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What Exactly Happens When Data Is Written to Hadoop Distributed File System?
Learn the mechanics of the HDFS write process for your Big Data certification. Understand why data is distributed and replicated across multiple DataNodes rather than being stored locally on the client or in a relational database.
Question
What happens when data is written to HDFS?
A. Data is distributed, not kept only on the client.
B. It is directly loaded into a relational database
C. It is stored without replication to save space
D. It is stored only on the client computer
Answer
A. Data is distributed, not kept only on the client.
Explanation
When data is written to the Hadoop Distributed File System (HDFS), the client contacts the NameNode to determine where the data should go, and the file is then split into blocks and distributed across multiple DataNodes in the cluster. This distributed architecture is the foundation of HDFS’s reliability and scalability. The data is deliberately not stored just on the local client machine; instead, it is written to the cluster and automatically replicated (typically three times by default) across different nodes to ensure fault tolerance and high availability. It is also not loaded into a relational database, as HDFS is a file system designed for raw data storage, regardless of its structure.