Asked by: Anahit Shamov
technology and computing programming languages

What are the main configuration parameters that user need to specify to run MapReduce job?

Last Updated: 1st May, 2020

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The main configuration parameters which users need to specify in “MapReduce” framework are:
  • Job's input locations in the distributed file system.
  • Job's output location in the distributed file system.
  • Input format of data.
  • Output format of data.
  • Class containing the map function.
  • Class containing the reduce function.

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Similarly one may ask, what are the main configuration parameters in a MapReduce program?

The main configuration parameters in “MapReduce” framework are:

  • Input location of Jobs in the distributed file system.
  • Output location of Jobs in the distributed file system.
  • The input format of data.
  • The output format of data.
  • The class which contains the map function.
  • The class which contains the reduce function.

Also Know, what are the parameters of mappers and reducers? The four parameters for mappers are:

  • LongWritable (input)
  • text (input)
  • text (intermediate output)
  • IntWritable (intermediate output)

Similarly, what are the main components of MapReduce job?

  • Main driver class which provides job configuration parameters.
  • Mapper class which must extend org. apache. hadoop. mapreduce. Mapper class and provide implementation for map () method.
  • Reducer class which should extend org. apache. hadoop. mapreduce. Reducer class.

What is partitioner and how it helps in MapReduce job process?

Partitioner in MapReduce job execution controls the partitioning of the keys of the intermediate map-outputs. With the help of hash function, key (or a subset of the key) derives the partition. Records as having the same key value go into the same partition (within each mapper).

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How do reducers communicate with each other?

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Which phase of MapReduce is optional?

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How many reducers run for a MapReduce job?

Using the command line: While running the MapReduce job, we have an option to set the number of reducers which can be specified by the controller mapred. reduce. tasks. This will set the maximum reducers to 20.

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When NameNode fails which node takes the responsibility of active node?

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What is MapReduce and how it works?

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What is the port number for Job Tracker?

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What are the two main components of Hadoop?

HDFS (storage) and MapReduce (processing) are the two core components of Apache Hadoop. The main components of HDFS are as described below: NameNode is the master of the system. It maintains the name system (directories and files) and manages the blocks which are present on the DataNodes.

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What do you mean by MapReduce?

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What is Hdfs and MapReduce?

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Chad Trapiello

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Who introduced MapReduce?

MapReduce really was invented by Julius Caesar. You've probably heard that MapReduce, the programming model for processing large data sets with a parallel and distributed algorithm on a cluster, the cornerstone of the Big Data eclosion, was invented by Google.

Jules Diez

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What are the two major components of the MapReduce layer?

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Aidi Piano

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What are the four basic parameters of a mapper?

The four basic parameters of a mapper are LongWritable, text, text and IntWritable. The first two represent input parameters and the second two represent intermediate output parameters.

Nicu Taldykin

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What is optimal size of a file for distributed cache?

In conclusion to Distributed cache, we can say that, it is a facility provided by the MapReduce. It caches files when needed by the applications. It can cache read only text files, archives, jar files etc. By default, distributed cache size is 10 GB.

Cristinel Jakub

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Can we set the number of reducers to zero in MapReduce?

Yes, we can set the Number of Reducer to zero. This means it is map only. The data is not sorted and directly stored in HDFS. If we want the output from mapper to be sorted ,we can use Identity reducer.