Hadoop 101 Cognitive Class Quiz Answers

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Learn the fundamentals of the Java-based, open-source Apache Hadoop programming platform. Why did it come about?

  • Become familiar with the design of Hadoop and its essential elements, including MapReduce and the Hadoop Distributed File System (HDFS).
  • Acquire knowledge of how to add and delete nodes from Hadoop clusters, as well as how to examine the amount of disc space each node has available and change configuration settings.
  1. Acquaint yourself with additional Apache projects, such as Pig, Hive, HBase, ZooKeeper, Oozie, Sqoop, and Flume, that are a part of the Hadoop ecosystem. Although BDU offers distinct courses on these additional projects, we advise starting here.

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Hadoop 101 Cognitive Class Quiz Answers

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

Q1. 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

Q2. The Hadoop distributed file system (HDFS) is the only distributed file system supported by Hadoop. True or false?

  • True
  • False

Q3. 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

Q4. 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

Q5. 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

Q6. 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

Q7. 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

Q8. 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

Q9. 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

Q10. Which of the following is NOT an open source project related to Hadoop?

  • Pig
  • UIMA
  • Jackal
  • Avro
  • Lucene

Q11. During the replication process, a block of data is written to all specified DataNodes in parallel. True or false?

  • True
  • False

Q12. With IBM BigInsights, Hadoop components can be started and stopped from a command line and from the Ambari Console. True or false?

  • True
  • False

Q13. 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

Q14. 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;

Q15. 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

Q16. 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

Q17. 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

Q18. 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;
Hadoop 101 Cognitive Class 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

GENERAL INFORMATION

  • This course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be audited as many times as you wish.

This free Apache Hadoop course introduces you to Big Data concepts and teaches you how to perform distributed processing of large data sets with Hadoop.

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Review:

Based on our knowledge, we urge you to enroll in this course so you can pick up new skills from specialists. It will be worthwhile, we trust.

 

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