Hortonworks HADOOP-PR000007 Actual PDF : Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer)

Hortonworks HADOOP-PR000007 Actual PDF
  • Exam Code: HADOOP-PR000007
  • Exam Name: Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer)
  • Updated: Jul 20, 2026
  • Q & A: 110 Questions and Answers
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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

SectionObjectives
Data Processing with Pig- Pig Latin fundamentals
  • 1. Pig operators and transformations
    • 2. Loading and storing data
      • 3. Data types and schemas
        - Advanced Pig processing
        • 1. Joins and grouping
          • 2. User Defined Functions (UDFs)
            Hadoop Ecosystem Integration- Data ingestion and ETL workflows
            - HDFS interaction
            - MapReduce basics
            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

                    Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:

                    1. 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) ZKFailoverController
                    C) QuorumManager
                    D) ZooKeeper


                    2. You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses
                    TextInputFormat: the mapper applies a regular expression over input values and emits key-values pairs
                    with the key consisting of the matching text, and the value containing the filename and byte offset.
                    Determine the difference between setting the number of reduces to one and settings the number of
                    reducers to zero.

                    A) With zero reducers, all instances of matching patterns are gathered together in one file on HDFS. With
                    one reducer, instances of matching patterns are stored in multiple files on HDFS.
                    B) With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one
                    reducer, all instances of matching patterns are gathered together in one file on HDFS.
                    C) There is no difference in output between the two settings.
                    D) With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances of
                    matching patterns are stored in a single file on HDFS.


                    3. Which two of the following statements are true about Pig's approach toward data? Choose 2 answers

                    A) Accepts only data that has a key/value pair structure
                    B) Accepts only data that is defined by metadata tables stored in a database
                    C) Accepts data whether it has metadata or not
                    D) Accepts tab-delimited text data only
                    E) Accepts any data: structured or unstructured


                    4. Which describes how a client reads a file from HDFS?

                    A) The client queries all DataNodes in parallel. The DataNode that contains the requested data responds
                    directly to the client. The client reads the data directly off the DataNode.
                    B) The client contacts the NameNode for the block location(s). The NameNode contacts the DataNode
                    that holds the requested data block. Data is transferred from the DataNode to the NameNode, and then
                    from the NameNode to the client.
                    C) The client contacts the NameNode for the block location(s). The NameNode then queries the
                    DataNodes for block locations. The DataNodes respond to the NameNode, and the NameNode redirects
                    the client to the DataNode that holds the requested data block(s). The client then reads the data directly
                    off the DataNode.
                    D) The client queries the NameNode for the block location(s). The NameNode returns the block location(s)
                    to the client. The client reads the data directory off the DataNode(s).


                    5. For each input key-value pair, mappers can emit:

                    A) One intermediate key-value pair, of a different type.
                    B) As many intermediate key-value pairs as designed, but they cannot be of the same type as the input
                    key-value pair.
                    C) One intermediate key-value pair, but of the same type.
                    D) As many intermediate key-value pairs as designed. There are no restrictions on the types of those
                    key-value pairs (i.e., they can be heterogeneous).
                    E) As many intermediate key-value pairs as designed, as long as all the keys have the same types and all
                    the values have the same type.


                    Solutions:

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

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