Free Hadoop Quiz Online Practice Test1

Thank you very much for taking test

Test your caliber

1. What is a SequenceFile?
ASequenceFilecontains a binaryencoding ofan arbitrary numberof homogeneous writable objects.	ASequenceFilecontains a binary encoding of an arbitrary number of heterogeneous writable objects.
ASequenceFilecontains a binary encoding of an arbitrary number of WritableComparable objects, in sorted order.	ASequenceFilecontains a binary encoding of an arbitrary number key-value pairs. Each key must be the same type. Each value must be sametype.

2. Is there a map input format?
Yes, but only in Hadoop 0.22+.	Yes, there is a special format for map files.
No, but sequence file input format can read map files.	Both 2 and 3 are correct answers.

3. In a MapReduce job, you want each of you input files processed by a single map task. How do you configure a MapReduce job so that a single map task processes each input file regardless of how many blocks the input file occupies?
Increase the parameter that controls minimum split size in the job configuration.	Write a custom MapRunner that iterates over all key-value pairs in the entire file.
Set the number of mappers equal to the number of input files you want to process.	Write a custom FileInputFormat and override the method isSplittable to always return false.

4. Which of the following best describes the workings of TextInputFormat?
Input file splits may cross line breaks. A line thatcrosses tile splits is ignored.	The input file is split exactly at the line breaks, so each Record Reader will read a series of complete lines.
Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReaders of both splits containing the brokenline.	Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of the split that contains the end of the brokenline.

5. Which of the following statements most accurately describes the relationship between MapReduce and Pig?
Pig provides additional capabilities that allow certain types of data manipulation not possible with MapReduce.	Pig provides no additional capabilities to MapReduce. Pig programs are executed as MapReduce jobs via the Pig interpreter.
Pig programs rely on MapReduce but are extensible, allowing developers to do special-purpose processing not provided by MapReduce	Pig provides the additional capability of allowing you to control the flow of multiple MapReduce jobs.

6. You need to import a portion of a relational database every day as files to HDFS, and generate Java classes to Interact with your imported data. Which of the following tools should you use to accomplish this?
Pig	Hue
Hive	Flume

7. You have an employee who is a Date Analyst and is very comfortable with SQL. He would like to run ad-hoc analysis on data in your HDFS duster. Which of the following is a data warehousing software built on top of Apache Hadoop that defines a simple SQL-like query language well-suited for this kind of user?
Pig	Hue
Hive	Sqoop

8. Workflows expressed in Oozie can contain:
Iterative repetition of MapReduce jobs until a desired answer or state is reached.	Sequences of MapReduce and Pig jobs. These are limited to linear sequences of actions with exception handlers but no forks.
Sequences of MapReduce jobs only; no Pig or Hive tasks or jobs. These MapReduce sequences can be combined with forks and path joins.	Sequences of MapReduce and Pig. These sequences can be combined with other actions including forks, decision points, and path joins.

9. You need a distributed, scalable, data Store that allows you random, realtime read/write access to hundreds of terabytes of data. Which of the following would you use?
Hue	Pig
Hive	HBase

10. Which of the following utilities allows you to create and run MapReduce jobs with any executable or script as the mapper and/or the reducer?
Oozie	Sqoop
Flume	Hadoop Streaming

11. You are running a Hadoop cluster with all monitoring facilities properly configured. Which scenario will go undetected.?
Map or reduce tasks that are stuck in an infinite loop.	HDFS is almost full.
The NameNode goes down.	A DataNode is disconnectedfrom the cluster.

12. Which of the following scenarios makes HDFS unavailable?
JobTracker failure	TaskTracker failure
DataNode failure	NameNode failure

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

14. Which of the following statements most accurately describes the general approach to error recovery when using MapReduce?
Ranger	Longhorn
Lonestar	Spur

15. The Combine stage, if present, must perform the same aggregation operation as Reduce.
True	False
All of the Above	None of these

16. What is the implementation language of the Hadoop MapReduce framework?
Java	C
FORTRAN	Python

17. Which of the following MapReduce execution frameworks focus on execution in sharedmemory environments?
Hadoop	Twister
Phoenix	All of the Above

18. How can a distributed filesystem such as HDFS provide opportunities for optimization of a MapReduce operation?
Data represented in a distributed filesystem is already sorted.	Distributed filesystems must always be resident in memory, which is much faster than disk.
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.	A distributed filesystem makes random access faster because of the presence of a dedicated node serving file metadata.

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

20. Which MapReduce phase is theoretically able to utilize features of the underlying file system in order to optimize parallel execution?
Split	Map
Combine	All of the Above