PDE Storing the Data Practice Question
A data engineer needs to design a Bigtable row key for a time-series IoT application where each device sends data every second. The query pattern is to retrieve all data for a specific device over a time range. Which row key design minimizes hotspots?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
hash(device_id)#timestamp (e.g., a3f2#2024-03-15-10:30:00)
To avoid hotspots (where all writes hit a single tablet server), the row key should start with a hash of the device ID to distribute writes across the cluster, then append the timestamp for range scans.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
device_id#timestamp (e.g., device123#2024-03-15-10:30:00)
Why it's wrong here
Starting with device_id will cause all writes for one device to go to a single tablet, creating a hotspot.
- ✓
hash(device_id)#timestamp (e.g., a3f2#2024-03-15-10:30:00)
Why this is correct
Hashing the device ID distributes writes across tablets, and appending timestamp allows efficient time-range scans.
- ✗
timestamp#device_id (e.g., 2024-03-15-10:30:00#device123)
Why it's wrong here
Starting with timestamp will cause all writes at the same second to hit the same tablet, causing a hotspot.
- ✗
device_type#device_id#timestamp
Why it's wrong here
Starting with device_type doesn't help; if many devices share the same type, it still causes hotspots.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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