In this part of the series, we will be designing the whole system which we will be coding in go in the future videos
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Brief Explanation
We will have users interact with out system.
They will be saving their data in the postgres database which is the database we will be using in the backend.
Schema
Table blogs (id, name, content, created_at, updated_at, deleted_at)
Table user (id, username, created_at, updated_at, deleted_at)
Table tag (id, name)
Table blog_user (user_id, blog_id)
Table blog_tag (blog_id, tag_id)
The tables blog_user and blog_tag will be for keeping the relationships.
One user can have many blogs and one blog can have many tags
Architecture
The user will interact with the system. All data will be saved to postgres database.
The data will be synced to elasticsearch in the backend. This sync will take place at regular intervals.
The user will be able to search the data using keywords (which will be fetched from elasticsearch).
Elasticsearch is a highly available nosql database optimised for searching.
We cannot fire
select * from postgres_table where content like %VALUE%
The query above is super costly especially if have 10s of 1000s of blogs.
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