Big Data NoSQL Tenta. Exam Questions
With Verified And Updated Answers
What are the two main phases of MapReduce used in Hadoop for processing and generating
large datasets? - answer✔The two main phases of MapReduce are the Map phase and the
Reduce phase.
What is the primary function of the Map phase in Hadoop's MapReduce, and how does it
prepare the data for the subsequent phase? - answer✔The Map phase in Hadoop's MapReduce
involves mapping data into key-value pairs using a defined function. This phase prepares the
data by shuffling and sorting the key-value pairs for the subsequent Reduce phase.
What is the fundamental purpose of the Reduce phase in Hadoop's MapReduce, and how does
it contribute to distributed data processing? - answer✔The Reduce phase in Hadoop's
MapReduce combines and reduces intermediate results produced by map tasks, ultimately
generating the final output. This phase is fundamental in achieving distributed data processing
in Hadoop.
In the context of MapReduce, what is the purpose of the "Combine" operation, and how does it
contribute to optimizing the efficiency of a MapReduce job? - answer✔The "Combine"
operation in MapReduce aims to reduce data transfer during the shuffle and sort phase by
applying a combiner function to the Map phase's output before it reaches the Reduce phase.
This optimization helps minimize network overhead and enhances the overall efficiency of the
MapReduce job.
In the context of Hadoop and big data tools, how is Awk commonly utilized, and what types of
tasks is it often employed for? - answer✔Awk is frequently used in scripting and data
preprocessing tasks when working with Hadoop and other big data tools. It is particularly
employed for tasks such as log file analysis and data extraction.
What is the primary role of HDFS (Hadoop Distributed File System) in the Hadoop ecosystem,
and how does it achieve fault tolerance in storing and managing large datasets? -
answer✔HDFS serves as the primary storage system in Hadoop, designed for storing and
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managing large datasets across a distributed cluster of commodity hardware. It achieves fault
tolerance by dividing data into blocks and replicating them across the cluster.
In the context of Hadoop and big data, what term refers to the process of combining and
summarizing large datasets? - answer✔Aggregate
Which Hadoop concept involves processing continuous data in real-time, allowing for
immediate analysis and insights? - answer✔Streaming
What is the central component in HDFS responsible for storing metadata and managing the file
system namespace? - answer✔NameNode
In HDFS, what type of node stores actual data and is responsible for serving read and write
requests? - answer✔DataNode
What term in Hadoop refers to the system's ability to continue functioning even in the presence
of hardware or software failures? - answer✔Fault Tolerance
In HDFS, data is divided into fixed-size units for storage. What is the term used for these units? -
answer✔Block
In the context of Hadoop, what data structure is used to represent a file system object, such as
a file or directory? - answer✔Inode
What is the term for the node in Hadoop that controls the overall operation of the distributed
system and manages resources? - answer✔Master node
In Hadoop, what type of node is responsible for performing computations on the data and is
subordinate to the master node? - answer✔Work/slave node
What term is used in big data to describe datasets that are continuously generated and have no
predefined size? - answer✔Unbounded data; It is suitable for real-time analytics and
processing.
In big data, what term describes datasets with a known and fixed size, often suitable for batch
processing? - answer✔Bounded data; It is good for tasks requiring structured processing and
analysis
What is the primary purpose of Apache Drill in the big data ecosystem, and what is one of its
weaknesses? - answer✔Purpose: Apache Drill is designed for interactive analysis of large-scale
datasets with a schema-free approach, supporting diverse data sources. Parallel processing.
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