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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

SectionObjectives
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. Resource scheduling concepts
        • 2. Cluster resource allocation
          Apache Hive- Hive architecture
          • 1. Metastore and query execution engine
            - HiveQL Query Language
            • 1. Schema definition and tables
              • 2. SELECT, JOIN, and aggregation queries
                Apache Pig- Pig Latin Programming
                • 1. Data loading and transformation
                  • 2. Filtering, grouping, and joining data
                    - Pig execution model
                    • 1. MapReduce translation of Pig scripts
                      Data Processing and Integration- Hadoop data formats
                      • 1. Text, SequenceFile, and columnar formats
                        - Data ingestion and ETL workflows
                        • 1. Batch processing concepts

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

                          1. Which one of the following statements describes a Hive user-defined aggregate function?

                          A) Operates on a single input row and produces a single row as output
                          B) Operates on a single input row and produces a table as output
                          C) Operates on multiple input rows and produces a table as output
                          D) Operates on multiple input rows and creates a single row as output


                          2. MapReduce v2 (MRv2/YARN) is designed to address which two issues?

                          A) HDFS latency.
                          B) Resource pressure on the JobTracker.
                          C) Single point of failure in the NameNode.
                          D) Reduce complexity of the MapReduce APIs.
                          E) Ability to run frameworks other than MapReduce, such as MPI.
                          F) Standardize on a single MapReduce API.


                          3. Given the following Hive commands:

                          Which one of the following statements Is true?

                          A) The file mydata.txt does not move from Its current location in HDFS
                          B) The file mydata.txt is copied to a subfolder of /apps/hive/warehouse
                          C) The file mydata.txt is moved to a subfolder of /apps/hive/warehouse
                          D) The file mydata.txt is copied into Hive's underlying relational database 0.


                          4. All keys used for intermediate output from mappers must:

                          A) Implement a splittable compression algorithm.
                          B) Be a subclass of FileInputFormat.
                          C) Override isSplitable.
                          D) Implement WritableComparable.
                          E) Implement a comparator for speedy sorting.


                          5. Which one of the following files is required in every Oozie Workflow application?

                          A) Oozie.xml
                          B) Config-default.xml
                          C) job.properties
                          D) Workflow.xml


                          Solutions:

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

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