Frameworks (e.g., Hadoop, Spark) MCQs January 8, 2026November 19, 2024 by u930973931_answers 15 min Score: 0 Attempted: 0/15 Subscribe 1. Which of the following is a primary feature of the Hadoop framework? (A) In-memory processing for real-time data (B) Interactive data visualization (C) Built-in machine learning algorithms (D) Distributed storage and processing of large-scale datasets 2. What is the core component of Hadoop responsible for storing large datasets? (A) Hadoop MapReduce (B) Hadoop Distributed File System (HDFS) (C) Apache Hive (D) Apache Pig 3. What is the main advantage of using Apache Spark over Hadoop MapReduce? (A) Spark does not support real-time processing (B) Hadoop MapReduce processes data in memory (C) Spark only works with small datasets (D) Spark is faster due to in-memory processing 4. In Hadoop, what is the role of the JobTracker? (A) It manages file system operations (B) It schedules and manages tasks for distributed processing (C) It stores data in a distributed environment (D) It processes data in parallel 5. Which framework is best suited for performing iterative algorithms on large datasets? (A) Hadoop MapReduce (B) Apache Flink (C) Apache Hive (D) Apache Spark 6. What is the function of the ResourceManager in Hadoop YARN architecture? (A) It performs data preprocessing (B) It handles data storage in HDFS (C) It runs MapReduce jobs (D) It allocates resources and schedules tasks on the cluster 7. Which data processing model does Apache Spark use for parallel processing? (A) MapReduce (B) Entity-Relationship Model (C) Directed Acyclic Graph (DAG) (D) Dataflow Model 8. Which of the following is a feature of Apache Spark’s Resilient Distributed Dataset (RDD)? (A) RDDs are immutable and fault-tolerant (B) RDDs are stored on a single machine (C) RDDs cannot be processed in parallel (D) RDDs are only used for storage 9. In Hadoop, what is MapReduce primarily used for? (A) Storing large datasets (B) Writing SQL queries (C) Processing large datasets in a distributed manner (D) Visualizing analysis results 10. What is Apache Hive primarily used for in the Hadoop ecosystem? (A) Real-time data processing (B) Machine learning development (C) Data warehousing and SQL-like querying (D) Data visualization 11. Which of the following is an advantage of Apache Spark over Hadoop MapReduce? (A) Spark offers faster performance through in-memory computing (B) Spark is easier to set up (C) Spark supports only batch processing (D) Spark requires fewer resources 12. In Apache Hadoop, what is the purpose of the NameNode? (A) It stores actual data blocks (B) It executes MapReduce jobs (C) It performs data processing (D) It manages metadata of files in HDFS 13. Which of the following languages can be used to write Apache Spark applications? (A) Java (B) Python (C) All of the above (D) Scala 14. In Apache Spark, what is the role of the driver program? (A) It coordinates and controls task execution across the cluster (B) It processes data stored in HDFS (C) It manages Spark data storage (D) It handles incoming data streams 15. Which framework is best suited for real-time stream processing? (A) Apache Flink (B) Apache Hadoop (C) Apache Kafka (D) Apache Hive