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LinkedIn Hadoop assessment answers

LinkedIn Hadoop Assessment

 

 

LinkedIn Hadoop Assessment Answers

LinkedIn Hadoop Assessment Answers 2021 feature is recently introduced by LinkedIn. These assessments are actually quiz-dependent on multiple-choice questions. Each assessment has around 15 questions which are taken randomly from a major pool of questions that are accessible in various categories. Passing these assessments will earn you an assessment identification that will appear alongside your skill on your LinkedIn profile. In the event that you bomb an assessment or got an underwhelming score, you can retake it after 3 months We can help you pass LinkedIn skill assessments with a high score for sure.

The LinkedIn Skill Assessments feature allows you to demonstrate your knowledge of the skills you’ve added on your profile. Job posters on LinkedIn can also add Skill Assessments as part of the job application process. This allows job posters to more efficiently and accurately verify the crucial skills a candidate should have for a role.

The topics in the Hadoop assessment include:

  • Hadoop Common
  • Hadoop Components
  • MapReduce
  • Using Hadoop
  • Hadoop Concepts
  • Hadoop Optimization

Question Format

Multiple Choice

Language

English

Linkedin Hadoop Assessment Questions and  Answers

Q1. Partitioner controls the partitioning of what data?

  •  final keys
  •  final values
  •  intermediate keys
  •  intermediate values
Q2. SQL Windowing functions are implemented in Hive using which keywords?
  •  UNION DISTINCT, RANK
  •  OVER, RANK
  •  OVER, EXCEPT
  •  UNION DISTINCT, RANK
Q3. Rather than adding a Secondary Sort to a slow Reduce job, it is Hadoop best practice to perform which optimization?
  •  Add a partitioned shuffle to the Map job.
  •  Add a partitioned shuffle to the Reduce job.
  •  Break the Reduce job into multiple, chained Reduce jobs.
  •  Break the Reduce job into multiple, chained Map jobs.
Q4. Hadoop Auth enforces authentication on protected resources. Once authentication has been established, it sets what type of authenticating cookie?
  •  encrypted HTTP
  •  unsigned HTTP
  •  compressed HTTP
  •  signed HTTP
Q5. MapReduce jobs can be written in which language?
  •  Java or Python
  •  SQL only
  •  SQL or Java
  •  Python or SQL
Q6. To perform local aggregation of the intermediate outputs, MapReduce users can optionally specify which object?
  •  Reducer
  •  Combiner
  •  Mapper
  •  Counter
Q7. To verify job status, look for the value **\_** in the **\_**.
 
  •  SUCCEEDED; syslog
  •  SUCCEEDED; stdout
  •  DONE; syslog
  •  DONE; stdout
Q8. Which line of code implements a Reducer method in MapReduce 2.0?
  •  public void reduce(Text key, Iterator values, Context context){…}
  •  public static void reduce(Text key, IntWritable[] values, Context context){…}
  •  public static void reduce(Text key, Iterator values, Context context){…}
  •  public void reduce(Text key, IntWritable[] values, Context context){…}
Q9. To get the total number of mapped input records in a map job task, you should review the value of which counter?
  •  FileInputFormatCounter
  •  FileSystemCounter
  •  JobCounter
  •  TaskCounter (NOT SURE)
Q10. Hadoop Core supports which CAP capabilities?
  •  A, P
  •  C, A
  •  C, P
  •  C, A, P
Q11. What are the primary phases of a Reducer?
  •  combine, map, and reduce
  •  shuffle, sort, and reduce
  •  reduce, sort, and combine
  •  map, sort, and combine
Q12. To set up Hadoop workflow with synchronization of data between jobs that process tasks both on disk and in memory, use the _ service, which is _.
  •  Oozie; open source
  •  Oozie; commercial software
  •  Zookeeper; commercial software
  •  Zookeeper; open source
Q13. For high availability, use multiple nodes of which type?
  •  data
  •  name
  •  memory
  •  worker
Q14. DataNode supports which type of drives?
  •  hot swappable
  •  cold swappable
  •  warm swappable
  •  non-swappable
Q15. Which method is used to implement Spark jobs?
  •  on disk of all workers
  •  on disk of the master node
  •  in memory of the master node
  •  in memory of all workers
Q16. In a MapReduce job, where does the map() function run?
  •  on the reducer nodes of the cluster
  •  on the data nodes of the cluster (NOT SURE)
  •  on the master node of the cluster
  •  on every node of the cluster
Q17. To reference a master file for lookups during Mapping, what type of cache should be used?
  •  distributed cache
  •  local cache
  •  partitioned cache
  •  cluster cache
Q18. Skip bad records provide an option where a certain set of bad input records can be skipped when processing what type of data?
 
  •  cache inputs
  •  reducer inputs
  •  intermediate values
  •  map inputs

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