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Answer: Upgrade the external table to a BigLake table. Enable metadata caching for the table.
The correct answer is **C**. Upgrading the external table to a BigLake table and enabling metadata caching can significantly improve query performance against partitioned data in Cloud Storage. BigLake tables are designed for efficient querying of large datasets, leading to faster execution times. Metadata caching reduces overhead, further boosting performance. - **Option A** is incorrect because migrating data to a multi-region bucket enhances availability and durability but doesn't directly affect query speed. - **Option B** is incorrect as changing the storage class impacts cost and availability, not query performance. - **Option D** is incorrect because managing multiple tables complicates administration without guaranteed performance gains, and wildcard queries may not resolve the root performance issues.
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You've configured an external table in Apache Hive for partitioned data stored in a Cloud Storage bucket, which contains many files. However, queries on this table are performing slowly. What steps can you take to improve the query performance?
A
Migrate the Hive partitioned data objects to a multi-region Cloud Storage bucket.
B
Change the storage class of the Hive partitioned data objects from Coldline to Standard.
C
Upgrade the external table to a BigLake table. Enable metadata caching for the table.
D
Create an individual external table for each Hive partition by using a common table name prefix. Use wildcard table queries to reference the partitioned data.
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