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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

Section	Objectives
Hadoop Ecosystem Tools	- Sqoop and data ingestion - Workflow and processing frameworks
Hive Development	- Hive optimization and execution - Hive table definitions and queries
Pig Development	- Pig Latin scripting - Pig data types and UDFs
Hadoop Core Concepts	- HDFS architecture and commands - YARN and MapReduce fundamentals

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

Question 1

For each input key-value pair, mappers can emit:

A. One intermediate key-value pair, but of the same type.
B. As many intermediate key-value pairs as designed, but they cannot be of the same type as the input
key-value pair.
C. One intermediate key-value pair, of a different type.
D. As many intermediate key-value pairs as designed. There are no restrictions on the types of those
key-value pairs (i.e., they can be heterogeneous).
E. As many intermediate key-value pairs as designed, as long as all the keys have the same types and all
the values have the same type.

Question 2

Which HDFS command uploads a local file X into an existing HDFS directory Y?

A. hadoop scp X Y
B. hadoop fs -localPut X Y
C. hadoop fs-put X Y
D. hadoop fs -get X Y

Question 3

You are developing a MapReduce job for sales reporting. The mapper will process input keys
representing the year (IntWritable) and input values representing product indentifies (Text).
Indentify what determines the data types used by the Mapper for a given job.

A. The key and value types specified in the JobConf.setMapInputKeyClass and
JobConf.setMapInputValuesClass methods
B. The InputFormat used by the job determines the mapper's input key and value types.
C. The data types specified in HADOOP_MAP_DATATYPES environment variable
D. The mapper-specification.xml file submitted with the job determine the mapper's input key and value
types.

Question 4

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, 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.
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, no reducer runs and the job throws an exception. With one reducer, instances of
matching patterns are stored in a single file on HDFS.
D. There is no difference in output between the two settings.

Question 5

Which describes how a client reads a file from HDFS?

A. The client queries the NameNode for the block location(s). The NameNode returns the block location(s)
to the client. The client reads the data directory off the DataNode(s).
B. The client contacts the NameNode for the block location(s). The NameNode then queries the
DataNodes for block locations. The DataNodes respond to the NameNode, and the NameNode redirects
the client to the DataNode that holds the requested data block(s). The client then reads the data directly
off the DataNode.
C. The client queries all DataNodes in parallel. The DataNode that contains the requested data responds
directly to the client. The client reads the data directly off the DataNode.
D. The client contacts the NameNode for the block location(s). The NameNode contacts the DataNode
that holds the requested data block. Data is transferred from the DataNode to the NameNode, and then
from the NameNode to the client.