Operating Modes in Hadoop Explored
Hadoop, the open-source distributed computing framework, offers various modes to cater to different use cases and requirements. These modes differ in their cluster setup, daemon management, file system usage, configuration complexity, and primary use cases.
Standalone Mode is the simplest mode, running Hadoop on a single JVM without starting any Hadoop daemons. It uses the local file system rather than HDFS, requires no configuration changes, and is mainly used for learning, debugging, or running small jobs quickly. By default, Hadoop works in Standalone Mode after installation.
Pseudo-Distributed Mode simulates a distributed environment on a single physical machine. All Hadoop daemons (NameNode, DataNode, ResourceManager, NodeManager, etc.) run as separate processes on independent JVMs on the same machine. It uses a fully functional HDFS where data is stored in blocks and requires configuration changes. This mode is ideal for development and testing since it emulates a real cluster environment on one node.
Fully Distributed Mode runs Hadoop on a multi-node cluster across several machines. Master daemons run on master nodes and slave daemons run on worker nodes. HDFS stores and replicates data across these nodes for fault tolerance and scalability. This mode demands full configuration and is the production-grade environment suited for real-world, large-scale data processing. Fully Distributed Mode is used for production and real-world applications.
The following table summarises the key features of each mode:
| Feature | Standalone Mode | Pseudo-Distributed Mode | Fully Distributed Mode | |--------------------------|----------------------------|---------------------------------|-----------------------------------| | Number of Nodes | Single JVM | Single Machine (multiple JVMs) | Multiple Machines (cluster) | | HDFS Usage | Not used (local FS) | Fully functional HDFS | Fully functional HDFS | | Daemons | None | All daemons on one machine | Daemons distributed across nodes | | Configuration Required | No | Yes | Yes | | Performance | Fastest | Moderate | Scalable, depends on cluster size | | Primary Use Case | Learning, debugging small jobs | Development, testing | Production, large-scale processing |
This distinction allows users to select the appropriate mode depending on their needs—from simple experiments to full-scale, fault-tolerant, and scalable deployments. Fully Distributed Mode, which uses a cluster of multiple machines, ensures fault tolerance and high availability. Performance in Fully Distributed Mode depends on the cluster size. In Pseudo-Distributed Mode, master daemons (NameNode, ResourceManager, SecondaryNameNode) and slave daemons (DataNode, NodeManager) all run on the same system. No extra configuration is required in core-site.xml, hdfs-site.xml, or mapred-site.xml in Standalone Mode.
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