Map/Reduce job is a programming paradigm which is used to allow massive scalability across the thousands of server.

MapReduce refers to two different and distinct tasks that Hadoop performs. In the first step maps jobs which takes the set of data and converts it into another set of data and in the second step, Reduce job. It takes the output from the map as input and compresses those data tuples into the smaller set of tuples.

Map: In Hadoop, a map is a phase in HDFS query solving. A map reads data from an input location and outputs a key-value pair according to the input type.

Reducer: In Hadoop, a reducer collects the output generated by the mapper, processes it, and creates a final output of its own.

Shuffling is a process which is used to perform the sorting and transfer the map outputs to the reducer as input.

NameNode is a node, where Hadoop stores all the file location information in HDFS (Hadoop Distributed File System). We can say that NameNode is the centerpiece of an HDFS file system which is responsible for keeping the record of all the files in the file system, and tracks the file data across the cluster or multiple machines.

Heartbeat is a signal which is used between a data node and name node, and between task tracker and job tracker. If the name node or job tracker doesn't respond to the signal then it is considered that there is some issue with data node or task tracker.

There is a very unique way of indexing in Hadoop. Once the data is stored as per the block size, the HDFS will keep on storing the last part of the data which specifies the location of the next part of the data.

If a data node fails the job tracker and name node will detect the failure. After that, all tasks are re-scheduled on the failed node and then name node will replicate the user data to another node.

Hadoop streaming is a utility which allows you to create and run map/reduce job. It is a generic API that allows programs written in any languages to be used as Hadoop mapper.

A Combiner is a mini-reduce process which operates only on data generated by a Mapper. When Mapper emits the data, combiner receives it as input and sends the output to a reducer.

Following are the three configuration files in Hadoop:

• core-site.xml
• mapred-site.xml
• hdfs-site.xml