- 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
The bigger our database, the more we need to care about its performance. A common way of improving it is through indexes. Therefore, this article introduces the idea of indexes and implements them through Prisma.
You can find the code from this article in this repository.
Introduction to indexes
In one of the recent articles, we’ve created a posts table.
postSchema.prisma
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model Post { id Int @default(autoincrement()) @id title String content String author User @relation(fields: [authorId], references: [id]) authorId Int categories Category[] } |
At some point, we might want to allow querying for all posts written by a particular author.
posts.service.ts
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import { Injectable } from '@nestjs/common'; import { PrismaService } from '../prisma/prisma.service'; @Injectable() export class PostsService { constructor(private readonly prismaService: PrismaService) {} getPostsByAuthor(authorId: number) { return this.prismaService.post.findMany({ where: { authorId, }, }); } // ... } |
The crucial thing we need to realize is that the above query has to scan the entire posts table to find the matching records. Let’s run a query that helps us to visualize that.
1 2 3 |
EXPLAIN ANALYZE SELECT * FROM "Post" WHERE "authorId" = 1 |
In the above result, we can see that PostgreSQL performed the sequential scan. If our database is extensive, iterating through it from cover to cover might cause performance issues. To deal with that, we can create an index.
Adding an index
By adding an index, we can organize our table using a particular column. For example, to make the above query faster, let’s add an index on the authorId column by using the @@index keyword.
postSchema.prisma
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model Post { id Int @id @default(autoincrement()) title String content String author User @relation(fields: [authorId], references: [id]) authorId Int categories Category[] @@index([authorId]) } |
Now, we need to use the Prisma CLI to generate a migration.
1 |
npx prisma migrate dev --name add-author-index-to-post |
Running the above command creates a new file in the migrations directory.
migrations/20230428222734_add_author_index_to_post/migration.sql
1 2 |
-- CreateIndex CREATE INDEX "Post_authorId_idx" ON "Post"("authorId"); |
When we add an index, PostgreSQL maintains a data structure organized by a particular column. Let’s imagine the index as key and value pairs.
In our example, the keys are author ids, and the values point to posts.
authorId | postId |
---|---|
1 | 1 |
2 | 2 |
2 | 3 |
3 | 4 |
3 | 5 |
3 | 6 |
The actual data structures used by PostgreSQL are more complex. By default, PostgreSQL implements the B-tree data structure where every leaf points to a table row.
Since PostgreSQL now maintains a data structure sorted by the author’s id, it can quickly find all posts written by a particular author. However, indexes have some important downsides.
While indexes can speed up fetching data with the SELECT queries, they make inserts and updates slower. This is because PostgreSQL needs to update the indexes each time we modify our table. Also, indexes take up additional space in our database.
Multi-column indexes
Some of our queries might have multiple conditions. For example, we might want to find a post written by a particular author with a specific title.
1 2 |
SELECT * FROM "Post" WHERE "authorId" = 1 AND title = 'Hello world!' |
Creating an index either for the authorId or the title columns would speed up the above query. However, if we want to take it a step further, we can create a multi-column index. To do that, we need to provide two column names for the @@index operator.
postSchema.prisma
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model Post { id Int @id @default(autoincrement()) title String content String author User @relation(fields: [authorId], references: [id]) authorId Int categories Category[] @@index([authorId]) @@index([authorId, title]) } |
Unique indexes
In this series of articles, we’ve defined a schema for the user.
userSchema.prisma
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model User { id Int @id @default(autoincrement()) email String @unique name String password String address Address? @relation(fields: [addressId], references: [id]) addressId Int? @unique posts Post[] } |
When doing so, we marked the email column with the @unique keyword. Because of that, each time we insert a new record to the above table, PostgreSQL checks if the new email is unique.
The important thing is that adding a unique constraint causes PostgreSQL to create an index. Because of that, PostgreSQL can quickly search the existing emails to determine if the new value is unique. This index can also benefit the SELECT queries and give them a performance boost.
Types of indexes
So far, our indexes have used the B-tree structure under the hood. It fits most use cases, but we have other options.
Hash indexes
Using the hash table through the hash index might be beneficial for some uses.
userSchema.prisma
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model User { id Int @id @default(autoincrement()) email String @unique name String password String address Address? @relation(fields: [addressId], references: [id]) addressId Int? @unique posts Post[] @@index(fields: [name], type: Hash) } |
Generalized Inverted Indexes (GIN)
The GIN index can come in handy when the value contains more than one key. An example would be the array data type. They can also be helpful when implementing text searching.
userSchema.prisma
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model User { id Int @id @default(autoincrement()) email String @unique name String password String address Address? @relation(fields: [addressId], references: [id]) addressId Int? @unique posts Post[] @@index(fields: [name], type: Gin) } |
To make the GIN index work, we might need to enable the bree_gin and pg_trim extensions first.
1 2 |
CREATE EXTENSION btree_gin; CREATE EXTENSION pg_trgm; |
Block Range Indexes (BRIN)
The Block Range Indexes might be helpful when dealing with data types with linear sort order.
userSchema.prisma
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model User { id Int @id @default(autoincrement()) email String @unique name String password String address Address? @relation(fields: [addressId], references: [id]) addressId Int? @unique posts Post[] @@index(fields: [name], type: Brin) } |
Generalized Search Tree (GIST)
The GIST indexes can be useful when indexing geometric data and implementing text search. In some cases, they might be preferable over GIN.
userSchema.prisma
1 2 3 4 5 6 7 8 9 10 11 |
model User { id Int @id @default(autoincrement()) email String @unique name String password String address Address? @relation(fields: [addressId], references: [id]) addressId Int? @unique posts Post[] @@index(fields: [name], type: Gin) } |
For the GIST indexes to work, we might need to enable the btree_gist extension.
1 |
CREATE EXTENSION btree_gist; |
Summary
This article covered the basics of indexes by implementing examples that improve the performance of various SELECT queries. It also considered both advantages and disadvantages of indexes.
Besides the most basic indexes, we’ve also mentioned indexes that use data structures different than B-tree and multi-column indexes. All of the above serves as an introduction to how to create indexes in Prisma and how indexes work in general.
Hi, nice article! Can you also add the result after adding the authorId index? How fast is it after?
Your tutorial was excellent and has been tremendously helpful to me. I express my gratitude and appreciation for your assistance.