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A data analysis team is working with the table_bronze SQL table as a source for one of its most complex projects. A stakeholder of the project notices that some of the downstream data is duplicative. The analysis team identifies table_bronze as the source of the duplication. Which of the following queries can be used to deduplicate the data from table_bronze and write it to a new table table_silver? A) CREATE TABLE table_silver AS SELECT DISTINCT * FROM table_bronze; B) CREATE TABLE table_silver AS INSERT * FROM table_bronze; C) CREATE TABLE table_silver AS MERGE DEDUPLICATE * FROM table_bronze; D) INSERT INTO TABLE table_silver SELECT * FROM table_bronze; E) INSERT OVERWRITE TABLE table_silver SELECT * FROM table_bronze;
Correct Answer: A
Option A uses the SELECT DISTINCT statement to remove duplicate rows from the table_bronze and create a new table table_silver with the deduplicated data. This is the correct way to deduplicate data using Spark SQL12. Option B simply inserts all the rows from table_bronze into table_silver, without removing any duplicates. Option C is not a valid syntax for Spark SQL, as there is no MERGE DEDUPLICATE statement. Option D appends all the rows from table_bronze into table_silver, without removing any duplicates. Option E overwrites the existing data in table_silver with the data from table_bronze, without removing any duplicates. Reference: Delete Duplicate using SPARK SQL, Spark SQL - How to Remove Duplicate Rows