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PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
A company is designing a Cloud Bigtable schema for time-series data. The data is written by millions of devices every second. The query patterns are: (1) retrieve the most recent reading for a specific device, (2) retrieve all readings for a device in a time range. Which TWO row key design techniques should the team use to optimize for these patterns? (Choose two.)
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
✓
Use field promotion: put device_id as the first component of the row key
Using a reverse timestamp allows the most recent data to be at the beginning of the row key, making scans for the latest reading efficient. Field promotion ensures that device_id comes first in the row key, enabling efficient prefix scans for all readings of a device. Salting is not needed because device_id already distributes writes if there are many devices.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use salting (hash prefix) to distribute writes
Why it's wrong here
Salting would break the natural ordering needed for prefix scans by device_id.
- ✓
Use field promotion: put device_id as the first component of the row key
Why this is correct
Field promotion ensures that queries for all readings of a device can use a prefix scan.
- ✓
Use a reverse timestamp (e.g., MAX_TIMESTAMP - timestamp) as part of the row key
Why this is correct
Reverse timestamp brings the most recent data to the top, making 'latest reading' queries fast via a limit scan.
- ✗
Use a monotonically increasing timestamp as the first part of the row key
Why it's wrong here
This would cause hotspots and make recent data inefficient to query.
- ✗
Store the entire row as a single column family to reduce overhead
Why it's wrong here
Column families are for organization, not for optimizing read patterns.
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