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Big Data NoSQL Tenta Exam Questions And Accurate Answers (A+)
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Big Data NoSQL Tenta Exam Questions AndAccurate Answers (A+)
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 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
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