Databricks Certified Data Engineer - Associate
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As a Data Engineer at a multinational corporation, you are tasked with integrating and analyzing employee performance data to support HR decision-making. The data is stored in two distinct formats within your Databricks environment: a JSON string containing employee details ('id', 'name', 'department', 'salary') and a table named 'performance_reviews' with fields ('employee_id', 'review_date', 'performance_rating'). Your objective is to parse the JSON string into a structured table and join it with the 'performance_reviews' table for comprehensive analysis. Given the importance of accuracy and efficiency in your analysis, and considering the need to include all employees in the results, even those without performance reviews, which of the following Spark SQL queries would you use? Choose the two most correct options from the five provided.
As a Data Engineer at a multinational corporation, you are tasked with integrating and analyzing employee performance data to support HR decision-making. The data is stored in two distinct formats within your Databricks environment: a JSON string containing employee details ('id', 'name', 'department', 'salary') and a table named 'performance_reviews' with fields ('employee_id', 'review_date', 'performance_rating'). Your objective is to parse the JSON string into a structured table and join it with the 'performance_reviews' table for comprehensive analysis. Given the importance of accuracy and efficiency in your analysis, and considering the need to include all employees in the results, even those without performance reviews, which of the following Spark SQL queries would you use? Choose the two most correct options from the five provided.
Explanation:
Option B is correct because it accurately selects all necessary fields from both tables and performs the join on the correct field 'id'. Option E is also correct as it uses a LEFT JOIN to ensure all employees are included in the results, even those without performance reviews, which is crucial for a comprehensive analysis. Option A is incorrect as it does not specify the fields to be selected, potentially leading to unnecessary data retrieval. Option C is incorrect due to the incorrect join condition 'employee_id' instead of 'id'. Option D is incorrect because it unnecessarily filters the results to only the 'Sales' department, limiting the analysis scope.