How can a simple pagination destroy your app?

Summary

Key Points

• —The core problem with offset is that the database engine must scan all preceding elements up to the specified offset before applying the limit, making queries progressively slower for deeper pages. 0:44
• —Traditional limit and offset pagination, commonly taught, leads to significant performance degradation when querying deep pages in large datasets. 1:02
• —A benchmark demonstrates that the limit and offset technique takes much longer as the pagination depth increases, with a query for 1 million entries taking 20 milliseconds. 1:22
• —The key set, or cursor, pagination technique is presented as a significantly faster and more efficient alternative for handling large datasets. 1:41
• —Key set pagination works by selecting records that are 'higher than' the `created_at` timestamp or ID of the last record from the previous page, effectively using the last item as a cursor. 2:47
• —To prevent data collisions, it is recommended to use a combination of `created_at` and a unique identifier like `ID` in the `WHERE` clause for the cursor. 3:25
• —For front-end integration, the back-end should return the 'last cursor' (e.g., the timestamp or ID of the last element) along with the data for each page. 3:34
• —The front-end then sends this last cursor in subsequent requests to the back-end, enabling it to efficiently fetch the next set of records starting from that point. 3:57
• —Many companies, including Stripe and GitHub, enhance flexibility by base64 encoding the cursor data, allowing the back-end to decode and process various types of cursor information. 4:06