Hadoop 101 Cognitive Class Exam Answers

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Introduction to Hadoop 101

Hadoop is a powerful framework designed for distributed storage and processing of large data sets across clusters of computers using simple programming models. It is open-source and part of the Apache project, maintained and developed by a global community of contributors.

Key Components of Hadoop:

1. Hadoop Distributed File System (HDFS):
   • HDFS is a distributed file system that stores data across multiple machines without requiring them to be in close proximity. It provides high-throughput access to application data and is fault-tolerant.
2. Yet Another Resource Negotiator (YARN):
   • YARN is a framework responsible for managing computing resources in clusters and scheduling users’ applications. It separates the resource management and job scheduling/monitoring functionalities, allowing for more efficient resource utilization.
3. MapReduce:
   • MapReduce is a programming model and processing engine for distributed computing on large data sets. It consists of two main functions: Map, which processes data in parallel across multiple nodes, and Reduce, which aggregates the results of the Map step.

Benefits of Hadoop:

• Scalability: Hadoop can scale from single servers to thousands of machines, each offering local computation and storage.
• Reliability: It automatically handles hardware failures and ensures data availability.
• Flexibility: It can handle various types of data, structured and unstructured, and supports multiple programming languages.
• Cost-effective: Uses commodity hardware to store large quantities of data.

Ecosystem:

Hadoop has a rich ecosystem with additional components and tools that extend its capabilities, such as Apache Hive (data warehouse infrastructure), Apache Pig (platform for analyzing large data sets), Apache HBase (distributed NoSQL database), and many others.

Conclusion:

Hadoop revolutionized the way large-scale data processing is handled by providing an efficient, scalable, and cost-effective framework. It continues to evolve, addressing new challenges in the field of big data analytics and processing.

Hadoop 101 Cognitive Class Certification Answers

Module 1 – Introduction to Hadoop Quiz Answers

Question 1: Hadoop is designed for Online Transactional Processing. True or False?

• True
• False

Question 2: 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

Question 3: 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 Quiz Answers

Question 1: 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

Question 2: Hadoop works best on a large data set. True or False?

• True
• False

Question 3: HDFS is a fully POSIX compliant file system. True or False?

• True
• False

Module 3 – Hadoop Administration Quiz Answers

Question 1: You can add or remove nodes from the open source Apache Ambari console. True or False?

• True
• False

Question 2: It is recommended that you start all of the services in Ambari in order to speed up communications. True or False?

• True
• False

Question 3: 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 Quiz Answers

Question 1: The output of the shuffle operation goes into the mapper before going into the reducer. True or False?

• True
• False

Question 2: 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
• All of the above

Question 3: Which of the following tools is designed to move data to and from a relational database?

• Pig
• Flume
• Oozie
• Sqoop

Hadoop 101 Final Exam Answers

Question 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

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

• True
• False

Question 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

Question 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

Question 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

Question 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

Question 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

Question 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

Question 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

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

• Pig
• UIMA
• Jackal
• Avro
• Lucene

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

• True
• False

Question 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

Question 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

Question 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

Question 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

Question 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

Question 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

Question 18: In which of these scenarios should Hadoop be used?

• Processing billions of email messages to perform text analytics
• 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