Question
Which of the following Big Data processing models is
based on the concept of continuous data flow processing?Solution
Stream processing involves continuously analyzing data as it arrives, which is ideal for real-time applications. It processes data in real-time, as opposed to waiting for a complete dataset, making it highly efficient for scenarios requiring immediate insights, such as fraud detection, social media analytics, and sensor data analysis. Stream processing frameworks include Apache Storm, Flink, and Spark Streaming. Batch Processing : Involves processing data in large chunks rather than continuously. It is not real-time. MapReduce : A programming model used for batch processing large datasets, not real-time processing. Hadoop : A framework that supports batch processing but not real-time stream processing. HDFS : The Hadoop Distributed File System (HDFS) is for storing large data sets, not processing them.
Which operating system concept allows multiple processes to run concurrently by sharing system resources?
Which component of the CPU is responsible for performing arithmetic operations (like addition, subtraction) and logical operations (like AND, OR, NOT)?
In OOP, what is meant by "overriding"?
Which type of computer is designed to be used by a single user at a time and is commonly found in homes and offices?
Which of the following is an example of an output device?
Which of the following is a feature of abstraction?
Which component of the CPU is responsible for performing arithmetic operations (like addition, subtraction) and logical operations (like AND, OR, NOT)?
Which operating system component manages and allocates system resources among various running processes?
...Which of the following is an essential feature of a Doubly Linked List over a Singly Linked List?
Which big data technology is specifically designed for distributed data processing using a cluster of computers?
