Question - How is Hadoop different from other parallel computing systems?
Answer -
Hadoop is a distributed file system that lets you store and handle large amounts of data on a cloud of machines, handling data redundancy.
The primary benefit of this is that since the data is stored in several nodes, it is better to process it in a distributed manner. Each node can process the data stored on it, instead of spending time moving the data over the network.
On the contrary, in the relational database computing system, you can query the data in real-time, but it is not efficient to store the data in tables, records, and columns, when the data is large.
Hadoop also provides a scheme to build a column database with Hadoop HBase for runtime queries on rows.
Listed below are the main components of Hadoop:
- HDFS: HDFS is Hadoop’s storage unit.
- MapReduce: MapReduce the Hadoop’s processing unit.
- YARN: YARN is the resource management unit of Apache Hadoop.