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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:

1. Given the following Hive command:
INSERT OVERWRITE TABLE mytable SELECT * FROM myothertable;
Which one of the following statements is true?

A) A new table named mytable is created, and the contents of myothertable are copied into mytable
B) The contents of myothertable are appended to mytable
C) Any existing data in mytable will be overwritten
D) The statement is not a valid Hive command

2. What is the disadvantage of using multiple reducers with the default HashPartitioner and distributing your
workload across you cluster?

A) By using multiple reducers with the default HashPartitioner, output files may not be in globally sorted
order.
B) You will not be able to compress the intermediate data.
C) You will longer be able to take advantage of a Combiner.
D) There are no concerns with this approach. It is always advisable to use multiple reduces.

3. The Hadoop framework provides a mechanism for coping with machine issues such as faulty
configuration or impending hardware failure. MapReduce detects that one or a number of machines are
performing poorly and starts more copies of a map or reduce task. All the tasks run simultaneously and
the task finish first are used. This is called:

A) Speculative Execution
B) Default Partitioner
C) Combine
D) IdentityMapper
E) IdentityReducer

4. You use the hadoop fs -put command to write a 300 MB file using and HDFS block size of 64 MB. Just
after this command has finished writing 200 MB of this file, what would another user see when trying to
access this life?

A) They would see the current state of the file, up to the last bit written by the command.
B) They would see Hadoop throw an ConcurrentFileAccessException when they try to access this file.
C) They would see the current of the file through the last completed block.
D) They would see no content until the whole file written and closed.

5. You need to perform statistical analysis in your MapReduce job and would like to call methods in the
Apache Commons Math library, which is distributed as a 1.3 megabyte Java archive (JAR) file. Which is
the best way to make this library available to your MapReducer job at runtime?

A) Package your code and the Apache Commands Math library into a zip file named JobJar.zip
B) Have your system administrator copy the JAR to all nodes in the cluster and set its location in the
HADOOP_CLASSPATH environment variable before you submit your job.
C) When submitting the job on the command line, specify the -libjars option followed by the JAR file path.
D) Have your system administrator place the JAR file on a Web server accessible to all cluster nodes and
then set the HTTP_JAR_URL environment variable to its location.

Solutions: