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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

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

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

Question 1

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. 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.
B. Package your code and the Apache Commands Math library into a zip file named JobJar.zip
C. 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.
D. When submitting the job on the command line, specify the -libjars option followed by the JAR file path.

Question 2

Which one of the following statements is true regarding a MapReduce job?

A. The default Hash Partitioner sends key value pairs with the same key to the same Reducer
B. The Mapper must sort its output of (key.value) pairs in descending order based on value
C. The job's Partitioner shuffles and sorts all (key.value) pairs and sends the output to all reducers
D. The reduce method is invoked once for each unique value

Question 3

Can you use MapReduce to perform a relational join on two large tables sharing a key? Assume that the
two tables are formatted as comma-separated files in HDFS.

A. No, MapReduce cannot perform relational operations.
B. Yes, so long as both tables fit into memory.
C. No, but it can be done with either Pig or Hive.
D. Yes.
E. Yes, but only if one of the tables fits into memory

Question 4

Which best describes how TextInputFormat processes input files and line breaks?

A. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReaders of
both splits containing the broken line.
B. Input file splits may cross line breaks. A line that crosses file splits is ignored.
C. 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 broken line.
D. The input file is split exactly at the line breaks, so each RecordReader will read a series of complete
lines.
E. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of the
split that contains the beginning of the broken line.

Question 5

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

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