Mapreduce Development MCQ

Test your knowledge with important Mapreduce Development MCQ and their applications. These MCQs are beneficial for competitive exams too. Explore 30 + more Mapreduce Development MCQs at Bissoy

• Users can specify a different symbolic name for files and archives passed through -files and -archives option, using __________
  ক

  $

  খ

  @

  গ

  #

  ঘ

  $
• The option ___________ allows to pass comma separated list of archives as arguments.
  ক

  optionname

  খ

  -libjars

  গ

  -archives

  ঘ

  none of the mentioned
• The ________ option allows applications to add jars to the classpaths of the maps and reduces.
  ক

  optionname

  খ

  -libjars

  গ

  -archives

  ঘ

  all of the mentioned
• Key classes have to implement the __________ interface to facilitate sorting by the framework.
  ক

  Writable

  খ

  Comparable

  গ

  WritableComparable

  ঘ

  None of the mentioned
• The key and value classes have to be _________ by the Mapreduce framework.
  ক

  collected

  খ

  serializable

  গ

  compacted

  ঘ

  none of the mentioned
• Hadoop _________ is a SWIG- compatible C++ API to implement MapReduce applications.
  ক

  Streaming

  খ

  Pipes

  গ

  Orchestration

  ঘ

  All of the mentioned
• Hadoop __________ is a utility which allows users to create and run jobs with any executables.
  ক

  Streaming

  খ

  Pipes

  গ

  Orchestration

  ঘ

  All of the mentioned
• ________ job usually splits the input data-set into independent chunks which are processed by the map tasks in a completely parallel manner.
  ক

  Tasker

  খ

  MapReduce

  গ

  Tasktrack

  ঘ

  None of the mentioned
• The output of the reduce task is typically written to the FileSystem via _____________
  ক

  OutputCollector.collect

  খ

  OutputCollector.get

  গ

  OutputCollector.receive

  ঘ

  OutputCollector.put
• The framework groups Reducer inputs by key in _________ stage.
  ক

  sort

  খ

  shuffle

  গ

  reduce

  ঘ

  none of the mentioned
• The number of reduces for the job is set by the user via _________
  ক

  JobConf.setNumTasks(int)

  খ

  JobConf.setNumReduceTasks(int)

  গ

  JobConf.setNumMapTasks(int)

  ঘ

  All of the mentioned
• The right level of parallelism for maps seems to be around _________ maps per-node.
  ক

  1-10

  খ

  10-100

  গ

  100-150

  ঘ

  150-200
• Applications can use the ____________ to report progress and set application-level status messages.
  ক

  Partitioner

  খ

  OutputSplit

  গ

  Reporter

  ঘ

  All of the mentioned
• Users can control which keys (and hence records) go to which Reducer by implementing a custom?
  ক

  Partitioner

  খ

  OutputSplit

  গ

  Reporter

  ঘ

  All of the mentioned
• The Hadoop MapReduce framework spawns one map task for each __________ generated by the InputFormat for the job.
  ক

  OutputSplit

  খ

  InputSplit

  গ

  InputSplitStream

  ঘ

  All of the mentioned
• The Mapper implementation processes one line at a time via _________ method.
  ক

  map

  খ

  reduce

  গ

  mapper

  ঘ

  reducer