Match List I and List II

LIST - I

LIST - II

A.

Apache Kafka

I.

Platform for constructing data flows for extract, transform, and load (ETL) processing and analysis of large datasets.

B.

Pig

II.

General-purpose computing model and runtime system for distributed data analytics.

C.

Apache Mahout

III.

Open-source platform that was created by Linkedin.

D.

Mapreduce

IV.

Open-source platform used for creating scalable machine learning algorithms.


Choose the correct answer from the options given below:

This question was previously asked in
UGC NET Computer Science (Paper 2) 11 March 2023 Official Paper
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  1. A - II, B - IV, C - I, D - III
  2. A - II, B - I, C - IV, D - III
  3. A - III, B - I, C - IV, D - II
  4. A - I, B - II, C - IV, D - III

Answer (Detailed Solution Below)

Option 3 : A - III, B - I, C - IV, D - II
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UGC NET Paper 1: Held on 21st August 2024 Shift 1
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Detailed Solution

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The correct answer is

Key Points

  • A. Apache Kafka - Open-source platform that was created by Linkedin. 
    • Apache Kafka is an open-source stream-processing software platform developed by LinkedIn and was donated to the Apache Software Foundation. It is designed for high-volume real-time data ingestion and processing. It is used in scenarios where high throughput, reliable delivery and horizontal scalability are necessary.
  • B. Pig - Platform for constructing data flows for extract, transform, and load (ETL) processing and analysis of large datasets. 
    • Pig is an open-source platform that provides a high-level mechanism for the parallel execution of map-reduce jobs executed on Hadoop clusters. Pig simplifies the use of Hadoop by allowing SQL-like commands for data extract-transform-load (ETL) operations, as well as large data set analysis.
  • C. Apache Mahout - Open-source platform used for creating scalable machine learning algorithms.
    • Apache Mahout is a project of the Apache Software Foundation with the goal of creating scalable machine learning algorithms. The algorithms focus primarily in the areas of collaborative filtering, clustering, and classification, and are designed to be scalable and robust.
  • D. MapReduce - General-purpose computing model and runtime system for distributed data analytics. 
    • MapReduce is a computational model and software framework for writing applications that rapidly process vast amounts of data in parallel on large clusters of compute nodes. It is a core component of the Apache Hadoop software framework which allows processing huge amounts of data.
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