Every one of us can easily initiate Hadoop admin because the Linux system administration is simple and easy. Because the system admins have to initiate administration skills for complex apps. We have many common and simple steps for Hadoop administration. However, many of the mistakes will come from the thinking of how Hadoop works. Now I will show some common problems that we can find. Hadoop certification will give complete knowledge on Hadoop admin error questions. Read More Info On Hadoop Online Training
Single point Failure
We all know that Hadoop is a traditional distributed system. However, as of now, you move and it is difficult to keep it in that way. For instance, a common misunderstanding of Hadoop is that because it is the only source of file system like metadata. The name node to show the single point failure. This is the single case if you do not configure the name node for storing the multiple places and metadata. It is concerned on NFS store on the network and other single points of failure introduced by setups contain Hadoop home and nfs, Hbase zookeeper.
Measures to focus on small Problems
When a single node experiences an issue, with one Hadoop Process. It is concerned to take big measures, like terminating extra process on the other type of nodes. By taking the nodes offline until the cluster is terminated. If you go through an issue with Information node or a group of information nodes. It is simply that to focus data has lost. Try to restore your file system from a name node of the snapshot. In Hadoop online training you will get complete cloud access, by that you can solve many issues.
Not considering which file contain which information
You can read every documentation that you need. However, every log file to think about and examine. Usually, every time consider Stderr/stdout when they move their jobs on a large cluster. Much of the information is logged. However, it is a tough time to know where to watch. When you experience, you will remember simple and common designs in the log files.
Ignorance in metrics
Hadoop do not provide more in the way of designing. Therefore, it is more tempting to think about which is important and which is not important. It is complex to roll some solution for capturing the Hadoop results. In the same way, monitoring and alerting the general OS is stronger and healthier. The tools like Nagios and Ganglia will offer you to monitor the total cluster in one dashboard. It became a simple task for determining what will go when something went wrong in a small cluster. No network While the Hadoop does not need a concentrated network. It mainly needs to operate as performed and designed. The information is complete to design MapReduce and HDFS. Without any requirement of a dedicated network, Hadoop has only one-way of knowing how to assign data blocks. Get More Hadoop Certification
Allocating the Resources
Everyone gets a question, how much amount of decreased slots and map slots. We assign on a single machine. If the admin put the wrong value, there are many unfortunate consequences. You may get extra swapping and long operating works. The number of slots on machine learning looks like a simple configuration. But the minimum value is just like a subject for any types of factors. That is like application design, network speed, disk capacity, power of CPU.
No knowledge of configuration management
It designs a sense to initiate a small cluster and then to measure out the time. Therefore, you can find great success and you need to grow. No central configuration management. You end with many issues that cascade your picks. For instance, in manual mode, ssh-ing and SCP-ing files around by the hand is a great set of view to manage very effectively with many machines. Soon when you get cluster you will see 5 or many numbers of nodes. It will become very critical to handle and unable to trace which files go somewhere.
It will become more and more heterogeneous and you have many different combination files for handling. With every version modifying over time and time. This will add version control and mechanism to set your management. This contains a parallel shell and another type of routines for initiating and terminating cluster process and make a move on copying the files. Get More Points on Hadoop Training