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Hadoop 101 Cognitive Class Exam Answers 2024

Hadoop 101 Cognitive Class Exam Answers 2024

About This Course Learn the basics of 

Apache Hadoop, a free, open source, Java-based programming framework. Why was it invented?

  • Learn about Hadoop’s architecture and core components, such as MapReduce and the Hadoop Distributed File System (HDFS).
  • Learn how to add and remove nodes from Hadoop clusters, how to check available disk space on each node, and how to modify configuration parameters.
  • Learn about other Apache projects that are part of the Hadoop ecosystem, including Pig, Hive, HBase, ZooKeeper, Oozie, Sqoop, Flume, among others. BDUprovides separate courses on these other projects, but we recommend you start here.

Module 1: Introduction to Hadoop

Q1) Hadoop is designed for Online Transactional Processing. True or False?

  • True
  • False

Q2) When is Hadoop useful for an application?

  • When all of the application data is unstructured
  • When work can be parallelized
  • When the application requires low latency data access
  • When random data access is required

Q3) With the help of InfoSphere Streams, Hadoop can be used with data-at-rest as well as data-in-motion. True or false?

  • True
  • False     

Module 2: Hadoop Architecture & HDFS

Q1) Network bandwidth between any two nodes in the same rack is greater than bandwidth between two nodes on different racks. True or False?

  • True
  • False

Q2) Hadoop works best on a large data set. True or False?

  • True
  • False

Q3) HDFS is a fully POSIX compliant file system. True or False?

  • True
  • False

Module 3: Hadoop Administration

Q1) You can add or remove nodes from the open source Apache Ambari console. True or False?

  • True
  • False

Q2) It is recommended that you start all of the services in Ambari in order to speed up communications. True or False?

  • True
  • False

Q3) To remove a node using Ambari, you must first remove all of the services using that node. True or False?

  • True
  • False

Module 4: Hadoop Components

Q1) The output of the shuffle operation goes into the mapper before going into the reducer. True or False?

  • True
  • False

Q2) What is true about Pig and Hive in relation to the Hadoop ecosystem?

  • HiveQL requires that you create the data flow
  • PigLatin requires that the data have a schema
  • Fewer lines of code are required compared to a Java program correct
  • All of the above

Q3) Which of the following tools is designed to move data to and from a relational database?

  • Pig
  • Flume
  • Oozie
  • Sqoop

Final Exam Answers HADOOP Certification by IBM

1. HDFS is designed for:

  • Large files, streaming data access, and commodity hardware
  • Large files, low latency data access, and commodity hardware
  • Large files, streaming data access, and high-end hardware
  • Small files, streaming data access, and commodity hardware
  • None of the options is correct

2. The Hadoop distributed file system (HDFS) is the only distributed file system supported by Hadoop. True or false?

  • True
  • False

3. The input to a mapper takes the form < k1, v1 > . What form does the mapper’s output take?

  • < list(k2), v2 >
  • list( < k2, v2 > )
  • < k2, list(v2) >
  • < k1, v1 >
  • None of the options is correct

4. What is Flume?

  • A service for moving large amounts of data around a cluster soon after the data is produced.
  • A distributed file system.
  • A programming language that translates high-level queries into map tasks and reduce tasks.
  • A platform for executing MapReduce jobs.
  • None of the options is correct

5. What is the purpose of the shuffle operation in Hadoop MapReduce?

  • To pre-sort the data before it enters each mapper node.
  • To distribute input splits among mapper nodes.
  • To transfer each mapper’s output to the appropriate reducer node based on a partitioning function.
  • To randomly distribute mapper output among reducer nodes.
  • None of the options is correct

6. Which of the following is a duty of the DataNodes in HDFS?

  • Control the execution of an individual map task or a reduce task.
  • Maintain the file system tree and metadata for all files and directories.
  • Manage the file system namespace.
  • Store and retrieve blocks when told to by clients or the NameNode.
  • None of the options is correct

7. Which of the following is a duty of the NameNode in HDFS?

  • Control the MapReduce job from end-to-end
  • Maintain the file system tree and metadata for all files and directories
  • Store the block data
  • Transfer block data from the data nodes to the clients
  • None of the options is correct

8. Which component determines the specific nodes that a MapReduce task will run on?

  • The NameNode
  • The JobTracker
  • The TaskTrackers
  • The JobClient
  • None of the options is correct

9). Which of the following characteristics is common to Pig, Hive, and Jaql?

  • All translate high-level languages to MapReduce jobs
  • All operate on JSON data structures
  • All are data flow languages
  • All support random reads/writes

               None of the options is correct    

10. Which of the following is NOT an open source project related to Hadoop?

  • Pig
  • UIMA
  • Jackal
  • Avro
  • Lucene

11. During the replication process, a block of data is written to all specified DataNodes in parallel. True or false?

  • True
  • False

12. With IBM BigInsights, Hadoop components can be started and stopped from a command line and from the Ambari Console. True or false?

  • True
  • False

13. When loading data into HDFS, data is held at the NameNode until the block is filled and then the data is sent to a DataNode. True or false?

  • True
  • False

14. Which of the following is true about the Hadoop federation?

  • Uses JournalNodes to decide the active NameNode
  • Allows non-Hadoop programs to access data in HDFS
  • Allows multiple NameNodes with their own namespaces to share a pool of DataNodes
  • Implements a resource manager external to all Hadoop frameworks

15. Which of the following is true about Hadoop high availability?

  • Uses JournalNodes to decide the active NameNode
  • Allows non-Hadoop programs to access data in HDFS
  • Allows multiple NameNodes with their own namespaces to share a pool of DataNodes
  • Implements a resource manager external to all Hadoop frameworks

16. Which of the following is true about YARN?

  • Uses JournalNodes to decide the active NameNode
  • Allows non-Hadoop programs to access data in HDFS
  • Allows multiple NameNodes with their own namespaces to share a pool of DataNodes
  • Implements a resource manager external to all Hadoop frameworks

17. Which of the following sentences is true?

  • Hadoop is good for OLTP, DSS, and big data
  • Hadoop includes open source components and closed source components
  • Hadoop is a new technology designed to replace relational databases
  • All of the options are correct
  • None of the options is correct

18. In which of these scenarios should Hadoop be used?

  • Processing billions of email messages to perform text analytics correct
  • Obtaining stock price trends on a per-minute basis
  • Processing weather sensor information to predict a hurricane path
  • Analyzing vital signs of a baby in real time
  • None of the options is correct

COURSE SYLLABUS

Module 1 –  Introduction to Hadoop

  • Understand what Hadoop is
  • Understand what Big Data is
  • Learn about other open source software related to Hadoop
  • Understand how Big Data solutions can work on the Cloud

Module 2 – Hadoop Architecture

  • Understand the main Hadoop components
  • Learn how HDFS works
  • List data access patterns for which HDFS is designed
  • Describe how data is stored in an HDFS cluster

Module 3 – Hadoop Administration

  • Add and remove nodes from a cluster
  • Verify the health of a clusterStart and stop a clusters components
  • Modify Hadoop configuration parameters
  • Setup a rack topology

Module 4 – Hadoop Components

  • Describe the MapReduce philosophy
  • Explain how Pig and Hive can be used in a Hadoop environment
  • Describe how Flume and Sqoop can be used to move data into Hadoop
  • Describe how Oozie is used to schedule and control Hadoop job execution

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