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1. You're working with a DataFrame containing customer data, including a "purchase_date" column. How can you calculate the average purchase amount per month for the past year?

A) Use Spark SQL's MONTH function and AVG function with appropriate windowing
B) Utilize Spark's machine learning library (MLIiB. for time series analysis
C) Loop through the DataFrame and group purchases by month, calculating the average manually
D) Convert the "purchase_date" column to a string and filter based on the year

2. In Apache Airflow, which strategy allows for the dynamic generation of tasks within a DAG based on external data sources, such as a list of database tables?

A) Utilizing the @dag decorator with dynamic input parameters
B) Employing the TaskFlow API with dynamic task mapping
C) Using the Variable class to store and retrieve the list of tables
D) Implementing a PythonOperator that generates other tasks at runtime

3. When writing a DataFrame to a CSV file, what potential issues should you consider and how can you address them?

A) Ensure proper handling of special characters and delimiters to avoid data corruption
B) Choose an appropriate compression format like Gzip to reduce file size
C) All of the above
D) No specific issues need to be considered, as CSV is a simple format

4. Your Airflow DAG includes tasks that can potentially fail due to various reasons. How can you handle such failures and ensure the overall workflow continues as intended?

A) Utilize Airflow XCom to share information about failed tasks with downstream tasks for alternative processing.
B) Implement custom logic within each task to handle potential errors and retry failed tasks manually.
C) All of the above
D) Configure the DAG to automatically retry failed tasks a specific number of times.

5. Which of the following is a benefit of using broadcast variables in Spark for caching static lookup tables?

A) They reduce network I/O by making data available locally on each node.
B) They increase the amount of data shuffle during joins.
C) They reduce the reliability of Spark applications.
D) They are automatically cleaned up after each task.

問題與答案：