Answer-first summary for fast verification
Answer: Convert the sharded tables into a single partitioned table
The correct answer is B: Convert the sharded tables into a single partitioned table. Partitioning tables improves performance compared to sharding, as it reduces the overhead of managing multiple tables' metadata and permissions. Converting multiple daily log tables into a single partitioned table allows BigQuery to handle larger datasets more efficiently and avoid the 1,000-table limit encountered when using wildcard functions. This approach optimizes both query performance and management overhead.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
Your gaming app, which was launched nearly three years ago, has generated extensive log data. Each day, you upload the previous day’s log files into individual Google BigQuery tables named using the format LOGS_yyyymmdd. These tables are then used to create daily and monthly analytical reports across various time ranges using table wildcard functions. Recently, you encountered an issue where queries spanning long date ranges are failing because they exceed the 1,000 table limit. What is the best way to resolve this issue?
A
Convert all daily log tables into date-partitioned tables
B
Convert the sharded tables into a single partitioned table
C
Enable query caching so you can cache data from previous months
D
Create separate views to cover each month, and query from these views
No comments yet.