Hadoop is a Java-based open source programming framework that supports the processing and storage of extremely large datasets in a distributed computing environment. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an original essayHadoop allows you to run applications on systems with thousands of commodity hardware nodes and handle thousands of terabytes of data. Its distributed file system facilitates fast data transfer rates between nodes and allows the system to continue functioning in the event of node failure. This approach reduces the risk of catastrophic system failures and unexpected data losses, even if a significant number of nodes become inoperative. As a result, Hadoop has quickly emerged as the basis for big data processing tasks, such as scientific analytics, business and sales planning, and processing huge volumes of sensor data, including from IoT sensors. Why It Matters Keep in mind: This is just a sample. Get a custom paper from our expert writers now. Get a Custom Essay Ability to store and process massive amounts of any type of data, quickly. With ever-increasing volumes and variety of data, especially from social media and the Internet of Things (IoT), this is a key consideration. IT power. Hadoop's distributed computing model processes big data quickly. The more compute nodes you use, the more processing power you have. Low cost. The open source framework is free and uses commodity hardware to store large amounts of data. Scalability. You can easily grow your system to handle more data by simply adding nodes. Little administration is required. Flexibility. Unlike traditional relational databases, there is no need to preprocess the data before storing it. You can store as much data as you want and decide how to use it later. This includes unstructured data such as text, images, and videos. How it works The way HDFS works is to have a main «NameNode» and multiple «data nodes» on a basic hardware cluster. All nodes are usually organized within the same physical rack in the data center. The data is then split into separate 'blocks' which are distributed across the various data nodes for storage. The NameNode is the "smart" node in the cluster. It knows exactly which data node contains which blocks and where the data nodes are located within the machine cluster. The NameNode also manages file access, including reads, writes, creation, deletion, and replication of data blocks across different data nodes. The NameNode operates in a "loosely coupled" manner with the data nodes. This means that cluster elements can dynamically adapt to real-time demand for server capacity by adding or subtracting nodes as the system sees fit. The data nodes constantly communicate with the NameNode to see if they need to complete a certain task. Constant communication ensures that the NameNode is always aware of the status of each data node. Because the NameNode assigns tasks to individual datanodes, if it realizes that a datanode is not functioning properly it can immediately reassign that node's task to a different node containing the same data block. Data nodes also communicate with each other so they can cooperate during normal file operations. Clearly the NameNode is critical to the entire system and should be replicated to prevent system failures. Again, data blocks are replicated across multiple data nodes and access is.