In a scenario involving iterative machine learning algorithms, which Apache Spark feature would be most beneficial?
- DataFrames
- Resilient Distributed Datasets (RDDs)
- Spark MLlib
- Spark Streaming
In scenarios with iterative machine learning algorithms, Spark MLlib would be most beneficial. MLlib is Spark's machine learning library that provides high-level APIs for machine learning tasks, including iterative algorithms commonly used in machine learning workflows.
Loading...
Related Quiz
- How does a Combiner function in a MapReduce job optimize the data processing?
- How does Sqoop handle the import of large tables into Hadoop?
- In Hadoop, which framework is traditionally used for batch processing?
- What advanced feature does Impala support for optimizing distributed queries?
- In a case study where Hive is used for analyzing web log data, what data storage format would be most optimal for query performance?