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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

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

Question #1
You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses
TextInputFormat: the mapper applies a regular expression over input values and emits key-values pairs
with the key consisting of the matching text, and the value containing the filename and byte offset.
Determine the difference between setting the number of reduces to one and settings the number of
reducers to zero.

A. With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances of
matching patterns are stored in a single file on HDFS.
B. With zero reducers, all instances of matching patterns are gathered together in one file on HDFS. With
one reducer, instances of matching patterns are stored in multiple files on HDFS.
C. With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one
reducer, all instances of matching patterns are gathered together in one file on HDFS.
D. There is no difference in output between the two settings.

Question #2
Your cluster's HDFS block size in 64MB. You have directory containing 100 plain text files, each of which
is 100MB in size. The InputFormat for your job is TextInputFormat. Determine how many Mappers will
run?

A. 640
B. 200
C. 64
D. 100

Question #3
In a MapReduce job with 500 map tasks, how many map task attempts will there be?

A. At most 500.
B. At least 500.
C. Exactly 500.
D. Between 500 and 1000.
E. It depends on the number of reduces in the job.

Question #4
In a MapReduce job, you want each of your 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?

A. Write a custom FileInputFormat and override the method isSplitable to always return false.
B. Increase the parameter that controls minimum split size in the job configuration.
C. Set the number of mappers equal to the number of input files you want to process.
D. Write a custom MapRunner that iterates over all key-value pairs in the entire file.

Question #5
Given the following Hive command:
INSERT OVERWRITE TABLE mytable SELECT * FROM myothertable;
Which one of the following statements is true?

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

Solutions: