Google PCA Practice Question: Analysing and Optimising Technical and Business Processes
A company runs a Bigtable instance for real-time analytics. They notice increasing latency for point reads. The row key pattern is 'YYYYMMDD_userID_productID'. The team suspects read hotspots. Which row key design change would BEST distribute the load across tablets?
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
✓
Reorder to 'userID_productID_YYYYMMDD'
Using a field prefix (like user ID) before the timestamp distributes reads across tablets because Bigtable orders rows lexicographically. If the timestamp is first, recent data falls into a single tablet, causing hotspots. Reversing the timestamp or hashing the row key are also common strategies. Salting with a random prefix is another approach.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Prepend a random number field: 'random_YYYYMMDD_userID_productID'
Why it's wrong here
A random prefix distributes writes but makes range scans inefficient. For point reads, it may help distribution but is not optimal for time-range queries.
- ✓
Reorder to 'userID_productID_YYYYMMDD'
Why this is correct
By moving user ID first, reads for a specific user are spread across many tablets. If different users are read concurrently, load is distributed.
- ✗
Keep the same order but use a shorter timestamp: 'YYMMDD_userID_productID'
Why it's wrong here
Shortening the timestamp does not address the hotspot issue; recent dates still cluster together.
- ✗
Reverse the timestamp: 'DDMMYYYY_userID_productID'
Why it's wrong here
Reversing the timestamp does not change the fact that recent timestamps are similar; it may still cause hotspots if users read recent data.
Go deeper
Related to this question
Learn chapter
Load Balancing and Autoscaling
Key term
Row
A row is a horizontal record in a database table that contains all the information about a single entity, like one customer or one product.
Key term
Bigtable
Bigtable is Google's fully managed, scalable NoSQL database service designed for large analytical and operational workloads, handling petabytes of data with low latency.
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