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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

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

1. Which project gives you a distributed, Scalable, data store that allows you random, realtime read/write
access to hundreds of terabytes of data?

A) Hive
B) Oozie
C) HBase
D) Flume
E) Pig
F) Hue
G) Sqoop

2. What data does a Reducer reduce method process? Reference: Yahoo! Hadoop Tutorial, Module 4:
MapReduce

A) All the data in a single input file.
B) All data for a given value, regardless of which mapper(s) produced it.
C) All data produced by a single mapper.
D) All data for a given key, regardless of which mapper(s) produced it.

3. You want to perform analysis on a large collection of images. You want to store this data in HDFS and
process it with MapReduce but you also want to give your data analysts and data scientists the ability to
process the data directly from HDFS with an interpreted high-level programming language like Python.
Which format should you use to store this data in HDFS?

A) SequenceFiles
B) CSV
C) HTML
D) JSON
E) XML
F) Avro

4. Assuming default settings, which best describes the order of data provided to a reducer's reduce method:

A) The keys given to a reducer aren't in a predictable order, but the values associated with those keys
always are.
B) Neither keys nor values are in any predictable order.
C) Both the keys and values passed to a reducer always appear in sorted order.
D) The keys given to a reducer are in sorted order but the values associated with each key are in no
predictable order

5. A combiner reduces:

A) The number of output files a reducer must produce.
B) The number of values across different keys in the iterator supplied to a single reduce method call.
C) The number of input files a mapper must process.
D) The amount of intermediate data that must be transferred between the mapper and reducer.

Solutions: