Crucial Exams

GCP Professional Data Engineer Practice Question

You are investigating a slow dashboard query that aggregates data from the BigQuery table sales.transactions, partitioned on the DATE column transaction_date. The EXPLAIN plan shows the first stage scanning 4.5 TB with the note partition pruning: NONE. The SQL contains the filter WHERE DATE(transaction_ts) >= DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY). Which change will most reduce data scanned and alleviate the bottleneck without purchasing additional slots?

  • Purchase a dedicated 2,000-slot BigQuery reservation so the query has more parallel resources.

  • Rewrite the predicate to WHERE transaction_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY) so the filter references the partition column directly, enabling partition pruning.

  • Add clustering on customer_id to the sales.transactions table to improve selective reads.

  • Insert the /*+ BROADCAST_JOIN(orders) */ hint to avoid repartitioning during joins in the query plan.

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