Hortonworks Apache-Hadoop-Developer exam - in .pdf

Apache-Hadoop-Developer pdf
  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
  • Updated: Aug 22, 2026
  • Q & A: 110 Questions and Answers
  • PDF Price: $49.99
  • PDF Demo

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  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
  • Updated: Aug 22, 2026
  • Q & A: 110 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $99.98  $69.99
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Hortonworks Apache-Hadoop-Developer exam - Testing Engine

Apache-Hadoop-Developer Testing Engine
  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
  • Updated: Aug 22, 2026
  • Q & A: 110 Questions and Answers
  • Software Price: $49.99
  • Testing Engine

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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Ingestion- Import data into Hadoop
  • 1. Use Sqoop for relational data import
  • 2. Use Flume for log and event data ingestion
Topic 2: Data Transformation with Pig- Pig Latin programming
  • 1. Load, filter, join, group and aggregate data
  • 2. Transform and process datasets
Topic 3: Data Processing- End-to-end Hadoop workflows
  • 1. Analyze structured and semi-structured data
  • 2. Produce required output using Hadoop ecosystem tools
Topic 4: Data Analysis with Hive- Hive query development
  • 1. Write queries, joins, aggregations and partitions
  • 2. Create and manage databases and tables

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

1. Which process describes the lifecycle of a Mapper?

A) The JobTracker spawns a new Mapper to process all records in a single file.
B) The TaskTracker spawns a new Mapper to process all records in a single input split.
C) The TaskTracker spawns a new Mapper to process each key-value pair.
D) The JobTracker calls the TaskTracker's configure () method, then its map () method and finally its close () method.


2. Which one of the following statements is true regarding a MapReduce job?

A) The Mapper must sort its output of (key.value) pairs in descending order based on value
B) The default Hash Partitioner sends key value pairs with the same key to the same Reducer
C) The job's Partitioner shuffles and sorts all (key.value) pairs and sends the output to all reducers
D) The reduce method is invoked once for each unique value


3. 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, no reducer runs and the job throws an exception. With one reducer, instances of matching patterns are stored in a single file on HDFS.
C) There is no difference in output between the two settings.
D) 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.


4. Indentify which method in the Mapper you should use to implement code for reading the file and populating the associative array?

A) map
B) init
C) configure
D) combine


5. You need to move a file titled "weblogs" into HDFS. When you try to copy the file, you can't. You know you have ample space on your DataNodes. Which action should you take to relieve this situation and store more files in HDFS?

A) Decrease the block size on all current files in HDFS.
B) Increase the amount of memory for the NameNode.
C) Increase the number of disks (or size) for the NameNode.
D) Increase the block size on all current files in HDFS.
E) Decrease the block size on your remaining files.
F) Increase the block size on your remaining files.


Solutions:

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

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