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PCDE Practice Question: Which TWO actions improve query performance and…
Which TWO actions improve query performance and reduce cost in BigQuery for BI workloads?
⚠ Common exam trap
Google Cloud often tests the misconception that any data loading method (batch vs. streaming) or any file format (CSV) directly improves query performance, when in fact only storage and query-time optimizations like partitioning and clustering reduce bytes scanned.
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
✓
Cluster tables on columns used in GROUP BY
Clustering tables on columns used in GROUP BY improves query performance by physically co-locating rows with similar values, reducing the amount of data scanned during aggregation. Partitioning on columns frequently used in WHERE clauses allows BigQuery to prune entire partitions from the scan, directly reducing both cost (bytes billed) and query execution time. These two optimizations are specifically recommended for BI workloads where repeated, selective queries are common.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Cluster tables on columns used in GROUP BY
Why this is correct
Clustering improves aggregation performance.
- ✓
Partition tables on columns frequently used in WHERE clauses
Why this is correct
Partition pruning reduces bytes scanned.
- ✗
Load data using batch loads instead of streaming
Why it's wrong here
Loading method doesn't directly affect query performance.
- ✗
Store data in CSV format
Why it's wrong here
CSV is less efficient than columnar formats like Parquet.
- ✗
Use SELECT * in all queries
Why it's wrong here
Selecting all columns increases bytes processed.
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