Hadoop 101 Cognitive Class Exam Answers 100% Correct [Latest Updated ]

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Hadoop 101 Cognitive Class Exam Answers 100% Correct [Latest Updated ]

Here you will find ✅✅✅ all the Hadoop 101 Cognitive Class Exam Answers below marked in  Bold Color. These Accelerating Deep Learning with GPUs Cognitive Class quiz Answers have been updated recently with the latest questions asked in the previous examination with full explanations that you will get when you tap on the question.

Here are the 100 % correct answers of all the modules and the final exam of Hadoop IBM Course Certificate Exam Answers – Cognitive Class Hadoop 101 Answers

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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

Conclusion

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  137. 539開獎
    《539彩券：台灣的小確幸》

    哎呀，說到台灣的彩券遊戲，你怎麼可能不知道539彩券呢？每次”539開獎”，都有那麼多人緊張地盯著螢幕，心想：「這次會不會輪到我？」。

    ### 539彩券，那是什麼來頭？

    嘿，539彩券可不是昨天才有的新鮮事，它在台灣已經陪伴了我們好多年了。簡單的玩法，小小的投注，卻有著不小的期待，難怪它這麼受歡迎。

    ### 539開獎，是場視覺盛宴！

    每次”539開獎”，都像是一場小型的節目。專業的主持人、明亮的燈光，還有那台專業的抽獎機器，每次都帶給我們不小的刺激。

    ### 跟我一起玩539？

    想玩539？超簡單！走到街上，找個彩券行，選五個你喜歡的號碼，買下來就對了。當然，現在科技這麼發達，坐在家裡也能買，多方便！

    ### 539開獎，那刺激的感覺！

    每次”539開獎”，真的是讓人既期待又緊張。想像一下，如果這次中了，是不是可以去吃那家一直想去但又覺得太貴的餐廳？

    ### 最後說兩句

    539彩券，真的是個小確幸。但嘿，玩彩券也要有度，別太沉迷哦！希望每次”539開獎”，都能帶給你一點點的驚喜和快樂。

    Reply

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