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Answer SQL And Data Warehouse Fundamentals For A Data Engineering Interview

ClickhouseData Engineer · Technical Screen
MediumData EngineerTechnical ScreenData Manipulation (SQL/Python)

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This problem tests foundational knowledge of SQL set operations, performance optimization techniques for join operations, and the architectural principles behind building scalable data warehouses.

Part 1: SQL Set Operations and Joins

Imagine you have two tables, active_sensors and backup_sensors, both containing a sensor_id (INT) column.

  1. Explain the performance difference between UNION and UNION ALL. Under what specific conditions would you prefer one over the other in a large-scale data warehouse?
  2. Provide a SQL query to identify sensor_ids present in active_sensors that do not exist in backup_sensors. Ensure your solution is NULL-safe (i.e., if a sensor ID is NULL, handle it explicitly).

Part 2: Windowing and Analytics

Given a table sensor_readings with columns sensor_id, reading_value (FLOAT), and timestamp (TIMESTAMP), write a query to retrieve the top 3 highest reading_value entries for each sensor_id within the last 24 hours.

-- Example Input:
-- sensor_id | reading_value | timestamp
-- 1         | 98.5          | 2023-10-01 10:00:00
-- 1         | 99.2          | 2023-10-01 10:05:00
-- 1         | 97.0          | 2023-10-01 09:00:00
-- 2         | 50.1          | 2023-10-01 10:10:00

Part 3: Data Warehouse Modeling

You are tasked with designing a system to store high-frequency telemetry data.

  1. Describe the difference between a Fact Table and a Dimension Table in a Star Schema.
  2. How would you handle a 'Slowly Changing Dimension' (SCD Type 2) if a sensor undergoes a major maintenance overhaul that changes its metadata (e.g., location, manufacturer) without changing the sensor_id?

Hints

Hint 1

Consider that UNION performs a distinct operation on the resulting set, requiring a sort or hash aggregate, whereas UNION ALL preserves all rows.

Hint 2

For the top-N problem, utilize the DENSE_RANK() or ROW_NUMBER() window functions partitioned by the identifier.

Hint 3

For SCD Type 2, think about adding surrogate keys and validity timestamps (start_date/end_date) to track historical versions of a record.

Follow-up questions

  • How would you optimize the `UNION` query if you knew the two datasets were disjoint by design?
  • If the `sensor_readings` table grows to petabyte scale, what partitioning strategy would you suggest for the underlying table?
  • How does the choice of a columnar storage engine affect the performance of your top-N query compared to a traditional row-store database?