logo
  • Home
  • About
  • Training
  • Programming
  • CS
  • IT
  • IS
  • ECE
  • EEE
  • EE
  • Civil
  • Mechanical
  • Chemical
  • Metallurgy
  • Instrumentation
  • Aeronautical
  • Aerospace
  • Biotechnology
  • Agriculture
  • MCA
  • BCA
  • Internship
  • Contact

Hadoop Multiple Choice Questions | MCQs | Quiz

Hadoop Interview Questions and Answers
Pratice Hadoop questions and answers for interviews, campus placements, online tests, aptitude tests, quizzes and competitive exams.

Get Started

•   Hadoop - History
•   Hadoop - Big Data
•   Hadoop - Ecosystem
•   Hadoop - Mapreduce Basic
•   Hadoop - Analyzing Data
•   Hadoop - Scaling Out
•   Hadoop - Streaming
•   Hadoop - HDFS Basics
•   Hadoop - Java Interface
•   Hadoop - Data Flow
•   Hadoop - Archives
•   Hadoop - I/O
•   Hadoop - Compression
•   Hadoop - Data Integrity
•   Hadoop - Serialization
•   Hadoop - Avro 1
•   Hadoop - Avro 2
•   Mapreduce - Development 1
•   Mapreduce - Development 2
•   MapReduce - Features - 1
•   MapReduce - Features - 2
•   Hadoop - Configuration
•   Hadoop - Security
•   MapReduce - Job - 1
•   MapReduce - Job - 2
•   Hadoop - Task Execution
•   Hadoop - YARN - 1
•   Hadoop - YARN - 2
•   Mapreduce - Types
•   Mapreduce - Formats - 1
•   Mapreduce - Formats - 2
•   Hadoop - Cluster - 1
•   Hadoop - Cluster - 2
•   HDFS - Administration
•   HDFS - Monitoring
•   HDFS - Maintenance
•   Hadoop - Pig Basics
•   Pig - Latin
•   User Defined Functions
•   Data Processing Operators
•   Pig - In Practice
•   Hadoop - Hive Basics
•   Hive - Query Language - 1
•   Hive - Query Language - 2
•   HiveQL - Querying Data - 1
•   HiveQL - Querying Data - 1
•   Hadoop - HBase Basics
•   HBase - Schema Diagram
•   Hbase - Metrics
•   Hadoop - Zookeeper Basics
•   ZooKeeper - Service - 1
•   ZooKeeper - Service - 1
•   Hadoop - Sqoop Basics
•   Hadoop - Sqoop - 1
•   Hadoop - Sqoop 2
•   Hadoop - Cassandra Basics
•   Hadoop - Cassandra - 1
•   Hadoop - Cassandra - 2
•   Hadoop - Incubators - 1
•   Hadoop - Incubators - 2
•   Hadoop - Incubators - 3
•   Hadoop - Chuckwa - 1
•   Hadoop - Chuckwa - 2
•   Hadoop - Ambari
•   Hadoop - Knox
•   Hadoop - HDT
•   Hadoop - Spark - 1
•   Hadoop - Spark - 2
•   Hadoop - Flume
•   Hadoop - Lucene - 1
•   Hadoop - Lucene - 2
•   Hadoop - Hama - 1
•   Hadoop - Hama - 2
•   Hadoop - HCatalog Basics
•   Hadoop - HCatalog - 1
•   Hadoop - HCatalog - 2
•   Hadoop - Mahout
•   Hadoop - Drill
•   Hadoop - Crunch - 1
•   Hadoop - Crunch - 2
•   Hadoop - Thrift - 1
•   Hadoop - Thrift - 2
•   Hadoop - Oozie - 1
•   Hadoop - Oozie - 2
•   Hadoop - Oozie - 3
•   Hadoop - Orchestration
•   Hadoop - BigTop
•   Hadoop - Impala
•   Hadoop - Storm
•   Hadoop - Kafka - 1
•   Hadoop - Kafka - 2
•   Hadoop - Libraries - 1
•   Hadoop - Libraries - 2
•   Hadoop - Utilities - 1
•   Hadoop - Utilities - 2
•   Hadoop - Cloudera
•   Hadoop - Microsoft Azure
•   Amazon Elastic Mapreduce
•   Amazon EC2/S3 services
•   Hadoop - IBM InfoSphere

Best Reference Books

Hadoop Books
« Prev Page
Next Page »

Hadoop Questions and Answers – Mapreduce Development-2

Posted on January 11, 2015 by Manish

This set of Questions & Answers focuses on “Hadoop MapReduce”.

1. The Mapper implementation processes one line at a time via _________ method.
a) map
b) reduce
c) mapper
d) reducer
View Answer

Answer: a
Explanation: The Mapper outputs are sorted and then partitioned per Reducer.

2. Point out the correct statement :
a) Mapper maps input key/value pairs to a set of intermediate key/value pairs
b) Applications typically implement the Mapper and Reducer interfaces to provide the map and reduce methods
c) Mapper and Reducer interfaces form the core of the job
d) None of the mentioned
View Answer

Answer: d
Explanation: The transformed intermediate records do not need to be of the same type as the input records.

3. The Hadoop MapReduce framework spawns one map task for each __________ generated by the InputFormat for the job.
a) OutputSplit
b) InputSplit
c) InputSplitStream
d) All of the mentioned
View Answer

Answer: b
Explanation: Mapper implementations are passed the JobConf for the job via the JobConfigurable.configure(JobConf) method and override it to initialize themselves.

4. Users can control which keys (and hence records) go to which Reducer by implementing a custom :
a) Partitioner
b) OutputSplit
c) Reporter
d) All of the mentioned
View Answer

Answer: a
Explanation: Users can control the grouping by specifying a Comparator via JobConf.setOutputKeyComparatorClass(Class).

5. Point out the wrong statement :
a) The Mapper outputs are sorted and then partitioned per Reducer
b) The total number of partitions is the same as the number of reduce tasks for the job
c) The intermediate, sorted outputs are always stored in a simple (key-len, key, value-len, value) format
d) None of the mentioned
View Answer

Answer: d
Explanation: All intermediate values associated with a given output key are subsequently grouped by the framework, and passed to the Reducer(s) to determine the final output.

6. Applications can use the ____________ to report progress and set application-level status messages
a) Partitioner
b) OutputSplit
c) Reporter
d) All of the mentioned
View Answer

Answer: c
Explanation: Reporter is also used to update Counters, or just indicate that they are alive.

7. The right level of parallelism for maps seems to be around _________ maps per-node
a) 1-10
b) 10-100
c) 100-150
d) 150-200
View Answer

Answer: b
Explanation: Task setup takes a while, so it is best if the maps take at least a minute to execute.

8. The number of reduces for the job is set by the user via :
a) JobConf.setNumTasks(int)
b) JobConf.setNumReduceTasks(int)
c) JobConf.setNumMapTasks(int)
d) All of the mentioned
View Answer

Answer: b
Explanation: Reducer has 3 primary phases: shuffle, sort and reduce.

9. The framework groups Reducer inputs by key in _________ stage.
a) sort
b) shuffle
c) reduce
d) none of the mentioned
View Answer

Answer: a
Explanation: The shuffle and sort phases occur simultaneously; while map-outputs are being fetched they are merged.

10. The output of the reduce task is typically written to the FileSystem via _____________
a) OutputCollector.collect
b) OutputCollector.get
c) OutputCollector.receive
d) OutputCollector.put
View Answer

Answer: a
Explanation: The output of the Reducer is not sorted.

Sanfoundry Global Education & Learning Series – Hadoop.

Here’s the list of Best Reference Books in Hadoop.

To practice all areas of Hadoop MapReduce, here is complete set of 1000+ Multiple Choice Questions and Answers.
« Prev Page - Hadoop Questions and Answers – Mapreduce Development-1
» Next Page - Hadoop Questions and Answers – MapReduce Features-1
« Hadoop Questions and Answers – Mapreduce Development-1
Hadoop Questions and Answers – MapReduce Features-1 »

Deep Dive @ Sanfoundry:

  1. C Programming Examples on Searching and Sorting
  2. Java Programming Examples on Data-Structures
  3. Hadoop Questions and Answers
  4. Hadoop Questions and Answers – Hadoop Streaming
  5. Hadoop Questions and Answers – Mapreduce Formats-1
  6. Hadoop Questions and Answers – MapReduce Features-2
  7. Hadoop Questions and Answers – Task Execution
  8. Hadoop Questions and Answers – Mapreduce Development-1
  9. Hadoop Questions and Answers – Java Interface
  10. Hadoop Questions and Answers – Introduction to Mapreduce
Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer and SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage & Cluster Administration, Advanced C Programming, SAN Storage Technologies, SCSI Internals and Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him below:
LinkedIn | Facebook | Twitter | Google+

Best Careers

Developer Tracks
SAN Developer
Linux Kernel Developer
Linux Driver Developer
Linux Network Developer

Live Training Photos
Mentoring
Software Productivity
GDB Assignment
Sanfoundry is No. 1 choice for Deep Hands-ON Trainings in SAN, Linux & C, Kernel Programming. Our Founder has trained employees of almost all Top Companies in India such as VMware, Citrix, Oracle, Motorola, Ericsson, Aricent, HP, Intuit, Microsoft, Cisco, SAP Labs, Siemens, Symantec, Redhat, Chelsio, Cavium, ST-Micro, Samsung, LG-Soft, Wipro, TCS, HCL, IBM, Accenture, HSBC, Mphasis, Tata-Elxsi, Tata VSNL, Mindtree, Cognizant and Startups.

Best Trainings

SAN I - Technology
SAN II - Admin
Linux Fundamentals
Advanced C Training
Linux-C Debugging
System Programming
Network Programming
Linux Threads
Kernel Programming
Kernel Debugging
Linux Device Drivers

Best Reference Books

Computer Science Books
Algorithm & Programming Books
Electronics Engineering Books
Electrical Engineering Books
Chemical Engineering Books
Civil Engineering Books
Mechanical Engineering Books
Industrial Engineering Books
Instrumentation Engg Books
Metallurgical Engineering Books
All Stream Best Books

Questions and Answers

1000 C Questions & Answers
1000 C++ Questions & Answers
1000 C# Questions & Answers
1000 Java Questions & Answers
1000 Linux Questions & Answers
1000 Python Questions
1000 PHP Questions & Answers
1000 Hadoop Questions
Cloud Computing Questions
Computer Science Questions
All Stream Questions & Answers

India Internships

Computer Science Internships
Instrumentation Internships
Electronics Internships
Electrical Internships
Mechanical Internships
Industrial Internships
Systems Internships
Chemical Internships
Civil Internships
IT Internships
All Stream Internships

About Sanfoundry

About Us
Copyright
TOS & Privacy
Jobs
Bangalore Training
Online Training
SAN Training
Developers Track
Mentoring Sessions
Contact Us
Sitemap
© 2011 Sanfoundry