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PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
A company is migrating a MySQL OLTP database to Bigtable for a time-series application. The current schema uses a relational model with normalized tables. Which two actions should the team take when designing the Bigtable schema? (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
✓
Denormalize the data into a single wide-column table.
Bigtable is a NoSQL wide-column store optimized for time-series data. Denormalization (option A) is recommended because it avoids joins and creates a single wide table that enables efficient scans over time ranges. Salting the row key (option C) distributes writes across nodes, preventing hot spotting on heavily written time-series data. Option B is incorrect because Bigtable only supports single-row transactions, not multi-row transactions. Option D is incorrect because Bigtable does not support secondary indexes; queries must rely on row key design. Option E is incorrect because normalization leads to multiple tables, which are inefficient in Bigtable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Denormalize the data into a single wide-column table.
Why this is correct
Denormalization is typical for Bigtable.
- ✗
Maintain transactional integrity using Bigtable transactions.
Why it's wrong here
Bigtable does not support multi-row transactions.
- ✓
Salting the row key to distribute writes across nodes.
Why this is correct
Salting prevents hotspotting.
- ✗
Create secondary indexes on timestamp columns.
Why it's wrong here
Bigtable does not have secondary indexes; queries rely on row key scans.
- ✗
Normalize the schema to reduce data duplication.
Why it's wrong here
Bigtable is denormalized; normalization hurts performance.
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