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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

SectionObjectives
Data Warehousing with Hive- HiveQL fundamentals
  • 1. SELECT queries and filtering
    • 2. Tables, partitions, and schemas
      - Advanced Hive features
      • 1. Joins and aggregations
        • 2. Metastore and HCatalog usage
          Hadoop Ecosystem Integration- Data ingestion and ETL workflows
          - HDFS interaction
          - MapReduce basics
          Data Processing with Pig- Pig Latin fundamentals
          • 1. Data types and schemas
            • 2. Loading and storing data
              • 3. Pig operators and transformations
                - Advanced Pig processing
                • 1. User Defined Functions (UDFs)
                  • 2. Joins and grouping

                    Hortonworks-Certified-Apache-Hadoop-2.0-Developer(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) Yes.
                    B) No, but it can be done with either Pig or Hive.
                    C) Yes, but only if one of the tables fits into memory
                    D) No, MapReduce cannot perform relational operations.
                    E) Yes, so long as both tables fit into memory.


                    2. A client application creates an HDFS file named foo.txt with a replication factor of 3. Identify which best
                    describes the file access rules in HDFS if the file has a single block that is stored on data nodes A, B and
                    C?

                    A) Each data node stores a copy of the file in the local file system with the same name as the HDFS file.
                    B) Each data node locks the local file to prohibit concurrent readers and writers of the file.
                    C) The file will be marked as corrupted if data node B fails during the creation of the file.
                    D) The file can be accessed if at least one of the data nodes storing the file is available.


                    3. When can a reduce class also serve as a combiner without affecting the output of a MapReduce program?

                    A) When the types of the reduce operation's input key and input value match the types of the reducer's output key and output value and when the reduce operation is both communicative and associative.
                    B) Always. Code can be reused in Java since it is a polymorphic object-oriented programming language.
                    C) Never. Combiners and reducers must be implemented separately because they serve different purposes.
                    D) When the signature of the reduce method matches the signature of the combine method.
                    E) Always. The point of a combiner is to serve as a mini-reducer directly after the map phase to increase performance.


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

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


                    5. Review the following data and Pig code.
                    M,38,95111 F,29,95060 F,45,95192 M,62,95102 F,56,95102
                    A = LOAD 'data' USING PigStorage('.') as (gender:Chararray, age:int,
                    zlp:chararray);
                    B = FOREACH A GENERATE age;
                    Which one of the following commands would save the results of B to a folder in hdfs named myoutput?

                    A) STORE A INTO 'myoutput' USING PigStorage(',');
                    B) STORE B INTO 'myoutput';
                    C) DUMP B INTO 'myoutput';
                    D) DUMP B using PigStorage('myoutput');


                    Solutions:

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

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