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


"Hadoop 2.0 Certification exam for Pig and Hive Developer", also known as Apache-Hadoop-Developer exam, is a Hortonworks Certification. With the complete collection of questions and answers, Pass4sureCert has assembled to take you through 110 Q&As to your Apache-Hadoop-Developer Exam preparation. In the Apache-Hadoop-Developer exam resources, you will cover every field and category in HCAHD Certification helping to ready you for your successful Hortonworks Certification.

  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
  • Total Questions: 110
  • Certification Provider: Hortonworks
  • Corresponding Certification: HCAHD
  • Updated on: Aug 06, 2026

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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

SectionObjectives
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
        Apache Hive- Hive architecture
        • 1. Metastore and query execution engine
          - HiveQL Query Language
          • 1. Schema definition and tables
            • 2. SELECT, JOIN, and aggregation queries
              Data Processing and Integration- Data ingestion and ETL workflows
              • 1. Batch processing concepts
                - Hadoop data formats
                • 1. Text, SequenceFile, and columnar formats
                  Hadoop Ecosystem Fundamentals- HDFS Architecture and Data Storage Concepts
                  • 1. NameNode and DataNode roles
                    • 2. Data replication and fault tolerance
                      - YARN and Resource Management
                      • 1. Cluster resource allocation
                        • 2. Resource scheduling concepts

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

                          1. How are keys and values presented and passed to the reducers during a standard sort and shuffle phase of MapReduce?

                          A) Keys are presented to reducer in sorted order; values for a given key are sorted in ascending order.
                          B) Keys are presented to a reducer in random order; values for a given key are not sorted.
                          C) Keys are presented to a reducer in random order; values for a given key are sorted in ascending order.
                          D) Keys are presented to reducer in sorted order; values for a given key are not sorted.


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


                          3. In Hadoop 2.0, which TWO of the following processes work together to provide automatic failover of the NameNode? Choose 2 answers

                          A) JournalNode
                          B) QuorumManager
                          C) ZooKeeper
                          D) ZKFailoverController


                          4. In a MapReduce job with 500 map tasks, how many map task attempts will there be?

                          A) At least 500.
                          B) It depends on the number of reduces in the job.
                          C) Exactly 500.
                          D) At most 500.
                          E) Between 500 and 1000.


                          5. Which HDFS command copies an HDFS file named foo to the local filesystem as localFoo?

                          A) hadoop fs -Is foo
                          B) hadoop fs -put foo LocalFoo
                          C) hadoop -cp foo LocalFoo
                          D) hadoop fs -get foo LocalFoo


                          Solutions:

                          Question # 1
                          Answer: D
                          Question # 2
                          Answer: D
                          Question # 3
                          Answer: A,D
                          Question # 4
                          Answer: A
                          Question # 5
                          Answer: D

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