Which component of the Hadoop ecosystem is responsible for processing large datasets in parallel across a distributed cluster?
- Apache HBase
- Apache Hadoop MapReduce
- Apache Kafka
- Apache Spark
Apache Hadoop MapReduce is responsible for processing large datasets in parallel across a distributed cluster by breaking down tasks into smaller subtasks that can be executed on different nodes.
Loading...
Related Quiz
- What is the role of anomaly detection in monitoring data pipelines?
- Scenario: You are tasked with transforming a large volume of unstructured text data into a structured format for analysis. Which data transformation method would you recommend, and why?
- Scenario: A telecommunications company is experiencing challenges with storing and processing large volumes of streaming data from network devices. As a data engineer, how would you design a scalable and fault-tolerant storage architecture to address these challenges?
- Scenario: A data anomaly is detected in the production environment, impacting critical business operations. How would you utilize data lineage and metadata management to identify the root cause of the issue and implement corrective measures swiftly?
- Scenario: A colleague is facing memory-related issues with their Apache Spark job. What strategies would you suggest to optimize memory usage and improve job performance?