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Dive deep into the fascinating world of Efficient Processing of Stream Data over Persistent Data with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Efficient Processing of Stream Data over Persistent Data, a crucial aspect of Big Data Computing. In this section, you will encounter a diverse range of MCQs that cover various aspects of Efficient Processing of Stream Data over Persistent 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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Efficient Processing of Stream Data over Persistent Data MCQs | Page 5 of 5

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Q41.
Why is tuning of the join components important in HYBRIDJOIN?

a.

To maximize the size of the hash table

b.

To minimize the size of the disk buffer

c.

To optimize resource usage and minimize disk I/O cost on fast input data streams

d.

To increase the size of the stream buffer

Discuss
Answer: (c).To optimize resource usage and minimize disk I/O cost on fast input data streams Explanation:Tuning of the join components in HYBRIDJOIN is important to optimize resource usage and minimize disk I/O cost on fast input data streams.
Q42.
How is the optimal size of the disk buffer determined in HYBRIDJOIN?

a.

By randomly selecting a size

b.

By increasing the size of the hash table

c.

By conducting experiments and finding the size that maximizes the service rate

d.

By decreasing the size of the stream buffer

Discuss
Answer: (c).By conducting experiments and finding the size that maximizes the service rate Explanation:The optimal size of the disk buffer in HYBRIDJOIN is determined by conducting experiments and finding the size that maximizes the service rate.
Q43.
What factor significantly affects the performance of HYBRIDJOIN when dealing with the distribution of master data foreign keys in the stream?

a.

The type of disk used

b.

The number of tuples in the stream buffer

c.

The distribution of master data foreign keys in the stream

d.

The size of the hash table

Discuss
Answer: (c).The distribution of master data foreign keys in the stream Explanation:The distribution of master data foreign keys in the stream significantly affects the performance of HYBRIDJOIN.
Q44.
In HYBRIDJOIN, what is the advantage of the algorithm when dealing with intermittent streams compared to the original MESHJOIN?

a.

MESHJOIN is faster for intermittent streams

b.

HYBRIDJOIN processes intermittent streams without pausing

c.

Both MESHJOIN and HYBRIDJOIN pause for intermittent streams

d.

MESHJOIN leaves tuples unprocessed for an open-ended period in intermittent streams

Discuss
Answer: (b).HYBRIDJOIN processes intermittent streams without pausing Explanation:In intermittent streams, HYBRIDJOIN processes without pausing, whereas the original MESHJOIN would pause and leave tuples unprocessed for an open-ended period.
Q45.
What type of distribution is often used to model sales data, where some products are sold frequently while most are sold rarely?

a.

Uniform distribution

b.

Gaussian distribution

c.

Zipfian distribution

d.

Exponential distribution

Discuss
Answer: (c).Zipfian distribution Explanation:Zipfian distributions are often used to model sales data, where some products are sold frequently while most are sold rarely.
Q46.
How does HYBRIDJOIN's performance change when it benefits from more general locality in the data distribution?

a.

HYBRIDJOIN's performance remains the same

b.

HYBRIDJOIN's performance improves

c.

HYBRIDJOIN's performance deteriorates

d.

HYBRIDJOIN becomes slower

Discuss
Answer: (b).HYBRIDJOIN's performance improves Explanation:HYBRIDJOIN's performance improves when it benefits from more general locality in the data distribution.
Q47.
What is the primary objective of the HYBRIDJOIN algorithm in the context of real-time data warehousing?

a.

To maximize the stay of every stream tuple in the join window

b.

To minimize the efficiency of access to the disk-based relation

c.

To improve the efficiency of access to the disk-based relation

d.

To ignore the nonuniform nature of update streams

Discuss
Answer: (c).To improve the efficiency of access to the disk-based relation Explanation:The primary objective of the HYBRIDJOIN algorithm in the context of real-time data warehousing is to improve the efficiency of access to the disk-based relation.
Q48.
What does the HYBRIDJOIN algorithm aim to achieve in dealing with the nonuniform nature of update streams?

a.

To make all update streams uniform

b.

To ignore the nonuniform nature of update streams

c.

To maximize the stay of nonuniform update streams in the join window

d.

To effectively handle the nonuniform nature of update streams

Discuss
Answer: (d).To effectively handle the nonuniform nature of update streams Explanation:The HYBRIDJOIN algorithm aims to effectively handle the nonuniform nature of update streams.
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