What is the difference between HDFS block size and InputSplit?

Block – By default, the HDFS block size is 128MB which you can change as per your requirement. Hadoop framework break files into 128 MB blocks and then stores into the Hadoop file system. InputSplit – InputSplit size by default is approximately equal to block size. It is user defined.

What is the purpose of RecordReader in Hadoop?

RecordReader , typically, converts the byte-oriented view of the input, provided by the InputSplit , and presents a record-oriented view for the Mapper and Reducer tasks for processing. It thus assumes the responsibility of processing record boundaries and presenting the tasks with keys and values.

What is shuffle and sort in MapReduce?

What is MapReduce Shuffling and Sorting? Shuffling is the process by which it transfers mappers intermediate output to the reducer. Reducer gets 1 or more keys and associated values on the basis of reducers. The intermediated key – value generated by mapper is sorted automatically by key.

What is the difference between yarn and Mr v1?

2 Answers. MRv1 uses the JobTracker to create and assign tasks to data nodes, which can become a resource bottleneck when the cluster scales out far enough (usually around 4,000 nodes). MRv2 (aka YARN, “Yet Another Resource Negotiator”) has a Resource Manager for each cluster, and each data node runs a Node Manager.

What is combiner and partitioner in MapReduce?

The difference between a partitioner and a combiner is that the partitioner divides the data according to the number of reducers so that all the data in a single partition gets executed by a single reducer. However, the combiner functions similar to the reducer and processes the data in each partition.

Why InputSplits and record reader are used?

In MapReduce, RecordReader load data from its source. Thus, it converts the data into key-value pairs suitable for reading by the mapper. RecordReader communicates with the inputsplit until it does not read the complete file. By, default; it uses TextInputFormat for converting data into key-value pairs.

What is shuffle and sort stage?

Shuffle phase in Hadoop transfers the map output from Mapper to a Reducer in MapReduce. Sort phase in MapReduce covers the merging and sorting of map outputs. Data from the mapper are grouped by the key, split among reducers and sorted by the key. Every reducer obtains all values associated with the same key.

What is a mapper and reducer in Hadoop?

Hadoop Mapper is a function or task which is used to process all input records from a file and generate the output which works as input for Reducer. It produces the output by returning new key-value pairs. The mapper also generates some small blocks of data while processing the input records as a key-value pair.

What is partitioner and combiner MapReduce?