Hortonworks : HADOOP-PR000007 Questions & Answers
Last Updated: Sep 17, 2026
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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Hadoop Fundamentals & HDFS | 20% | - Hadoop 2.0 architecture & YARN - HDFS file operations, permissions, and data management |
| Topic 2: Apache Hive Development | 35% | - HiveQL queries, joins, aggregations, and partitioning - Data types, serialization, and file formats - Hive architecture, metastore, and table management - Performance tuning and indexing |
| Topic 3: Apache Pig Development | 40% | - Pig Latin syntax, data loading, and storage - Data transformation, filtering, grouping, and joining - Integration with HCatalog and Hive - User-defined functions (UDFs) and optimization |
| Topic 4: Data Ingestion & Ecosystem Integration | 5% | - Sqoop and Flume usage basics - Workflow orchestration with Oozie |
Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:
Which Hadoop component is responsible for managing the distributed file system metadata?
- A. NameNode
- B. Metanode
- C. NameSpaceManager
- D. DataNode
Correct Answer: A 🗳️
Which one of the following statements is true regarding a MapReduce job?
- A. The job's Partitioner shuffles and sorts all (key.value) pairs and sends the output to all reducers
- B. The reduce method is invoked once for each unique value
- C. The Mapper must sort its output of (key.value) pairs in descending order based on value
- D. The default Hash Partitioner sends key value pairs with the same key to the same Reducer
Correct Answer: A 🗳️
In Hadoop 2.0, which one of the following statements is true about a standby NameNode?
The Standby NameNode:
- A. Processes all client requests and block reports from the appropriate DataNodes.
- B. Receives the same block reports as the active NameNode.
- C. Communicates directly with the active NameNode to maintain the state of the active NameNode.
- D. Runs on the same machine and shares the memory of the active NameNode.
Correct Answer: B 🗳️
How are keys and values presented and passed to the reducers during a standard sort and shuffle phase of MapReduce?
- A. Keys are presented to a reducer in random order; values for a given key are sorted in ascending order.
- B. Keys are presented to a reducer in random order; values for a given key are not sorted.
- C. Keys are presented to reducer in sorted order; values for a given key are sorted in ascending order.
- D. Keys are presented to reducer in sorted order; values for a given key are not sorted.
Correct Answer: D 🗳️
In a MapReduce job, you want each of your input files processed by a single map task. How do you
configure a MapReduce job so that a single map task processes each input file regardless of how many
blocks the input file occupies?
- A. Write a custom FileInputFormat and override the method isSplitable to always return false.
- B. Write a custom MapRunner that iterates over all key-value pairs in the entire file.
- C. Set the number of mappers equal to the number of input files you want to process.
- D. Increase the parameter that controls minimum split size in the job configuration.
Correct Answer: A 🗳️
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