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These are the answers to MapReduce and YARN Cognitive Class Course Answer certification course. These answers have been updated recently and are 100% correct. The final exam is on Monday, April. All answers are 100%.

Module 1: Introduction to MapReduce and YARN

Question 1 : Which phase of MapReduce is optional?

• Shuffle
• Reduce
• Combiner
• Map

Question 2: Where are the output files of the Reducer task stored?

• A data warehouse
• Hadoop FS
• Within the Reducer node
• Linux FS

Question 3: Which node is responsible for assigning (key, value) pairs to different reducers?

• Shuffle node
• Reducer node
• Combiner node
• Mapper node

Module 2: Limitations of Hadoop v1 & MapReduce v1

Question 1: How is YARN an improvement over the MapReduce v1 paradigm?

• It’s completely open source
• It splits the JobTracker into two processes: ResourceManager and ApplicationManager
• It reduces multi-tenancy to improve performance
• It splits the TaskTracker into two processes: ResourceManager and ApplicationManager

Question 2 : What is an issue or limitation of the original MapReduce v1 paradigm?

• It’s not scalable
• It only has one TaskTracker
• It only supports Parquet file types
• It only has one JobTracker

Question 3: Existing applications can run on YARN without recompilation. True or False?

• True
• False

Module 3: The Architecture of YARN

Question 1: The NodeManager is a more generic and efficient version of the TaskTracker. True or False?

• True
• False

Question 2: A new ApplicationMaster is launched for each job and ends when the job completes. True or False?

• True
• False

Question 3 : The main change from Hadoop v1 to Hadoop v2 was the consolidation of both resource management and job processing. True or False?

• True
• False

Final Exam :

Question 1 :What are the main components of the ResourceManager in YARN? Select two.

• Scheduler
• JobTracker
• DataManager
• HDFS
• ApplicationManager

Question 2 : What will a Hadoop job do if you try to run it with an output directory that is already present?

• It will create new files, but with a different suffix.
• It will create another directory to store the output.
• It will erase all files in that directory before running.
• It will not run.

Question 3 : Which of the following statements is true?

• You can set the number of Reducers.
• The Shuffle phase is optional.
• You can set the number of Mappers and the number of Reducers.
• The number of Combiners is the same as the number of Reducers.
• You can set the number of Mappers.

Question 4: On which file system (FS) is the output of a Mapper task stored?

• Linux FS, and it is replicated 3 times.
• HDFS, and it is replicated 3 times.
• Linux FS, but it is not replicated.
• HDFS, but it is not replicated.

Question 5: Which statement is true about MapReduce’s use of replication in HDFS?

• Only one copy of each replicated block is processed by MapReduce in normal operation.
• Speculative execution is normally performed on all copies of each “split.”
• Each DataNode uses RAID to store its data.
• Multiple copies of each record are kept on each node.

Question 6: Which of the following is the correct sequence of MapReduce flow?

• Reduce —> Combine —> Map
• Combine —> Reduce —> Map
• Map —> Reduce —> Combine
• Map —> Combine —> Reduce

Question 7:  Which of the following operations will work improperly when using a Combiner?

• Average
• Maximum
• Count
• Minimum

Question 8 : Input data to MapReduce is record-oriented and blocks of data contain the same number of full records. True or False?

• False.
• True.

Question 9:Which statement is true about the Reduce phase of MapReduce?

• Containers are used instead of slots in MRv1, and can be used with either Map or Reduce tasks in MRv2.
• There is one JobTracker in the cluster.
• MapReduce jobs written in Java for MRv1 never require recompilation.
• Each job has an ApplicationManager that obtains Container IDs from the NodeManager.

Question 10: Which of the following statements is true?

• The NameNode in Hadoop 2 is fully fault-tolerant, whereas in Hadoop 1 it was a single point of failure.
• The NodeManager in Hadoop 2 replaces the TaskTracker in Hadoop 1.
• YARN requires a minimum of two nodes, one master and one slave, to run
• Both MapReduce and YARN can scale to any cluster size.

Question 11 :  Which of the following can be used to control the number of part files in a MapReduce program’s output directory?

• Shuffle parameters
• Number of Reducers
• Counter
• Number of Mappers
• Duplicate of ‘Question 2’

Question 12 : Which of the following is true about MapReduce?

• Compression of input files is optional.
• Output from the Map phase is replicated.
• The programmer must write the Map code, the Shuffle code, and the Reduce code.
• MapReduce programs must be written in Java.

Question 13 :Which statement is true about the Reduce phase of MapReduce?

• Output results are sent to the client program.
• Data arrives from the Shuffle phase already sorted by key.
• The Reducer phase sums up the values associated with each key.
• Each Reduce task processes all the data for one key only.

Question 14: With YARN, long-running jobs acquire and retain fixed-size containers before execution starts. True or False?

• False.
• True.

Question 15: The command provides the CLASSPATH needed for compiling Java programs written for MapReduce or YARN. True or False?

• False.
• True.

Conclusion

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