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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

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

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

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


                          2. Table metadata in Hive is:

                          A) Stored along with the data in HDFS.
                          B) Stored in the Metastore.
                          C) Stored as metadata on the NameNode.
                          D) Stored in ZooKeeper.


                          3. You've written a MapReduce job that will process 500 million input records and generated 500 million key-value pairs. The data is not uniformly distributed. Your MapReduce job will create a significant amount of intermediate data that it needs to transfer between mappers and reduces which is a potential bottleneck. A custom implementation of which interface is most likely to reduce the amount of intermediate data transferred across the network?

                          A) InputFormat
                          B) OutputFormat
                          C) WritableComparable
                          D) Writable
                          E) Partitioner
                          F) Combiner


                          4. What are the TWO main components of the YARN ResourceManager process? Choose 2 answers

                          A) Task Tracker
                          B) Applications Manager
                          C) Scheduler
                          D) Job Tracker


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

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


                          Solutions:

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

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