Exam Professional Data Engineer topic 1 question 283 discussion

Actual exam question from Google's Professional Data Engineer

Question #: 283
Topic #: 1

[All Professional Data Engineer Questions]

You have created an external table for Apache Hive partitioned data that resides in a Cloud Storage bucket, which contains a large number of files. You notice that queries against this table are slow. You want to improve the performance of these queries. What should you do?

A. Change the storage class of the Hive partitioned data objects from Coldline to Standard.
B. 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.
C. Upgrade the external table to a BigLake table. Enable metadata caching for the table.
D. Migrate the Hive partitioned data objects to a multi-region Cloud Storage bucket.

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Suggested Answer: C 🗳️

by GCP001 at Jan. 7, 2024, 4:17 p.m.

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raaad

Highly Voted 1 year ago

Selected Answer: C

- BigLake Table: BigLake allows for more efficient querying of data lakes stored in Cloud Storage. It can handle large datasets more effectively than standard external tables. - Metadata Caching: Enabling metadata caching can significantly improve query performance by reducing the time taken to read and process metadata from a large number of files.

upvoted 8 times

AllenChen123

1 year ago

Agree. https://cloud.google.com/bigquery/docs/biglake-intro#metadata_caching_for_performance

upvoted 4 times

1 year ago

C. Upgrade the external table to a BigLake table. Enable metadata caching for the table. Check ref - https://cloud.google.com/bigquery/docs/biglake-intro

upvoted 2 times

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