HDFS System
The Hadoop Distributed File System (HDFS) is the primary storage system of the Hadoop ecosystem, designed to store and manage vast amounts of data across a distributed cluster of commodity hardware. HDFS is a key component of Apache Hadoop and is responsible for providing scalable and fault-tolerant storage for big data applications. Here are the main characteristics and components of HDFS:
Characteristics of HDFS:
Distributed and Scalable: HDFS distributes data across multiple nodes in a cluster, allowing it to scale horizontally as the data volume grows. New nodes can be added to the cluster to accommodate more data.
Fault Tolerance: HDFS achieves fault tolerance through data replication. It stores multiple copies (typically three) of each data block across different nodes in the cluster. If a node or block becomes unavailable, data can still be retrieved from the replicas.
High Throughput: HDFS is optimized for high-throughput data access. It is well-suited for batch processing and data-intensive workloads.
Write-Once, Read-Many Model: HDFS is optimized for a write-once, read-many model, making it suitable for storing and processing large volumes of data generated by applications like log files and sensor data.
Block-Based Storage: HDFS divides large files into fixed-size blocks (typically 128 MB or 256 MB), which are distributed across the cluster. This block-based storage simplifies data distribution and replication.
Components of HDFS:
NameNode:
- The NameNode is the central metadata and namespace management server in HDFS. It keeps track of file and directory structures, permissions, and the mapping of data blocks to their locations.
- The NameNode is a single point of failure in HDFS. To address this, Hadoop 2.x and later versions introduced the concept of a Secondary NameNode and HDFS High Availability (HA) for redundancy.
DataNode:
- DataNodes are responsible for storing and managing the actual data blocks. They receive data writes, read requests, and replication instructions from the NameNode.
- DataNodes periodically send heartbeats and block reports to the NameNode to confirm their status and report available data blocks.
Block Reports and Heartbeats:
- DataNodes send block reports to the NameNode with information about the blocks they are storing. Heartbeats are also sent to indicate that the DataNodes are functioning correctly.
Secondary NameNode:
- The Secondary NameNode periodically checkpoints the state of the NameNode and assists in maintaining the file system’s integrity. It does not serve as a backup NameNode.
HDFS Clients:
- Applications and users interact with HDFS through HDFS clients. These clients communicate with the NameNode and DataNodes to read, write, and manage files and directories.
Rack Awareness:
- HDFS has built-in rack awareness, which helps optimize data locality and reduces network traffic. It ensures that data blocks are stored across racks for fault tolerance and efficient data retrieval.
Web User Interfaces:
- HDFS provides web-based user interfaces, such as the NameNode’s web UI and the HDFS Health Monitor, for monitoring the health and status of the HDFS cluster.
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