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Welcome to the Introduction to Big Data MCQs Page

Dive deep into the fascinating world of Introduction to Big Data with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Introduction to Big Data, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Introduction to Big Data, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Big Data Computing.

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Check out the MCQs below to embark on an enriching journey through Introduction to Big Data. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Big Data Computing.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Introduction to Big Data. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Introduction to Big Data MCQs | Page 37 of 43

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Discuss
Answer: (c).Multivalue database model Explanation:OpenQM Database belongs to the Multivalue database model.
Discuss
Answer: (b).Lower development costs and easier maintenance Explanation:Using Multivalue databases like OpenQM for application development can result in lower development costs and easier maintenance.
Q363.
Which of the following is a compatible database system with OpenQM?
Discuss
Answer: (d).MongoDB Explanation:MongoDB is not a compatible database system with OpenQM.
Discuss
Answer: (c).Resource Description Framework - Header-Dictionary-Triples Explanation:RDF-HDT stands for Resource Description Framework - Header-Dictionary-Triples.
Discuss
Answer: (b).Header, Dictionary, and Triples Explanation:The three main components of RDF-HDT are Header, Dictionary, and Triples.
Discuss
Answer: (b).Implementing SPARQL Explanation:RDF-3X is primarily used for implementing SPARQL and achieving excellent query performance.
Discuss
Answer: (b).By performing exhaustive indexing of subject-predicate-object triples Explanation:RDF-3X achieves efficient indexing and query processing by performing exhaustive indexing of subject-predicate-object triples, resulting in highly compressed indices.
Q368.
What type of architecture does RDF-3X use for online updates?
Discuss
Answer: (c).Staging architecture Explanation:RDF-3X uses a staging architecture for efficient online updates.
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Answer: (c).By employing a query optimizer Explanation:RDF-3X chooses optimal join orders for complex queries using a query optimizer.
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Answer: (a).Statistical synopses for entire join paths Explanation:RDF-3X's cost model includes statistical synopses for entire join paths to optimize query performance.

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