- 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 complexity of our database queries grows together with our application. Due to that, the time necessary to complete the queries. A common way to address this problem is using indexes. In this article, we explore indexes both through MikroORM and SQL queries.
The idea behind indexes
Across the last few articles, we’ve defined a table where we keep posts. Among others, it contains the author_id field.
We might need a routine query to look for posts written by a specific author.
1 |
SELECT * FROM post_entity WHERE author_id = 1; |
We must be aware that the above query needs to scan the entire post_entity table to find matching entities. Sometimes iterating a table from cover to cover might not be good enough performance-wise. We can deal with this issue by creating an index.
The goal of the index is to make our queries faster by creating a data structure that organizes a table using a particular column.
1 |
CREATE INDEX post_entity_author_id_index ON post_entity (author_id); |
The above command creates an index using the author_id column of the post_entity table. We can imagine the index as key and value pairs. In our case, the keys are the author ids, and the values point to particular posts.
author_id | post_id |
---|---|
1 | 1 |
1 | 2 |
1 | 3 |
2 | 4 |
3 | 5 |
In real life, the data structures used by PostgreSQL for indexing are more elaborate to maximze the performance. By default, PostgreSQL uses the B-tree data structure when creating indexes where each leaf contains a pointer to a particular table row.
Thanks to the sorted data structure, we can quickly find all posts written by a particular author. However, besides the noticeable advantage when fetching data, there are some crucial downsides.
Every time we insert or update data, PostgreSQL also needs to update the indexes. While indexes can speed up our SELECT queries, they slow down our inserts and updates. Besides the performance, indexes create data structures that need additional space.
Creating indexes with MikroORM
To create an index using MikroORM, we need to use the @Index() decorator.
post.entity.ts
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 |
import { Entity, PrimaryKey, ManyToOne, Index, } from '@mikro-orm/core'; import User from '../users/user.entity'; import WithSoftDelete from '../utils/withSoftDelete'; @Entity() @WithSoftDelete() class PostEntity { @PrimaryKey() id: number; @ManyToOne() @Index() author: User; // ... } export default PostEntity; |
Adding the above to our schema and running npx mikro-orm migration:create results in the following migration:
Migration20220614231701.ts
1 2 3 4 5 6 7 8 9 10 11 12 13 |
import { Migration } from '@mikro-orm/migrations'; export class Migration20220614231701 extends Migration { async up(): Promise<void> { this.addSql('create index "post_entity_author_id_index" on "post_entity" ("author_id");'); } async down(): Promise<void> { this.addSql('drop index "post_entity_author_id_index";'); } } |
We can use the name option in the @Index() decorator to change the auto-generated name of the index to something else.
Multi-column indexes
Sometimes we might notice that we often make queries with multiple conditions. For example, let’s look for posts authored by a certain user and deleted during the last month.
1 2 |
SELECT * FROM post_entity WHERE author_id = 1 AND deleted_at > NOW() - interval '1 month' |
We can easily create a multi-column index using an SQL query.
1 2 |
CREATE INDEX post_entity_author_id_deleted_at_index ON post_entity (author_id, deleted_at); |
We can achieve the same thing with MikroORM by using the @Index() decorator with the properties argument.
post.entity.ts
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
import { Entity, Property, PrimaryKey, ManyToOne, Collection, ManyToMany, Index, } from '@mikro-orm/core'; import User from '../users/user.entity'; import Category from '../categories/category.entity'; import WithSoftDelete from '../utils/withSoftDelete'; @Entity() @WithSoftDelete() @Index({ properties: ['author', 'deletedAt'] }) class PostEntity { @PrimaryKey() id: number; @Property() title: string; @Property() content: string; @ManyToOne() @Index() author: User; @ManyToMany(() => Category) categories: Collection<Category>; @Index() @Property({ nullable: true, type: 'timestamptz' }) deletedAt?: Date; } export default PostEntity; |
Creating the above index and running npx mikro-orm migration:create generates the following migration:
Migration20220615230639.ts
1 2 3 4 5 6 7 8 9 10 11 12 13 |
import { Migration } from '@mikro-orm/migrations'; export class Migration20220615230639 extends Migration { async up(): Promise<void> { this.addSql('create index "post_entity_author_id_deleted_at_index" on "post_entity" ("author_id", "deleted_at");'); } async down(): Promise<void> { this.addSql('drop index "post_entity_author_id_deleted_at_index";'); } } |
Unique indexes
In one of the previous articles, we’ve defined a table for a user.
One of the columns of the above table is email, which we’ve declared as unique.
1 |
CONSTRAINT user_email_unique UNIQUE (email) |
Whenever we define a unique constraint, PostgreSQL automatically creates a unique index to enforce the constraint.
1 |
CREATE UNIQUE INDEX user_email_unique ON "user" (email); |
We don’t need to manualy create indexes on unique columns, PostgtreSQL does that for us when we define the constraint.
Remember that PostgreSQL also creates the unique constraint and index for primary keys. Because of that, every table has at least one index if it contains a primary key.
Creating unique indexes with MikroORM
To create a unique constraint and index with MikroORM, we can use unique: true along with the @Property() decorator.
user.entity.ts
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 |
import { Entity, Property, PrimaryKey, } from '@mikro-orm/core'; @Entity() class User { @PrimaryKey() id: number; @Property({ unique: true }) email: string; // ... } export default User; |
An alternative approach to the above is using the @Unique() decorator.
user.entity.ts
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 |
import { Entity, Property, PrimaryKey, Unique } from '@mikro-orm/core'; @Entity() class User { @PrimaryKey() id: number; @Property() @Unique() email: string; // ... } export default User; |
Defining the above schema and running npx mikro-orm migration:create causes the following migration to be created:
Migration20220615013946.ts
1 2 3 4 5 6 7 8 9 10 11 12 13 |
import { Migration } from '@mikro-orm/migrations'; export class Migration20220615013946 extends Migration { async up(): Promise<void> { this.addSql('alter table "user" add constraint "user_email_unique" unique ("email");'); } async down(): Promise<void> { this.addSql('alter table "user" drop constraint "user_email_unique";'); } } |
Types of indexes
So far, all the indexes we’ve created in this article used the B-tree data structure. While it fits most of the cases, there are some other options. For example, we can use the expression property of the @Index() decorator to provide an SQL query used to create the index.
Generalized Inverted Indexes (GIN)
GIN indexes fit best where the values contain more than one key. A good example would be the array data type. However, they can also come in handy when implementing text searching.
1 2 3 4 5 6 |
@Property() @Index({ expression: 'CREATE INDEX post_entity_title_index ON post_entity USING GIN (title)', }) title: string; |
Please notice that GIN indexes might not work out of the box.
Hash indexes
Hash index uses the hash table data structure and might come in handy in some specific use-cases.
1 2 3 4 5 6 |
@Property() @Index({ expression: 'CREATE INDEX post_entity_title_index ON post_entity USING hash (title)', }) title: string; |
Block Range Indexes (BRIN)
The Block Range Indexes can come in handy when used with data types that have a linear sort order.
1 2 3 4 5 6 |
@Property() @Index({ expression: 'CREATE INDEX post_entity_title_index ON post_entity USING BRIN (title)', }) title: string; |
Generalized Search Tree (GIST)
The GIST indexes can be helpful when indexing geometric data and implementing text search. In some cases, it might be preferable over GIN.
1 2 3 4 5 6 |
@Property() @Index({ expression: 'CREATE INDEX post_entity_title_index ON post_entity USING GIN (title)', }) title: string; |
Summary
In this article, we’ve gone through indexes and how they can affect the performance of our queries. The above includes improving the performance and, in some cases, making it worse. We’ve also learned how to create indexes through SQL queries and MikroORM. Besides regular indexes, we’ve also created multi-column indexes and used index types other than B-tree. All of the above gives us a solid introduction to how indexes work and what are their pros and cons.