Thursday, 3 September 2015

Hadoop Objective type Questions and Answers

11. You are running a Hadoop cluster with all monitoring facilities properly configured. Which scenario will go undetected.?
A. Map or reduce tasks that are stuck in an infinite loop.
B. HDFS is almost full.
C. The NameNode goes down.
D. A DataNode is disconnectedfrom the cluster.
E. MapReduce jobs that are causing excessive memory swaps.
Answer: C

12. Which of the following scenarios makes HDFS unavailable?
A. JobTracker failure
B. TaskTracker failure
C. DataNode failure
D. NameNode failure
E. Secondary NameNode failure
Answer: A

13. Which MapReduce stage serves as a barrier, where all previous stages must be completed before it may proceed?
A. Combine
B. Group (a.k.a. 'shuffle')
C. Reduce
D. Write
Ans: A

14. Which of the following statements most accurately describes the general approach to error recovery when using MapReduce?
A. Ranger
B. Longhorn
C. Lonestar
D. Spur
Ans: A

15. The Combine stage, if present, must perform the same aggregation operation as Reduce.
A. True
B. False
Ans: B

16. What is the implementation language of the Hadoop MapReduce framework?
A. Java
B. C
C. FORTRAN
D. Python
Ans: A

17. Which of the following MapReduce execution frameworks focus on execution in sharedmemory environments?
A. Hadoop
B. Twister
C. Phoenix
Ans: C

18. How can a distributed filesystem such as HDFS provide opportunities for optimization of a MapReduce operation?
A. Data represented in a distributed filesystem is already sorted.
B. Distributed filesystems must always be resident in memory, which is much faster than disk.
C. Data storage and processing can be co-located on the same node, so that most input data relevant to Map or Reduce will be present on local disks or cache.
D. A distributed filesystem makes random access faster because of the presence of a dedicated node serving file metadata.
Ans: D

19. What is the input to the Reduce function?
A. One key and a list of all values associated with that key.
B. One key and a list of some values associated with that key.
C. An arbitrarily sized list of key/value pairs.
Ans: A

20. Which MapReduce phase is theoretically able to utilize features of the underlying file system in order to optimize parallel execution?
A. Split
B. Map
C. Combine
Ans: A

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