What are the important hardware requirements for a Hadoop cluster?
Table of Contents
- 1 What are the important hardware requirements for a Hadoop cluster?
- 2 Which hardware feature on an Hadoop DataNode is recommended for cost efficient performance?
- 3 Which hardware configuration is most beneficial for Hadoop jobs?
- 4 How do I check my Hadoop cluster memory?
- 5 What is in memory cluster computing?
- 6 Can Hadoop run on 8GB RAM?
What are the important hardware requirements for a Hadoop cluster?
Hadoop Cluster Hardware Recommendations
| Hardware | Sandbox Deployment | Basic or Standard Deployment |
|---|---|---|
| CPU speed | 2 – 2.5 GHz | 2 – 2.5 GHz |
| Logical or virtual CPU cores | 16 | 24 – 32 |
| Total system memory | 16 GB | 64 GB |
| Local disk space for yarn.nodemanager.local-dirs 1 | 256 GB | 500 GB |
Which hardware feature on an Hadoop DataNode is recommended for cost efficient performance?
cluster commodity hardware
Hadoop HDFS runs on the cluster commodity hardware which is cost effective.
What is in-memory in Hadoop?
1. In-Memory MapReduce. It’s an alternative implementation of Hadoop Job tracker and task tracker, which can accelerate job execution performance. It eliminates the overhead associated with job tracker and task trackers in a standard Hadoop architecture while providing low- latency, HPC-style distributed processing.
Which hardware configuration is most beneficial for Hadoop jobs?
What is the best hardware configuration to run Hadoop? The best configuration for executing Hadoop jobs is dual core machines or dual processors with 4GB or 8GB RAM that use ECC memory. Hadoop highly benefits from using ECC memory though it is not low – end.
How do I check my Hadoop cluster memory?
Checking HDFS Disk Usage
- Use the df command to check free space in HDFS.
- Use the du command to check space usage.
- Use the dfsadmin command to check free and used space.
How does Hadoop calculate number of clusters?
1 Answer
- Here is the simple formula to find the number of nodes in Hadoop Cluster?
- N = H / D.
- where N = Number of nodes.
- H = HDFS storage size.
- D = Disk space available per node.
- Consider you have 400 TB of the file to keep in Hadoop Cluster and the disk size is 2TB per node.
- Number of nodes required = 400/2 = 200.
What is in memory cluster computing?
In-memory computing means using a type of middleware software that allows one to store data in RAM, across a cluster of computers, and process it in parallel. Consider operational datasets typically stored in a centralized database which you can now store in “connected” RAM across multiple computers.
Can Hadoop run on 8GB RAM?
Highly recommend that you run Hadoop on machines with around 8 GB of RAM or more, if you’re using a single node virtual machine (like the Hortonworks Sandbox).