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Big Data and Hadoop Free Certificate | Free Quiz Certificate | The Digital Adda

Apache Hadoop is an open source framework that is used to efficiently store and process large datasets ranging in size from gigabytes to petabytes of data. Instead of using one large computer to store and process the data, Hadoop allows clustering multiple computers to analyze massive datasets in parallel more quickly.

Get Big Data and Hadoop  certificate from The Digital Adda which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

TERMS AND CONDITIONS:

  • There are 20 MCQ Questions in this test
  • You need to score atleast 50% to get a certificate
  • A certificate of achievement will be awarded .
  • Structured
  • Semi – structured
  • Unstructured
  • All of the above
  • Python
  • Java
  • C++
  • Scala
  • Bare metal
  • Unix-like
  • Cross-platform
  • Debian
  • Hadoop MapReduce processes the data at very low latency
  • Hadoop can’t handle structured data
  • Hadoop is schema-less – we don’t need to define a schema before writing the data
  • None of the above
  • Data locality means moving computation to data instead of data to computation
  • Data locality means moving data to computation instead of computation to data
  • Both the above
  • None of the above
  • It is a distributed framework
  • The main algorithm used in Hadoop is Map Reduce
  • Hadoop can work with commodity hardware
  • All are true
  • YARN
  • HDFS
  • MapReduce
  • All of the above
  • Apache License 2.0
  • Shareware
  • Mozilla Public License
  • Commercial
  • NameNode
  • Node manager
  • DataNode
  • All of the above
  • Filesystem
  • RAID
  • Local FS
  • Operating system
  • Centralized processing fashion
  • master – slave fashion
  • worker/slave fashion
  • All of the mentioned
  • Replication factor
  • Java Environment variables
  • Directory names to store hdfs files
  • Which framework to use with MapReduce jobs
  • .hrh
  • .har
  • .hrc
  • .hrar
  • Flume
  • Oozie
  • Hive
  • Kafka
  • Has higher data Integrity
  • Does ACID transactions
  • Is suitable for read and write many times
  • Works better on unstructured and semi-structured data
  • Java
  • Python
  • C++
  • All of the above
  • hadoop fsck / -files -blocks
  • hadoop fsck / -blocks -files
  • hadoop ls / -blocks -files
  • hadoop fchk / -files -blocks
  • Synchronization & coordination engine
  • NoSQL database
  • Data collection & aggregation system
  • Data processing engine
  • Open source
  • Real-time data processing system
  • Java-based
  • Distributed computing approach
  • Sqoop
  • Flume
  • Oozie
  • Drill

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