Practice Test 3 | Google Cloud Certified Professional Data Engineer | Dumps | Mock Test
As a data engineer, you are assigned to assist data analysts with data modeling to maintain and re-design the existing tables in BigQuery. Data analysts have provided you with the new table schema to be applied to existing datasets. From the list of to-do for modifying the schema, the most notable changes are renaming columns and changing the data type for others, as well as adding “REQUIRED” constraints to some critical columns. How would you achieve this?
A. Create a new table schema in BigQuery. Insert data from existing dataset to the new one using INSERT SELECT statement.
B. Create authorized views on BigQuery tables with new column names and data types.
C. You can modify columns names and data types and apply constraints using ALTER command.
D. Export data to Google Storage. Create new tables with the updated schema. Import data to the new schema from Google Storage.
Correct Answer: A
In BigQuery, the following schema modifications are unsupported and require manual workarounds:
• Changing a column’s name.
• Changing a column’s data type.
• Changing a column’s mode (aside from relaxing REQUIRED columns to NULLABLE). • Deleting a column.
Option B is incorrect: You cannot specify a different data type while creating a view. You also cannot apply constraints since views are only for projection.
Option C is incorrect: You cannot change a column’s name or data type in BigQuery. You need to create a new table and move data to it.
Option D is incorrect: No need to export data to Google Storage. You can use INSERT SELECT to move data from existing tables to new ones.
Source(s):
BigQuery – Modifying Table Schemas: https://cloud.google.com/bigquery/docs/managing-table-schemas
Comments are closed, but trackbacks and pingbacks are open.