Google Like Search and Autocomplete with MongoDB, Nextjs, Nodejs, and Material UI
This is a tutorial on how to implement Google like search into your application. This is often referred to as full text search with SQL databases. This allows the user to search for an item, and have similar items suggested to them. In addition to this, you'll learn how to implement fuzzy searching, which will allow the user to misspell words and get accurate suggestions. The tech stack that I used to do this was MongoDB, Nextjs, Nodejs, and Material UI. However, you can use whatever you like for the frontend and backend technologies. You really only need to use MongoDB to set up the database and search indexes.
Link to the code: https://github.com/JeremyPersing/mong...
Link to Dataset (Too large for Github): https://drive.google.com/file/d/1IMSn...
Documentation and Resources used:
https://docs.atlas.mongodb.com/atlas-...
• Building an Autocomplete Form Element...
• $search vs $regex vs $text: The Best ...
https://mui.com/components/autocomple...
Timestamps
0:00 - 0:20 Intro
0:21 - 3:24 Creating a database in MongoDB
3:25 - 9:19 Starting on a Nodejs backend
9:20 - 13:00 Creating search indexes with MongoDB
13:01 - 19:00 Finishing backend
19:01 - 23:20 Creating frontend components for first autocomplete method
23:20 - 24:09 First autocomplete demo
24:10 - 25:15 Creating frontend components for second autocomplete method
25:16 - 26:20 Demo and Comparison
26:21 - 27:16 Handling a suggestion being clicked
27:17 - 27:37 Demo
27:38 - 27:48 Outro
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