features. We'll begin by adding an interface that describes our movie-search-response items, in <span class="inline-text">src/movies/interfaces/movie-search-document.interface.ts</span>.
// src/movies/interfaces/movie-search-document.interface.ts
export interface MovieSearchDocument {
id: number;
title: string;
}
Followed by a <span class="inline-code"><pre><code>MoviesSearchService</code></pre></span> service in <span class="inline-text">src/movies/movies-search.service.ts</span> file, which will encapsulate our application's interactions with the search database:
// src/movies/movies-search.service.ts
import { Injectable } from '@nestjs/common';
import { ElasticsearchService } from '@nestjs/elasticsearch';
import { RequestParams } from '@elastic/elasticsearch';
import { MovieEntity } from './infrastructure/persistence/relational/entities/movie.entity';
import { ApiResponse, Context } from '@elastic/elasticsearch/lib/Transport';
import { MovieSearchDocument } from './interfaces/movie-search-document.interface';
@Injectable()
export class MoviesSearchService {
index = 'movies';
constructor(private readonly elasticsearchService: ElasticsearchService) {}
async existsIndex(): Promise {
const request: RequestParams.IndicesExists = {
index: this.index,
};
return this.elasticsearchService.indices.exists(request);
}
async statusIndex(): Promise {
const request: RequestParams.ClusterHealth = {
index: this.index,
};
return this.elasticsearchService.cluster.health(request);
}
async createIndex(): Promise {
const request: RequestParams.IndicesCreate = {
body: {
settings: {
index: {
number_of_shards: 1,
number_of_replicas: 1, // for local development
},
},
},
index: this.index,
};
return this.elasticsearchService.indices.create(request);
}
async indexMovies(movies: MovieEntity[]): Promise {
const idx = this.index;
const body = movies.flatMap((movie) => {
const doc: MovieSearchDocument = { id: movie.id, title: movie.title };
return [{ index: { _index: idx } }, doc];
});
const request: RequestParams.Bulk = {
refresh: true,
body,
};
return this.elasticsearchService.bulk(request);
}
async count(query: string, fields: string[]) {
const {
body: result,
}: ApiResponse<
Record,
Context
> = await this.elasticsearchService.count({
index: this.index,
body: {
query: {
multi_match: {
query,
fields,
},
},
},
});
return result.count;
}
async search(text: string, offset?: number, limit?: number, startId = 0) {
let separateCount = 0;
if (startId) {
separateCount = await this.count(text, ['title']);
}
const params: RequestParams.Search = {
index: this.index,
from: offset,
size: limit,
body: {
query: {
match: {
title: text,
},
},
},
};
const { body: result } = await this.elasticsearchService.search(params);
const count = result.hits.total.value;
const results = result.hits.hits.map((item) => item._source);
return {
count: startId ? separateCount : count,
results,
};
}
}
The <span class="inline-code"><pre><code>MoviesSearchService</code></pre></span> currently provides a just a few of functions that will enable us to load our search database with movies, along with some others that will help us determine the status of our index:
To use this new functionality, we'll take a detour out of our NestJS application modules, and head over to <span class="inline-code"><pre><code>src/database/seeds/</code></pre></span>, where we'll create a new directory: <span class="inline-code"><pre><code>search</code></pre></span>.
This new <span class="inline-code"><pre><code>search</code></pre></span> directory will hold the scripts responsible for seeding our search database with indexes after we've loaded our relational database with movies.
We'll be adding similar files as to what's contained in the <span class="inline-text">src/database/seeds/relational</span> directory, so let's also create a sub-directory within <span class="inline-code"><pre><code>search</code></pre></span>: <span class="inline-text">src/database/seeds/search/movie</span>.
Add these files in:
// src/database/seeds/search/run-seed.ts
import { NestFactory } from '@nestjs/core';
import { SeedModule } from './seed.module';
import { MovieSeedService } from './movie/movie-seed.service';
const runSeed = async () => {
const app = await NestFactory.create(SeedModule);
// run
await app.get(MovieSeedService).run();
await app.close();
};
void runSeed();
// src/database/seeds/search/seed.module.ts
import { Module } from '@nestjs/common';
import { ConfigModule } from '@nestjs/config';
import { MovieSeedModule } from './movie/movie-seed.module';
import appConfig from '../../../config/app.config';
import searchConfig from '../../config/search.config';
import databaseConfig from '../../config/database.config';
import { TypeOrmModule } from '@nestjs/typeorm';
import { TypeOrmConfigService } from '../../typeorm-config.service';
import { DataSource, DataSourceOptions } from 'typeorm';
@Module({
imports: [
MovieSeedModule,
ConfigModule.forRoot({
isGlobal: true,
load: [databaseConfig, searchConfig, appConfig],
envFilePath: ['.env'],
}),
TypeOrmModule.forRootAsync({
useClass: TypeOrmConfigService,
dataSourceFactory: async (options: DataSourceOptions) => {
return new DataSource(options).initialize();
},
}),
],
})
export class SeedModule {}
// src/database/seeds/search/movie/movie-seed.service.ts
import { Injectable } from '@nestjs/common';
import { InjectRepository } from '@nestjs/typeorm';
import { Repository } from 'typeorm';
import { MovieEntity } from '../../../../movies/infrastructure/persistence/relational/entities/movie.entity';
import { MoviesSearchService } from '../../../../movies/movies-search.service';
@Injectable()
export class MovieSeedService {
constructor(
@InjectRepository(MovieEntity)
private repository: Repository,
private moviesSearchService: MoviesSearchService,
) {}
async run() {
// If index doesn't exist, create it and seed the database
const exists = await this.moviesSearchService.existsIndex();
if (!exists.body) {
await this.moviesSearchService.createIndex();
await this.moviesSearchService.statusIndex();
const insertedMovies = await this.repository.find({});
await this.moviesSearchService.indexMovies(insertedMovies);
}
}
}
// src/movies/infrastructure/persistence/movie.repository.ts
...
abstract find(options?: FindManyOptions): Promise;
...
2. And add the <span class="inline-text">implementation</span> to <span class="inline-text">`src/movies/infrastructure/persistence/relational/repositories/movie.repository.ts`</span>:
// src/movies/infrastructure/persistence/relational/repositories/movie.repository.ts
...
async find(options?: FindManyOptions): Promise {
return await this.moviesRepository.find(options);
}
...
// src/database/seeds/search/movie/movie-seed.module.ts
import { Module } from '@nestjs/common';
import { MovieSeedService } from './movie-seed.service';
import { TypeOrmModule } from '@nestjs/typeorm';
import { MovieEntity } from '../../../../movies/infrastructure/persistence/relational/entities/movie.entity';
import { MoviesModule } from '../../../../movies/movies.module';
@Module({
imports: [TypeOrmModule.forFeature([MovieEntity]), MoviesModule],
providers: [MovieSeedService],
exports: [MovieSeedService],
})
export class MovieSeedModule {}
Once we've added this, we'll also add a command-line interface command to our <span class="inline-code"><pre><code>package.json</code></pre></span>, allowing us to trigger the seeding of our search database from the command-line: add the following line to the <span class="inline-code"><pre><code>scripts</code></pre></span> section of your <span class="inline-code"><pre><code>package.json</code></pre></span>:
"seed:run:search": "ts-node -r tsconfig-paths/register ./src/database/seeds/search/run-seed.ts",
And finally, let's go ahead and run that command to seed our search cluster with movie data!
npm run seed:run:search
We won't see much output at the command's terminal, but we can check via the Elasticsearch API to see that our favorite movies have been indexed:
curl "http://localhost:9200/_search?pretty=true&q=*:*"
Which responds something like the below (some metrics and IDs may be different)!
{
"took" : 92,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 617,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "movies",
"_id" : "q_fOxZEB07qVS_LUa0y2",
"_score" : 1.0,
"_source" : {
"id" : 1,
"title" : "10 things i hate about you"
}
},
...
]
}
}
Now that our search database is loaded-up with our favorite movie details, we're ready to create a public interface to that functionality in our application!
Re-open the <span class="inline-code"><pre><code>MoviesService</code></pre></span> service in the <span class="inline-code"><pre><code>src/movies/movies.service.ts</code></pre></span> file, because we're going to be adding one new, important, service:
You'll note that the updated <span class="inline-code"><pre><code>MoviesService</code></pre></span> class has a new constructor and some additional imports - update yours to match the below.
// src/movies/movies.service.ts
import { Injectable } from '@nestjs/common';
import { ElasticsearchService } from '@nestjs/elasticsearch';
import { RequestParams } from '@elastic/elasticsearch';
import { MovieEntity } from './infrastructure/persistence/relational/entities/movie.entity';
import { ApiResponse, Context } from '@elastic/elasticsearch/lib/Transport';
import { MovieSearchDocument } from './interfaces/movie-search-document.interface';
@Injectable()
export class MoviesSearchService {
...
async search(text: string, offset?: number, limit?: number, startId = 0) {
let separateCount = 0;
if (startId) {
separateCount = await this.count(text, ['title']);
}
const params: RequestParams.Search = {
index: this.index,
from: offset,
size: limit,
body: {
query: {
match: {
title: text,
},
},
},
};
const { body: result } = await this.elasticsearchService.search(params);
const count = result.hits.total.value;
const results = result.hits.hits.map((item) => item._source);
return {
count: startId ? separateCount : count,
results,
};
}
...
}
Next, since we want to provide the option of using a search query, but we still want our movies index response to be paginated either way, the query and response types will need to be tweaked slightly:
export class InfinityPaginationResponseDto {
data: T[];
- hasNextPage: boolean;
+ hasNextPage?: boolean;
}
// src/movies/dto/query-movie.ts
export class QueryMovieDto {
@ApiPropertyOptional()
@Transform(({ value }) => (value ? Number(value) : 0))
@Type(() => Number)
@Min(0)
@IsNumber()
@IsOptional()
offset?: number;
@ApiPropertyOptional({ type: String })
@IsOptional()
@Type(() => Number)
@IsNumber()
@Min(1)
startId?: number;
@ApiPropertyOptional()
@Transform(({ value }) => (value ? Number(value) : 1))
@IsNumber()
@IsOptional()
page?: number;
@ApiPropertyOptional()
@Transform(({ value }) => (value ? Number(value) : 10))
@IsNumber()
@IsOptional()
limit?: number;
@ApiPropertyOptional({ type: String })
@IsOptional()
@Transform(({ value }) => {
return value ? plainToInstance(SortMovieDto, JSON.parse(value)) : undefined;
})
@ValidateNested({ each: true })
@Type(() => SortMovieDto)
sort?: SortMovieDto[] | null;
}
// src/utils/dto/search-response.dto.ts
import { ApiProperty } from '@nestjs/swagger';
import { IsArray, IsNumber } from 'class-validator';
export class SearchResponseDto {
@ApiProperty()
@IsArray()
data: T[];
@ApiProperty()
@IsNumber()
count: number;
}
// src/movies/movies.controller.ts
...
@ApiOkResponse({
type: InfinityPaginationResponse(Movie),
})
@Get()
@HttpCode(HttpStatus.OK)
async findAll(
@Query('search') search: string,
@Query() query: QueryMovieDto,
): Promise | SearchResponseDto> {
const page = query?.page ?? 1;
let limit = query?.limit ?? 10;
if (limit > 50) {
limit = 50;
}
if (search) {
return await this.moviesService.search(
search,
query?.offset,
query?.limit,
query?.startId,
);
}
return infinityPagination(
await this.moviesService.findManyWithPagination({
sortOptions: query?.sort,
paginationOptions: {
page,
limit,
},
}),
{ page, limit },
);
}
...
Now, blessedly, let's go ahead and run a query for that favorite movie of mine again, "The Third Element,"
# Start our dev server
npm run start:dev
# Query for our movie
curl localhost:3000/api/v1/movies?search=the%20third%20element
Lo and behold, it's not, "The Third Element,", it's, "The Fifth Element!"
{
"data": [
{
"id": 6,
"title": "the fifth element",
"createdAt": "2024-09-06T07:25:45.588Z",
"updatedAt": "2024-09-06T07:25:45.588Z",
"deletedAt": null,
"__entity": "MovieEntity"
},
{
"id": 24,
"title": "the avengers",
"createdAt": "2024-09-06T07:25:45.669Z",
"updatedAt": "2024-09-06T07:25:45.669Z",
"deletedAt": null,
"__entity": "MovieEntity"
},
{
...
},
...
}
Now that you've added search to your NestJS Application, you're ready to deploy into production! Check out our post, "Heroku and Bonsai, a Winning Search Combination", for a detailed tutorial on how to launch this application onto Heroku, using the Bonsai Heroku Addon!
There are a number of day-1 and day-2 features that we'll want to add into our application to get the most out of the newly-added search capabilities that we'll cover in future posts, so stay tuned for part 2 of this series!
Schedule a free consultation to see how we can create a customized plan to meet your search needs.
