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

Apache-Hadoop-Developer

Exam Code: Apache-Hadoop-Developer

Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer

Updated: Sep 12, 2026

Q & A: 110 Questions and Answers

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About Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer certification

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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

SectionObjectives
Topic 1: Apache Hive- Hive architecture
  • 1. Metastore and query execution engine
    - HiveQL Query Language
    • 1. SELECT, JOIN, and aggregation queries
      • 2. Schema definition and tables
        Topic 2: Apache Pig- Pig Latin Programming
        • 1. Filtering, grouping, and joining data
          • 2. Data loading and transformation
            - Pig execution model
            • 1. MapReduce translation of Pig scripts
              Topic 3: Data Processing and Integration- Hadoop data formats
              • 1. Text, SequenceFile, and columnar formats
                - Data ingestion and ETL workflows
                • 1. Batch processing concepts
                  Topic 4: Hadoop Ecosystem Fundamentals- YARN and Resource Management
                  • 1. Resource scheduling concepts
                    • 2. Cluster resource allocation
                      - HDFS Architecture and Data Storage Concepts
                      • 1. Data replication and fault tolerance
                        • 2. NameNode and DataNode roles

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

                          Question #1
                          You have written a Mapper which invokes the following five calls to the OutputColletor.collect method:
                          output.collect (new Text ("Apple"), new Text ("Red") ) ;
                          output.collect (new Text ("Banana"), new Text ("Yellow") ) ;
                          output.collect (new Text ("Apple"), new Text ("Yellow") ) ;
                          output.collect (new Text ("Cherry"), new Text ("Red") ) ;
                          output.collect (new Text ("Apple"), new Text ("Green") ) ;
                          How many times will the Reducer's reduce method be invoked?

                          A. 1
                          B. 5
                          C. 6
                          D. 0
                          E. 3


                          Question #2
                          To process input key-value pairs, your mapper needs to lead a 512 MB data file in memory. What is the best way to accomplish this?

                          A. Serialize the data file, insert in it the JobConf object, and read the data into memory in the configure method of the mapper.
                          B. Place the data file in the DistributedCache and read the data into memory in the configure method of the mapper.
                          C. Place the data file in the DataCache and read the data into memory in the configure method of the mapper.
                          D. Place the data file in the DistributedCache and read the data into memory in the map method of the mapper.


                          Question #3
                          When is the earliest point at which the reduce method of a given Reducer can be called?

                          A. As soon as a mapper has emitted at least one record.
                          B. Not until all mappers have finished processing all records.
                          C. It depends on the InputFormat used for the job.
                          D. As soon as at least one mapper has finished processing its input split.


                          Question #4
                          Workflows expressed in Oozie can contain:

                          A. Sequences of MapReduce job only; on Pig on Hive tasks or jobs. These MapReduce sequences can be combined with forks and path joins.
                          B. Iterntive repetition of MapReduce jobs until a desired answer or state is reached.
                          C. Sequences of MapReduce and Pig. These sequences can be combined with other actions including forks, decision points, and path joins.
                          D. Sequences of MapReduce and Pig jobs. These are limited to linear sequences of actions with exception handlers but no forks.


                          Question #5
                          Which Two of the following statements are true about hdfs? Choose 2 answers

                          A. Block sizes for all files must be the same size
                          B. Blocks are replicated to multiple datanodes
                          C. An HDFS file that is larger than dfs.block.size is split into blocks
                          D. HDFS works best when storing a large number of relatively small files


                          Solutions:

                          Question #1
                          Correct Answer: E
                          Question #2
                          Correct Answer: C
                          Question #3
                          Correct Answer: B
                          Question #4
                          Correct Answer: C
                          Question #5
                          Correct Answer: B,C

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