What are the various modes in which a Hadoop cluster can operate?
Hadoop clusters can operate in various modes depending on your needs and environment. Here are some common modes in which a Hadoop cluster can run:
- Standalone mode:
- Also known as local mode, it is suitable for development and testing purposes.
- All components run on a single node, with no distributed computing involved.
- Pseudo-distributed mode:
- Also known as the single node pseudo-distributed mode.
- Each Hadoop component runs on the same machine, but each component runs in a separate process.
- Simulated a realistic distributed environment, ideal for debugging and learning Hadoop.
- Fully distributed mode:
- Also known as the production pattern or true distributed pattern.
- A Hadoop cluster is made up of multiple machines, each node taking on different roles such as NameNode, DataNode, ResourceManager, NodeManager, etc.
- Data storage and computing are distributed across the entire cluster, suitable for large-scale data processing and analysis.
- High availability mode:
- Setting up master-slave backup nodes improves system availability, ensuring a quick switch to a backup node to continue working when the master node fails.
- YARN mode:
- YARN, introduced in Hadoop 2.x, is a resource manager that allows multiple application frameworks (such as MapReduce, Spark, etc) to run on a Hadoop cluster.
These are some common operating modes for Hadoop clusters. You can choose the mode that best suits your needs to deploy and manage the Hadoop cluster accordingly.
