- 1. API with NestJS #1. Controllers, routing and the module structure
- 2. API with NestJS #2. Setting up a PostgreSQL database with TypeORM
- 3. API with NestJS #3. Authenticating users with bcrypt, Passport, JWT, and cookies
- 4. API with NestJS #4. Error handling and data validation
- 5. API with NestJS #5. Serializing the response with interceptors
- 6. API with NestJS #6. Looking into dependency injection and modules
- 7. API with NestJS #7. Creating relationships with Postgres and TypeORM
- 8. API with NestJS #8. Writing unit tests
- 9. API with NestJS #9. Testing services and controllers with integration tests
- 10. API with NestJS #10. Uploading public files to Amazon S3
- 11. API with NestJS #11. Managing private files with Amazon S3
- 12. API with NestJS #12. Introduction to Elasticsearch
- 13. API with NestJS #13. Implementing refresh tokens using JWT
- 14. API with NestJS #14. Improving performance of our Postgres database with indexes
- 15. API with NestJS #15. Defining transactions with PostgreSQL and TypeORM
- 16. API with NestJS #16. Using the array data type with PostgreSQL and TypeORM
- 17. API with NestJS #17. Offset and keyset pagination with PostgreSQL and TypeORM
- 18. API with NestJS #18. Exploring the idea of microservices
- 19. API with NestJS #19. Using RabbitMQ to communicate with microservices
- 20. API with NestJS #20. Communicating with microservices using the gRPC framework
- 21. API with NestJS #21. An introduction to CQRS
- 22. API with NestJS #22. Storing JSON with PostgreSQL and TypeORM
- 23. API with NestJS #23. Implementing in-memory cache to increase the performance
- 24. API with NestJS #24. Cache with Redis. Running the app in a Node.js cluster
- 25. API with NestJS #25. Sending scheduled emails with cron and Nodemailer
- 26. API with NestJS #26. Real-time chat with WebSockets
- 27. API with NestJS #27. Introduction to GraphQL. Queries, mutations, and authentication
- 28. API with NestJS #28. Dealing in the N + 1 problem in GraphQL
- 29. API with NestJS #29. Real-time updates with GraphQL subscriptions
- 30. API with NestJS #30. Scalar types in GraphQL
- 31. API with NestJS #31. Two-factor authentication
- 32. API with NestJS #32. Introduction to Prisma with PostgreSQL
- 33. API with NestJS #33. Managing PostgreSQL relationships with Prisma
- 34. API with NestJS #34. Handling CPU-intensive tasks with queues
- 35. API with NestJS #35. Using server-side sessions instead of JSON Web Tokens
- 36. API with NestJS #36. Introduction to Stripe with React
- 37. API with NestJS #37. Using Stripe to save credit cards for future use
- 38. API with NestJS #38. Setting up recurring payments via subscriptions with Stripe
- 39. API with NestJS #39. Reacting to Stripe events with webhooks
- 40. API with NestJS #40. Confirming the email address
- 41. API with NestJS #41. Verifying phone numbers and sending SMS messages with Twilio
- 42. API with NestJS #42. Authenticating users with Google
- 43. API with NestJS #43. Introduction to MongoDB
- 44. API with NestJS #44. Implementing relationships with MongoDB
- 45. API with NestJS #45. Virtual properties with MongoDB and Mongoose
- 46. API with NestJS #46. Managing transactions with MongoDB and Mongoose
- 47. API with NestJS #47. Implementing pagination with MongoDB and Mongoose
- 48. API with NestJS #48. Definining indexes with MongoDB and Mongoose
- 49. API with NestJS #49. Updating with PUT and PATCH with MongoDB and Mongoose
- 50. API with NestJS #50. Introduction to logging with the built-in logger and TypeORM
- 51. API with NestJS #51. Health checks with Terminus and Datadog
- 52. API with NestJS #52. Generating documentation with Compodoc and JSDoc
- 53. API with NestJS #53. Implementing soft deletes with PostgreSQL and TypeORM
- 54. API with NestJS #54. Storing files inside a PostgreSQL database
- 55. API with NestJS #55. Uploading files to the server
- 56. API with NestJS #56. Authorization with roles and claims
- 57. API with NestJS #57. Composing classes with the mixin pattern
- 58. API with NestJS #58. Using ETag to implement cache and save bandwidth
- 59. API with NestJS #59. Introduction to a monorepo with Lerna and Yarn workspaces
- 60. API with NestJS #60. The OpenAPI specification and Swagger
- 61. API with NestJS #61. Dealing with circular dependencies
- 62. API with NestJS #62. Introduction to MikroORM with PostgreSQL
- 63. API with NestJS #63. Relationships with PostgreSQL and MikroORM
- 64. API with NestJS #64. Transactions with PostgreSQL and MikroORM
- 65. API with NestJS #65. Implementing soft deletes using MikroORM and filters
- 66. API with NestJS #66. Improving PostgreSQL performance with indexes using MikroORM
- 67. API with NestJS #67. Migrating to TypeORM 0.3
- 68. API with NestJS #68. Interacting with the application through REPL
- 69. API with NestJS #69. Database migrations with TypeORM
- 70. API with NestJS #70. Defining dynamic modules
- 71. API with NestJS #71. Introduction to feature flags
- 72. API with NestJS #72. Working with PostgreSQL using raw SQL queries
- 73. API with NestJS #73. One-to-one relationships with raw SQL queries
- 74. API with NestJS #74. Designing many-to-one relationships using raw SQL queries
- 75. API with NestJS #75. Many-to-many relationships using raw SQL queries
- 76. API with NestJS #76. Working with transactions using raw SQL queries
- 77. API with NestJS #77. Offset and keyset pagination with raw SQL queries
- 78. API with NestJS #78. Generating statistics using aggregate functions in raw SQL
- 79. API with NestJS #79. Implementing searching with pattern matching and raw SQL
- 80. API with NestJS #80. Updating entities with PUT and PATCH using raw SQL queries
- 81. API with NestJS #81. Soft deletes with raw SQL queries
- 82. API with NestJS #82. Introduction to indexes with raw SQL queries
- 83. API with NestJS #83. Text search with tsvector and raw SQL
- 84. API with NestJS #84. Implementing filtering using subqueries with raw SQL
- 85. API with NestJS #85. Defining constraints with raw SQL
- 86. API with NestJS #86. Logging with the built-in logger when using raw SQL
- 87. API with NestJS #87. Writing unit tests in a project with raw SQL
- 88. API with NestJS #88. Testing a project with raw SQL using integration tests
- 89. API with NestJS #89. Replacing Express with Fastify
- 90. API with NestJS #90. Using various types of SQL joins
- 91. API with NestJS #91. Dockerizing a NestJS API with Docker Compose
- 92. API with NestJS #92. Increasing the developer experience with Docker Compose
- 93. API with NestJS #93. Deploying a NestJS app with Amazon ECS and RDS
- 94. API with NestJS #94. Deploying multiple instances on AWS with a load balancer
- 95. API with NestJS #95. CI/CD with Amazon ECS and GitHub Actions
- 96. API with NestJS #96. Running unit tests with CI/CD and GitHub Actions
- 97. API with NestJS #97. Introduction to managing logs with Amazon CloudWatch
- 98. API with NestJS #98. Health checks with Terminus and Amazon ECS
- 99. API with NestJS #99. Scaling the number of application instances with Amazon ECS
- 100. API with NestJS #100. The HTTPS protocol with Route 53 and AWS Certificate Manager
- 101. API with NestJS #101. Managing sensitive data using the AWS Secrets Manager
- 102. API with NestJS #102. Writing unit tests with Prisma
- 103. API with NestJS #103. Integration tests with Prisma
- 104. API with NestJS #104. Writing transactions with Prisma
- 105. API with NestJS #105. Implementing soft deletes with Prisma and middleware
- 106. API with NestJS #106. Improving performance through indexes with Prisma
- 107. API with NestJS #107. Offset and keyset pagination with Prisma
- 108. API with NestJS #108. Date and time with Prisma and PostgreSQL
- 109. API with NestJS #109. Arrays with PostgreSQL and Prisma
- 110. API with NestJS #110. Managing JSON data with PostgreSQL and Prisma
- 111. API with NestJS #111. Constraints with PostgreSQL and Prisma
- 112. API with NestJS #112. Serializing the response with Prisma
- 113. API with NestJS #113. Logging with Prisma
- 114. API with NestJS #114. Modifying data using PUT and PATCH methods with Prisma
- 115. API with NestJS #115. Database migrations with Prisma
- 116. API with NestJS #116. REST API versioning
- 117. API with NestJS #117. CORS – Cross-Origin Resource Sharing
- 118. API with NestJS #118. Uploading and streaming videos
- 119. API with NestJS #119. Type-safe SQL queries with Kysely and PostgreSQL
- 120. API with NestJS #120. One-to-one relationships with the Kysely query builder
- 121. API with NestJS #121. Many-to-one relationships with PostgreSQL and Kysely
- 122. API with NestJS #122. Many-to-many relationships with Kysely and PostgreSQL
- 123. API with NestJS #123. SQL transactions with Kysely
- 124. API with NestJS #124. Handling SQL constraints with Kysely
- 125. API with NestJS #125. Offset and keyset pagination with Kysely
- 126. API with NestJS #126. Improving the database performance with indexes and Kysely
- 127. API with NestJS #127. Arrays with PostgreSQL and Kysely
- 128. API with NestJS #128. Managing JSON data with PostgreSQL and Kysely
- 129. API with NestJS #129. Implementing soft deletes with SQL and Kysely
- 130. API with NestJS #130. Avoiding storing sensitive information in API logs
- 131. API with NestJS #131. Unit tests with PostgreSQL and Kysely
- 132. API with NestJS #132. Handling date and time in PostgreSQL with Kysely
- 133. API with NestJS #133. Introducing database normalization with PostgreSQL and Prisma
- 134. API with NestJS #134. Aggregating statistics with PostgreSQL and Prisma
- 135. API with NestJS #135. Referential actions and foreign keys in PostgreSQL with Prisma
- 136. API with NestJS #136. Raw SQL queries with Prisma and PostgreSQL range types
- 137. API with NestJS #137. Recursive relationships with Prisma and PostgreSQL
- 138. API with NestJS #138. Filtering records with Prisma
- 139. API with NestJS #139. Using UUID as primary keys with Prisma and PostgreSQL
- 140. API with NestJS #140. Using multiple PostgreSQL schemas with Prisma
- 141. API with NestJS #141. Getting distinct records with Prisma and PostgreSQL
- 142. API with NestJS #142. A video chat with WebRTC and React
- 143. API with NestJS #143. Optimizing queries with views using PostgreSQL and Kysely
- 144. API with NestJS #144. Creating CLI applications with the Nest Commander
- 145. API with NestJS #145. Securing applications with Helmet
- 146. API with NestJS #146. Polymorphic associations with PostgreSQL and Prisma
- 147. API with NestJS #147. The data types to store money with PostgreSQL and Prisma
- 148. API with NestJS #148. Understanding the injection scopes
- 149. API with NestJS #149. Introduction to the Drizzle ORM with PostgreSQL
- 150. API with NestJS #150. One-to-one relationships with the Drizzle ORM
- 151. API with NestJS #151. Implementing many-to-one relationships with Drizzle ORM
- 152. API with NestJS #152. SQL constraints with the Drizzle ORM
- 153. API with NestJS #153. SQL transactions with the Drizzle ORM
- 154. API with NestJS #154. Many-to-many relationships with Drizzle ORM and PostgreSQL
- 155. API with NestJS #155. Offset and keyset pagination with the Drizzle ORM
- 156. API with NestJS #156. Arrays with PostgreSQL and the Drizzle ORM
- 157. API with NestJS #157. Handling JSON data with PostgreSQL and the Drizzle ORM
- 158. API with NestJS #158. Soft deletes with the Drizzle ORM
- 159. API with NestJS #159. Date and time with PostgreSQL and the Drizzle ORM
- 160. API with NestJS #160. Using views with the Drizzle ORM and PostgreSQL
- 161. API with NestJS #161. Generated columns with the Drizzle ORM and PostgreSQL
- 162. API with NestJS #162. Identity columns with the Drizzle ORM and PostgreSQL
- 163. API with NestJS #163. Full-text search with the Drizzle ORM and PostgreSQL
- 164. API with NestJS #164. Improving the performance with indexes using Drizzle ORM
- 165. API with NestJS #165. Time intervals with the Drizzle ORM and PostgreSQL
- 166. API with NestJS #166. Logging with the Drizzle ORM
- 167. API with NestJS #167. Unit tests with the Drizzle ORM
- 168. API with NestJS #168. Integration tests with the Drizzle ORM
- 169. API with NestJS #169. Unique IDs with UUIDs using Drizzle ORM and PostgreSQL
- 170. API with NestJS #170. Polymorphic associations with PostgreSQL and Drizzle ORM
- 171. API with NestJS #171. Recursive relationships with Drizzle ORM and PostgreSQL
- 172. API with NestJS #172. Database normalization with Drizzle ORM and PostgreSQL
- 173. API with NestJS #173. Storing money with Drizzle ORM and PostgreSQL
- 174. API with NestJS #174. Multiple PostgreSQL schemas with Drizzle ORM
- 175. API with NestJS #175. PUT and PATCH requests with PostgreSQL and Drizzle ORM
- 176. API with NestJS #176. Database migrations with the Drizzle ORM
- 177. API with NestJS #177. Response serialization with the Drizzle ORM
When our application grows, so does the database. At some point, we might return a lot of data from our endpoints. It might prove to be too much for our frontend application to process, for example. Therefore, we might need to paginate our records by returning just a portion of them. This article explores different ways of achieving that with MongoDB and Mongoose and considers their pros and cons.
You can find the code from this article in this repository.
Using skip and limit
The most straightforward form of pagination is expecting the users to provide how many documents they want to skip. Also, they can declare how many documents they want to receive.
To successfully implement pagination, we need a predictable order of documents. To achieve that, we must sort them:
posts.service.ts
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import { Model } from 'mongoose'; import { Injectable } from '@nestjs/common'; import { InjectModel } from '@nestjs/mongoose'; import { Post, PostDocument } from './post.schema'; @Injectable() class PostsService { constructor(@InjectModel(Post.name) private postModel: Model<PostDocument>) {} async findAll() { return this.postModel .find() .sort({ _id: 1 }) .populate('author') .populate('categories'); } // ... } export default PostsService; |
By doing sort({ _id: 1 }), we sort in an ascending order.
Above, we use an important feature of ids in MongoDB. The id in MongoDB consists of 12 bytes, 4 of them being the timestamp. While doing so, we need to be aware of some disadvantages:
- the timestamp value is measured in seconds, and documents created within the same second do not have a guaranteed valid order,
- the id is generated by clients that might have different system clocks.
Sorting by the _id has a significant advantage because MongoDB creates a unique index on the _id field. This increases the performance of sorting the documents by _id.
Implementing the pagination
The first step to implement the above approach is to allow the user to provide the offset and limit through query params. To do that, let’s use the class-validator and class-transformer.
paginationParams.ts
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import { IsNumber, Min, IsOptional } from 'class-validator'; import { Type } from 'class-transformer'; export class PaginationParams { @IsOptional() @Type(() => Number) @IsNumber() @Min(0) skip?: number; @IsOptional() @Type(() => Number) @IsNumber() @Min(1) limit?: number; } |
If you want to know more about the class-validator and class-transformer, check out Error handling and data validation and Serializing the response with interceptors.
We can now use the above params in our controller:
posts.controller.ts
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import { Controller, Get, Query, UseInterceptors } from '@nestjs/common'; import PostsService from './posts.service'; import MongooseClassSerializerInterceptor from '../utils/mongooseClassSerializer.interceptor'; import { Post as PostModel } from './post.schema'; import { PaginationParams } from '../utils/paginationParams'; @Controller('posts') @UseInterceptors(MongooseClassSerializerInterceptor(PostModel)) export default class PostsController { constructor(private readonly postsService: PostsService) {} @Get() async getAllPosts(@Query() { skip, limit }: PaginationParams) { return this.postsService.findAll(skip, limit); } // ... } |
Now we can use the above arguments in the findAll method.
posts.service.ts
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async findAll(documentsToSkip = 0, limitOfDocuments?: number) { const query = this.postModel .find() .sort({ _id: 1 }) .skip(documentsToSkip) .populate('author') .populate('categories'); if (limitOfDocuments) { query.limit(limitOfDocuments); } return query; } |
Thanks to doing that, the users can now specify how many posts they want to fetch and how many to skip. For example, requesting /posts?skip=20&limit=10 results in ten posts while omitting the first twenty documents.
Counting the documents
A common approach is to display how many pages of posts we have. To do that, we need to count how many documents we have in the database. To do that, we either need to use the aggregation framework or perform two separate queries.
posts.service.ts
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async findAll(documentsToSkip = 0, limitOfDocuments?: number) { const findQuery = this.postModel .find() .sort({ _id: 1 }) .skip(documentsToSkip) .populate('author') .populate('categories'); if (limitOfDocuments) { findQuery.limit(limitOfDocuments); } const results = await findQuery; const count = await this.postModel.count(); return { results, count }; } |
Now in our response, we have both the results and the total number of documents.
Disadvantages
The solution of using the limit and offset is very widely used both with SQL databases and MongoDB. Unfortunately, its performance leaves room for improvement. Using the skip() method still requires the database to scan from the beginning of the collection. First, the database sorts all of the documents by id. Then, MongoDB drops the specified number of documents. This might prove to be quite a lot of work with big collections.
Besides the performance issues, we need to consider consistency. Ideally, the document should appear in results only once. This might not be the case:
- the first user fetches page number one with posts,
- right after that, the second user creates a new post – after sorting, it ends up on page number one,
- the first user fetches the second page.
The user sees the last element of the first page again on the second page. Unfortunately, the user also missed the element that was added to the first page, which is even worse.
Advantages
The approach with the limit and the offset is common and straightforward to implement. Its big advantage is that it is straightforward to skip multiple pages of documents. Also, it is straightforward to change the column used for sorting, including sorting by multiple columns. Therefore, it can be a viable solution if the expected offset is not too big and the inconsistencies are acceptable.
Keyset pagination
If we care a lot about the performance, we might want to look for an alternative to the above approach. One of them is the keyset pagination. Here, we use the fact that the ids in MongoDB consist of timestamps and can be compared:
- we fetch a page of documents from the API,
- we check the id of the last document,
- then, we request documents with ids greater than the id of the last document.
Thanks to the above approach, the database no longer needs to process unnecessary documents. First, let’s create a way for the user to provide the starting id.
paginationParams.ts
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import { IsNumber, IsMongoId, Min, IsOptional } from 'class-validator'; import { Type } from 'class-transformer'; export class PaginationParams { @IsOptional() @IsMongoId() startId?: string; @IsOptional() @Type(() => Number) @IsNumber() @Min(0) skip?: number; @IsOptional() @Type(() => Number) @IsNumber() @Min(1) limit?: number; } |
Now, we need to use the startId property in our service.
posts.service.ts
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async findAll( documentsToSkip = 0, limitOfDocuments?: number, startId?: string, ) { const findQuery = this.postModel .find({ _id: { $gt: startId, }, }) .sort({ _id: 1 }) .skip(documentsToSkip) .populate('author') .populate('categories'); if (limitOfDocuments) { findQuery.limit(limitOfDocuments); } const results = await findQuery; const count = await this.postModel.count(); return { results, count }; } |
Thanks to doing $gt: startId, the user receives only the posts created after the post with the provided id.
Disadvantages
A big drawback of the keyset pagination is the need to know the exact document we want to start with. We can overcome this issue by combining it with offset-based pagination. Another issue with this approach is that it would be difficult for the user to skip multiple data pages at once.
Advantages
The most significant advantage of the keyset pagination is the performance improvement compared to the offset-based approach. Also, it helps solve the issue of inconsistency where the user adds or removes elements between fetching pages.
Summary
In this article, we’ve compared two types of pagination with MongoDB and Mongoose. We’ve considered both the disadvantages and advantages of the keyset pagination and the offset-based approach. Neither of them are perfect, but combining them covers a lot of different cases. It is crucial to choose the right tool for the given job.