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Welcome to the Big Data Exploration MCQs Page

Dive deep into the fascinating world of Big Data Exploration with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Big Data Exploration, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Big Data Exploration, 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 Big Data Exploration. 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 Big Data Exploration. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Big Data Exploration MCQs | Page 6 of 9

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Q51.
How does adaptive merging improve over plain cracking in terms of convergence speed?

a.

It reduces the number of queries needed to reach performance levels.

b.

It significantly increases the size of the initial runs.

c.

It applies a binary search to the initial runs.

d.

It aggressively sorts the results column.

Discuss
Answer: (a).It reduces the number of queries needed to reach performance levels. Explanation:Adaptive merging improves over plain cracking in terms of convergence speed by reducing the number of queries needed to reach performance levels.
Q52.
What is the main advantage of the crack-sort hybrid compared to other hybrid algorithms?

a.

It eliminates the need for an initial column.

b.

It performs an aggressive quicksort on the initial runs.

c.

It achieves the best overall balance between initialization and convergence costs.

d.

It minimizes the overhead of the first query.

Discuss
Answer: (c).It achieves the best overall balance between initialization and convergence costs. Explanation:The main advantage of the crack-sort hybrid is that it achieves the best overall balance between initialization and convergence costs.
Q53.
How does the performance of cracking depend on the arrival order of queries?

a.

Cracking performs the same regardless of the order of queries.

b.

The performance of cracking is entirely independent of query order.

c.

Cracking's adaptation speed and patterns depend on query order.

d.

The order of queries does not impact cracking performance.

Discuss
Answer: (c).Cracking's adaptation speed and patterns depend on query order. Explanation:The performance of cracking depends on the arrival order of queries, as cracking's adaptation speed and patterns are influenced by the order in which queries arrive.
Q54.
What problem does stochastic cracking aim to solve?

a.

Slow query processing

b.

High storage overhead

c.

Lack of robustness in cracking performance

d.

Inefficient data storage

Discuss
Answer: (c).Lack of robustness in cracking performance Explanation:Stochastic cracking aims to solve the lack of robustness in cracking performance, especially when queries are processed in a specific order that leaves large uncracked pieces.
Q55.
How does stochastic cracking work to reduce the chances of leaving back big uncracked pieces?

a.

It uses a random pivot for every cracking action.

b.

It skips certain cracking steps to speed up the process.

c.

It defers cracking actions until all queries have been processed.

d.

It performs aggressive sorting actions during cracking.

Discuss
Answer: (a).It uses a random pivot for every cracking action. Explanation:Stochastic cracking reduces the chances of leaving back big uncracked pieces by adding an additional cracking step for a randomly chosen pivot during the normal cracking actions. This randomness helps ensure better partitioning.
Q56.
Why is concurrent access to data challenging in the context of database cracking?

a.

Cracking doesn't support concurrent access.

b.

Cracking has unpredictable query times.

c.

Every query may change the organization of data.

d.

Cracking doesn't allow multiple users to query Big Data.

Discuss
Answer: (c).Every query may change the organization of data. Explanation:Concurrent access to data is challenging in the context of database cracking because every query may change the organization of data, which can lead to conflicts when multiple queries are trying to work on the same data simultaneously.
Q57.
How does database cracking achieve concurrency control for adaptive indexing during read queries?

a.

By locking entire columns during query processing.

b.

By using heavyweight database locks.

c.

By allowing multiple queries to work on different pieces of a column simultaneously.

d.

By avoiding concurrent access altogether.

Discuss
Answer: (c).By allowing multiple queries to work on different pieces of a column simultaneously. Explanation:Database cracking achieves concurrency control for adaptive indexing during read queries by allowing multiple queries to work on different pieces of a column simultaneously. This is done to enable parallelism while maintaining the adaptive behavior of database cracking.
Q58.
In the context of adaptive indexing during read queries, what remains intact even when data organization changes?

a.

Data contents

b.

Query performance

c.

Index structures

d.

Workload knowledge

Discuss
Answer: (a).Data contents Explanation:In the context of adaptive indexing during read queries, the data contents remain intact even when data organization changes. This means that data values themselves are not modified, only the way they are organized is changed to improve query performance.
Q59.
What is the advantage of using latching for concurrency control in adaptive indexing?

a.

Latching provides fine-grained control over data access.

b.

Latching is less efficient than full-fledged database locks.

c.

Latching is heavyweight and resource-intensive.

d.

Latching results in a lightweight concurrency control mechanism.

Discuss
Answer: (d).Latching results in a lightweight concurrency control mechanism. Explanation:The advantage of using latching for concurrency control in adaptive indexing is that it results in a lightweight concurrency control mechanism. Latching is less resource-intensive compared to full-fledged database locks and is suitable for managing concurrent access to pieces of data during read queries in adaptive indexing.
Q60.
Why is data loading considered a necessary step when setting up a database system?

a.

To optimize data access

b.

To control data directly

c.

To improve data creation

d.

To enable query processing

Discuss
Answer: (d).To enable query processing Explanation:Data loading is considered a necessary step when setting up a database system to enable query processing. It involves copying and transforming data into the database system, allowing the database to control data storage and optimize data access during query processing.
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