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The Hadoop Distributed File System (HDFS) is a distributed storage system designed to handle very large datasets across clusters of commodity hardware. It is a core component of the Apache Hadoop ecosystem and is specifically built to provide high throughput access to data, fault tolerance, and scalability. HDFS follows a master–slave architecture in which a single master server manages the file system namespace and multiple slave servers store and retrieve the actual data blocks. This architecture enables organizations to store and process petabytes of structured and unstructured data efficiently, which is essential in Data Science and Big Data applications. The basic architecture of HDFS consists of one NameNode and multiple DataNodes connected over a network. The NameNode acts as the master, while the DataNodes function as workers that store data blocks. A simplified representation of the architecture is shown below: ``` +-------------------+ | NameNode | | (Metadata Server) | +-------------------+ | ----------------------------------------- | | | | +---------------+ +---------------+ +---------------+ | DataNode 1 | | DataNode 2 | | DataNode 3 | | (Block A1) | | (Block A2) | | (Block A3) | | (Block B1) | | (Block B2) | | (Block B3) | +---------------+ +---------------+ +---------------+ ``` In HDFS, files are split into large fixed-size blocks, typically 128 MB or 256 MB, although this size can be configured. When a large dataset is stored in HDFS, it is divided into these blocks and distributed across _______ ____ _______ ___ ________.
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