What do you call the pieces into which HDFS splits large files?

In the Hadoop Distributed File System (HDFS), large files are divided into smaller units called blocks. This segmentation allows for efficient storage and retrieval of data across multiple nodes in a Hadoop cluster. Each block is typically 128 MB or 256 MB in size, which enhances parallel processing since different blocks can be processed simultaneously on different nodes.

The use of blocks in HDFS supports the system's scalability and fault tolerance. If one node fails, the blocks stored on that node can still be accessed from other nodes in the cluster where replicas of those blocks are maintained. This design is crucial for handling large datasets effectively and ensures high availability of data.

The other terms, such as fragments, nodes, and files, do not accurately describe the specific functionality or structure used in HDFS for dividing large files. Fragments are not a standard term within HDFS for this purpose, nodes refer to the individual machines in the cluster, and files are whole data entities rather than the smaller components that HDFS creates from them.