Your company has a large dataset of customer transaction records stored in a relational database. You need to transform this data to analyze customer behavior patterns. Describe how you would use Apache Spark to process the data, including the steps involved in creating a resilient and scalable ETL pipeline.

Simulated

Load the data directly into a data warehouse and perform SQL queries to analyze customer behavior patterns.

0.0%

Use Apache Spark to read the data from the relational database, perform necessary transformations, and store the transformed data in a distributed file system for further analysis.

62.5%

Use a MapReduce approach to process the data in Apache Spark, as it is more suitable for batch processing.

31.3%

Use Apache Spark's machine learning libraries to directly predict customer behavior patterns without any data transformation.

6.3%

AWS Certified Data Engineer - Associate

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