Big Data analysis in recent years is very hot, even so, many organizations found that the existing data mining and analysis techniques still can not do big data processing tasks. For this question, a possible solution is to build a Hadoop cluster, but it is not suitable for all situations. Let's look at the advantages and disadvantages of using Hadoop cluster.
What Hadoop clusters are?
Hadoop cluster is a specific type of cluster specifically for storing and analyzing vast amounts of unstructured data and design. Essentially, it is a computing cluster, i.e. data analysis jobs assigned to a plurality of cluster nodes, so that parallel processing of data.
Hadoop cluster to build advantage
The benefit of using Hadoop cluster biggest is that it is ideal for large data analysis. Big Data is usually widespread and unstructured. And Hadoop very suitable because such data, the principle is that Hadoop split the data into pieces, and each "slice" is assigned to a particular node cluster analysis. Data need not be evenly distributed, because each data piece is separately treated in a separate cluster nodes.
Hadoop cluster additional advantage scalability. And any other type of data, like, a big data analytics is increasing important question facing is the amount of data. And the biggest advantage is that big data can be analyzed and processed in real-time or near real time. The parallel processing capabilities of Hadoop clusters can increase the speed of analysis, but with the increase in the amount of data to be analyzed, the processing power of the cluster may be affected. But the good news is, you can effectively expand the cluster by adding additional cluster nodes.
A third benefit is that the cost of Hadoop clusters. This may sound strange, after all, analysis of large data is an enterprise-class IT activities, has been enterprise-class IT applications has never been cheap. However, it turns out, Hadoop cluster is indeed a cost-effective solution.
Hadoop cluster cheaper for two main reasons. It required software is open source, so that you can reduce costs. In fact, you can freely download Apache Hadoop distribution. At the same time, Hadoop cluster control costs by supporting commodity hardware. Without having to purchase a server-class hardware, you can build a powerful Hadoop cluster.
Another advantage is that fault tolerance Hadoop cluster. When a data piece is sent to a node for analysis, there will be a copy of the data on the other nodes in the cluster. In this manner, even when a node failure occurs, additional copies of the data node is still present elsewhere within the cluster, so that data can still be analyzed and processed.
Shortcoming Hadoop cluster
Although Hadoop clusters with more than numerous advantages and benefits, but it is not applicable to all enterprises data analysis solutions. For example, the amount of data a company is relatively small, even if much-needed analysis of the data may not benefit from a Hadoop cluster.
Use Hadoop cluster further disadvantage is that a solution is the basis cluster "separable" and parallel processing may be performed on the individual nodes in the data above. If the analysis do not suited to parallel processing environment, then Hadoop cluster is not an appropriate tool to accomplish this task.
Shortcoming may use Hadoop cluster is the most significant building cluster, operation and maintenance and support is a steep curve. Unless you happen to have Hadoop experts in the IT department, or learn how to build a cluster and execute the required data analysis tasks need to spend some time.
That being the case, should we build a Hadoop cluster? The answer depends on your data analysis requirements are consistent with the Hadoop cluster function. If you are not sure whether the company benefited from Hadoop cluster, before submitting to build large clusters, you can download and install Apache Hadoop to see how the extra hardware.
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