# Two tables sit on the same source database Canonical URL: Domain: Pipeline Design ยท Difficulty: medium ## Problem Two tables sit on the same source database. customers has 2 million rows that update slowly. orders has 500 million rows growing by 10 million per day. The current pipeline does a full load on both, which is fine for customers and unworkable for orders (the nightly extract has hit 4 hours). The section's spectrum: full load for small reference tables, incremental with a bookmark for large ones. Pick the load strategy by replacing each extract transform with one whose name states the strategy (full reload or bookmark-driven incremental), and add a shared bookmark-store node the incremental extract reads and writes only after a successful run. ## Related - [All practice problems](https://datadriven.io/problems) - [Mock interview mode](https://datadriven.io/interview/two-tables-sit-on-the-same-source-database-customers-has-2-eb65b79f) - [System Design Interview Questions](https://datadriven.io/data-engineering-system-design) - [Data Engineering Interview Prep Guide](https://datadriven.io/data-engineer-interview-prep) - [Daily Challenge](https://datadriven.io/daily) --- Source: DataDriven (https://datadriven.io). 100% free data engineering interview prep. Live code execution against Postgres 16, Python 3.11, and Spark sandboxes. No paywall, no premium tier, no signup gate.