Data Processing Big Data Processing 2

Question 1

What is stream processing in big data?

Accepted Answer

Continuously processing data as it arrives in real time

Answer

Importing data in large batches overnight

Answer

Storing data in sequential log files

Answer

Processing only structured data from relational systems

Question 2

What is Apache Kafka primarily used for?

Accepted Answer

Distributed real-time data streaming and messaging

Answer

Storing structured relational data

Answer

Running machine learning model training

Answer

Generating PDF reports from databases

Question 3

What distinguishes batch processing from stream processing?

Accepted Answer

Batch processing handles data in large collected groups at scheduled intervals; stream processing handles data continuously as it arrives

Answer

Batch processing is faster than stream processing

Answer

Stream processing stores data permanently; batch processing does not

Answer

Batch processing only works with unstructured data

Question 4

What is a data warehouse?

Accepted Answer

A centralized repository of integrated, structured data optimized for reporting and analysis

Answer

A temporary cache for raw incoming data

Answer

A tool for monitoring ETL job performance

Answer

A distributed file system for unstructured data

Question 5

What is horizontal scaling in the context of big data systems?

Accepted Answer

Adding more machines to a cluster to increase processing capacity

Answer

Upgrading the CPU and RAM of a single server

Answer

Increasing the size of database indexes

Answer

Adding more columns to existing tables

Question 6

What is a partitioning strategy in big data storage?

Accepted Answer

Dividing a large dataset into smaller subsets based on a key for parallel processing efficiency

Answer

Encrypting data segments individually for security

Answer

Creating backup copies of data across regions

Answer

Sorting data alphabetically before archiving