DEA-C01 Question 68
Select 4You are tasked with analyzing a large dataset stored in Amazon S3 using Apache Spark on Amazon EMR. The dataset contains semi-structured JSON data, and the goal is to extract specific fields, perform aggregations, and write the results back in Parquet format for efficient querying. Which of the following steps should you take to achieve this?
- A
Use the SparkSession object to read the JSON data directly from the S3 bucket.
- B
Define a schema manually for the JSON data to improve performance and reduce overhead.
- C
Perform transformations using Spark DataFrame APIs to extract the required fields and perform aggregations.
- D
Write the transformed data back to S3 directly using the .toJSON() method.
- E
Write the transformed data back to S3 in Parquet format using the .write.parquet() method.
Show answer and explanation
Correct answers: A, B, C, E
Explanation
To process semi-structured JSON data in Amazon S3 using Apache Spark on Amazon EMR, you should use the SparkSession object to read the JSON data and define a schema to improve performance. Transformations can be applied using Spark DataFrame APIs to extract fields and perform aggregations. Finally, the transformed data should be written back in Parquet format using the .write.parquet() method, as Parquet is optimized for query performance and space efficiency.
- A. Correct.
Correct. Apache Spark supports reading JSON data directly from S3 using the SparkSession’s read API, which simplifies data ingestion.
- B. Correct.
Correct. Manually defining a schema for semi-structured data like JSON helps improve performance by avoiding Spark's default schema inference, which can be slow for large datasets.
- C. Correct.
Correct. Spark DataFrame APIs are well-suited for extracting fields and performing aggregations efficiently.
- D. Incorrect.
Incorrect. The .toJSON() method converts the data to JSON format, which is not the desired output format. The requirement is to write the results in Parquet format.
- E. Correct.
Correct. The .write.parquet() method is the appropriate way to write data to S3 in Parquet format, meeting the requirement for efficient querying.