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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

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

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

                          1. 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) Flume
                          C) Hive
                          D) fuse-dfs
                          E) Sqoop
                          F) Oozie
                          G) Pig


                          2. Examine the following Hive statements:

                          Assuming the statements above execute successfully, which one of the following statements is true?

                          A) The SORT BY command causes only one reducer to be used
                          B) The output is guaranteed to be a single file with all the data sorted by age
                          C) The output of each reducer is only the age column
                          D) Each reducer generates a file sorted by age


                          3. Which Hadoop component is responsible for managing the distributed file system metadata?

                          A) DataNode
                          B) NameSpaceManager
                          C) Metanode
                          D) NameNode


                          4. Review the following 'data' file and Pig code.

                          Which one of the following statements is true?

                          A) The code executes successfully but there is not output because the D relation is empty
                          B) The code does not execute successfully because D is not a valid relation
                          C) The output of the dump d command is (M, {(38,95in),(62,95i02)})
                          D) The Output Of the DUMP D command IS (M,{(M,62.95102),(M,38,95111)})


                          5. You are developing a combiner that takes as input Text keys, IntWritable values, and emits Text keys, IntWritable values. Which interface should your class implement?

                          A) Reducer <Text, Text, IntWritable, IntWritable>
                          B) Combiner <Text, IntWritable, Text, IntWritable>
                          C) Combiner <Text, Text, IntWritable, IntWritable>
                          D) Reducer <Text, IntWritable, Text, IntWritable>
                          E) Mapper <Text, IntWritable, Text, IntWritable>


                          Solutions:

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

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