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Hortonworks Apache-Hadoop-Developer Actual Tests : Hadoop 2.0 Certification exam for Pig and Hive Developer

Apache-Hadoop-Developer actual test
  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
  • Updated: Aug 18, 2026
  • Q & A: 110 Questions and Answers
  • PDF Demo
  • PC Test Engine
  • Online Test Engine
  • Total Price: $49.99  

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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Transformation with Pig- Pig Latin programming
  • 1. Load, filter, join, group and aggregate data
  • 2. Transform and process datasets
Topic 2: Data Ingestion- Import data into Hadoop
  • 1. Use Flume for log and event data ingestion
  • 2. Use Sqoop for relational data import
Topic 3: Data Analysis with Hive- Hive query development
  • 1. Create and manage databases and tables
  • 2. Write queries, joins, aggregations and partitions
Topic 4: Data Processing- End-to-end Hadoop workflows
  • 1. Produce required output using Hadoop ecosystem tools
  • 2. Analyze structured and semi-structured data

Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:

1. Which one of the following statements is false about HCatalog?

A) Exists as a subproject of Hive
B) Provides a shared schema mechanism
C) Designed to be used by other programs such as Pig, Hive and MapReduce
D) Stores HDFS data in a database for performing SQL-like ad-hoc queries


2. What does Pig provide to the overall Hadoop solution?

A) Database table and storage management services
B) Legacy language Integration with MapReduce framework
C) C++ interface to MapReduce and data warehouse infrastructure
D) Simple scripting language for writing MapReduce programs


3. You need to run the same job many times with minor variations. Rather than hardcoding all job configuration options in your drive code, you've decided to have your Driver subclass org.apache.hadoop.conf.Configured and implement the org.apache.hadoop.util.Tool interface.
Indentify which invocation correctly passes.mapred.job.name with a value of Example to Hadoop?

A) hadoop "mapred.job.name=Example" MyDriver input output
B) hadoop setproperty ("mapred.job.name=Example") MyDriver input output
C) hadoop MyDriver mapred.job.name=Example input output
D) hadoop setproperty mapred.job.name=Example MyDriver input output
E) hadoop MyDrive -D mapred.job.name=Example input output


4. Identify the tool best suited to import a portion of a relational database every day as files into HDFS, and generate Java classes to interact with that imported data?

A) Hue
B) Sqoop
C) Pig
D) Oozie
E) Hive
F) Flume
G) fuse-dfs


5. Determine which best describes when the reduce method is first called in a MapReduce job?

A) Reduce methods and map methods all start at the beginning of a job, in order to provide optimal performance for map-only or reduce-only jobs.
B) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The reduce method is called only after all intermediate data has been copied and sorted.
C) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The reduce method is called as soon as the intermediate key-value pairs start to arrive.
D) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The programmer can configure in the job what percentage of the intermediate data should arrive before the reduce method begins.


Solutions:

Question # 1
Answer: D
Question # 2
Answer: D
Question # 3
Answer: E
Question # 4
Answer: B
Question # 5
Answer: B

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