Scenario: You need to perform complex data transformations on a large dataset in Apache Spark. Which transformation would you choose to ensure scalability and fault tolerance?
- FlatMap
- GroupByKey
- MapReduce
- Transformations with narrow dependencies
Transformations with narrow dependencies in Apache Spark, such as map and filter, allow for parallel processing and are preferred for complex data transformations on large datasets. These transformations minimize data shuffling and ensure scalability and fault tolerance by optimizing the execution plan and reducing the impact of node failures on the overall job performance.
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