How does Mapper work in Hadoop?

Mapper is a function which process the input data. The mapper processes the data and creates several small chunks of data. The input to the mapper function is in the form of (key, value) pairs, even though the input to a MapReduce program is a file or directory (which is stored in the HDFS).Click to see full answer. Subsequently, one may also ask, what does Mapper do in Hadoop?Mapper is the first code which is responsible to migrate/ manipulate the HDFS block stored data into key and value pair. Hadoop assign one map program to individually one blocks i.e. if my data is on 20 blocks then 20 map program will run parallel and the mapper output will getting store on local disk.Similarly, how MapReduce works on HDFS? MapReduce Overview. Apache Hadoop MapReduce is a framework for processing large data sets in parallel across a Hadoop cluster. Data analysis uses a two step map and reduce process. During the map phase, the input data is divided into input splits for analysis by map tasks running in parallel across the Hadoop cluster. Regarding this, how does mapper and reducer works in Hadoop? The output of a Mapper or map job (key-value pairs) is input to the Reducer. The reducer receives the key-value pair from multiple map jobs. Then, the reducer aggregates those intermediate data tuples (intermediate key-value pair) into a smaller set of tuples or key-value pairs which is the final output.What is a mapper?A mapper can describe a data mapper as well as a person who creates geographic maps. Duties of a geographic mapper or mapping technician include gathering and processing geographical data to create a map of an area.