https://github.com/vick-ram/full-text-search

This project works on Ktor + exposed + PostreSQL full-text-search which isn't not supported outside of the box by Ktor
https://github.com/vick-ram/full-text-search

dao exposed full-text-search hikaricp ktor postgresql type-safe-routing

Last synced: 7 months ago
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This project works on Ktor + exposed + PostreSQL full-text-search which isn't not supported outside of the box by Ktor

• Host: GitHub
• URL: https://github.com/vick-ram/full-text-search
• Owner: vick-ram
• Created: 2024-04-27T20:56:14.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2024-04-28T09:53:22.000Z (over 1 year ago)
• Last Synced: 2025-02-01T06:42:24.136Z (8 months ago)
• Topics: dao, exposed, full-text-search, hikaricp, ktor, postgresql, type-safe-routing
• Language: Kotlin
• Homepage:
• Size: 68.4 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
**FULL-TEXT-SEARCH**

- [x] [Full-Text Search](https://www.postgresql.org/docs/current/textsearch-tables.html#TEXTSEARCH-TABLES-SEARCH)

- [x] [Full-Text Search Functions and Operators](https://www.postgresql.org/docs/current/functions-textsearch.html)

The full-text search feature allows you to efficiently search text stored in a PostgreSQL database. The feature includes the following:

- Configurable text search configurations

- Full-text indexing

- Full-text search functions and operators

- Full-text search queries

The full-text search feature is based on the following concepts:

- **Document**: A piece of text to be searched.

- **Lexeme**: A word that has been normalized to its base form. For example, the words "jumping", "jumps", and "jumped" are all normalized to the lexeme "jump".

  - **Token**: A lexeme that is indexed for searching.

  - **Stopword**: A common word that is ignored during full-text search. For example, "the" and "is" are stopwords.

- **Parser**: A function that converts a document into a list of tokens.

The full-text search feature is useful for searching text in the following scenarios:

- **Web search engines**: Search engines use full-text search to search for web pages that contain specific keywords.

- **Document management systems**: Document management systems use full-text search to search for documents that contain specific keywords.

- **E-commerce websites**: E-commerce websites use full-text search to search for products that contain specific keywords.

- **Social media websites**: Social media websites use full-text search to search for posts that contain specific keywords.

- **Chat applications**: Chat applications use full-text search to search for messages that contain specific keywords.

**Technologies Used**

- **PostgreSQL**: A powerful, open-source object-relational database system.

- **pg_trgm**: A PostgreSQL extension that provides functions and operators for text similarity measurement and indexing.

- **Ktor**: A Kotlin-based framework for building asynchronous web applications.

- **Exposed**: A Kotlin SQL framework that provides a type-safe SQL API.

- **HikariCP**: A high-performance JDBC connection pool.

- **Kotlin Coroutines**: A Kotlin feature that allows you to write asynchronous code in a sequential style.

**Features**

- **Full-Text Indexing**: Indexes the text columns in the database to improve search performance.

- **Full-Text Search**: Searches for text in the database using the full-text search feature.

- **Text Similarity**: Measures the similarity between two text values using the pg_trgm extension.

- **Asynchronous Web Application**: Uses Kotlin Coroutines to build an asynchronous web application.

- **Type-Safe SQL API**: Uses Exposed to write type-safe SQL queries in Kotlin.

- **Connection Pooling**: Uses HikariCP to manage JDBC connections efficiently.

**Setup**

To set up the project, you need to have Kotlin and Java installed on your machine. You also need to set the following environment variables for the database connection:  

- `URL`: The JDBC URL of your PostgreSQL database.

- `USER`: The username for your PostgreSQL database.

- `DB_PASSWORD`: The password for your PostgreSQL database.

- `DRIVER`: The JDBC driver class name for your PostgreSQL database.

Once you have these set up, you can initialize the database by calling `DatabaseFactory.init()`. This will set up the connection pool, create the necessary tables and indices, and set up a trigger for updating the full-text search vector.

**API Endpoints**

The project provides the following API endpoints:

- `GET /api/v1/users`: Fetches users based on the provided query parameters. If an email is provided, it fetches the user with the matching email. If a search term is provided, it performs a search for users matching the term. If no parameters are provided, it fetches all users.  

- `POST /api/v1/users`: Creates a new user. The request body should contain the details of the user to be created.  

- `PUT /api/v1/users/{id}`: Updates the user with the provided ID. The request body should contain the updated details of the user.  

- `DELETE /api/v1/users/{id}`: Deletes the user with the provided ID.

**Running the Project**

You can run the project using the Gradle run task. This will start the server and make the API endpoints available for use.