Question 778 of 1,446
Design innovative, scalable, and highly available cloud database solutions →easyMultiple SelectObjective-mapped
PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
An engineer is designing a Bigtable schema for a weather data application. The data is written by thousands of sensors, each generating a reading every minute. Queries typically retrieve all readings for a sensor in a time range. The row key should be designed to avoid hotspots and support these queries. Which two row key components are recommended? (Choose two.)
⚠ Common exam trap
Google often tests the misconception that natural-order timestamps are optimal for time-range queries, but the trap here is that they cause write hotspots in Bigtable, so a reversed timestamp is required to distribute writes while still supporting range scans.
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
✓
Reversed timestamp
Using a reversed timestamp (e.g., Long.MAX_VALUE - timestamp) as part of the row key spreads writes across Bigtable tablets, avoiding hotspots that occur when sensors write sequentially in natural time order. This design also supports efficient range scans for a sensor's data over a time range when combined with a sensor ID prefix.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Sensor ID (raw) as the only key
Why it's wrong here
If sensor ID is the only key, all writes per sensor go to one node.
- ✗
Sensor location as a column
Why it's wrong here
Location is a column, not row key component.
- ✓
Reversed timestamp
Why this is correct
Reversed timestamp spreads writes and allows recent-first queries.
- ✗
Timestamp in natural order
Why it's wrong here
Natural order timestamps cause write hotspots on current time.
- ✓
Hash of sensor ID as prefix
Why this is correct
Salting distributes writes across nodes.
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Last reviewed: Jul 4, 2026
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