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Pritham, Hadoop can definitely handle structured as well as unstructured data of various forms. This makes it easy for users to collect, process and conduct data analysis rather than using relational databases for the same.

Hi Pritham. The most commonly used Hadoop component is HDFS. Hadoop Distributed File System, commonly known as HDFS is the core component of Hadoop Ecosystem. This component makes it possible to store structured, unstructured and semi-structured types of large data sets. HDFS also creates a level of abstraction over the resources, from where one can view the whole HDFS as a single unit. HDFS helps us in storing data across various nodes and maintain the log file of the stored data.

Nithin, not just HDFS, but its core components also plays a vital role. HDFS has two core components. NameNode DataNode (i) NameNode: This is the main node and it doesn’t store the actual data. It contains metadata, something like say, as a table of contents. Hence this type of node requires less storage space and high computational resources. (ii) DataNode: All the data is stored on this node.

Nithin & Morgan not just HDFS component but also MapReduce plays a vital. This component runtime infrastructure coordinates the tasks & also re-run any that fail or appear to hang. This model computes a job and decomposes it into smaller tasks. These are then distributed to parallelize and balance the load.

Thank you for the brief and accurate explanations.