Shulou(Shulou.com)06/03 Report--

Big data, as one of the most popular events at the moment, is actually not a very new thing. If big data had been discussed three or five years ago, it might have given people a very fresh feeling. Big data, as the most important strategic resource at present, has been paid more and more attention by the state and enterprises. We can see it from big data's rise to the national strategic level.

Now the knowledge sharing about big data can be said to be overwhelming. As a beginner, the information you want to query can basically be queried through the network. In fact, my understanding of big data is not particularly rich, after all, the time of study is not very long. Just take the DKhadoop that I am familiar with as an example to share some little knowledge to you, which can be of some help to beginners.

The basic framework of big data platform is a must for many beginners to master. Big data is so abstract that sometimes he inevitably feels a lot of difficulties when writing and sharing. Or through a specific case to write will be easier to understand. With regard to the basic framework of big data platform, I will take the DKhadoop that I am familiar with as an example.

Before that, let's make a simple explanation to DKhadoop: DKhadoop Express big data platform, an one-stop search engine-level big data general computing platform developed by Daxue search to open the channel between big data ecosystem and traditional non-big data company (written so professionally, I must have transported it from the express brochure). For traditional enterprises with a large amount of data to deal with, big data processing platform such as DKhadoop can easily cross the big data technology gap and achieve the search engine-level big data platform performance. Since there are such great advantages, what is the basic framework of the big data platform?

Let's start with a picture: this is a technical architecture diagram of the DKH standard platform.

Summary of the design scheme of the basic framework of DKhadoop big data platform:

1. If you are familiar with native hadoop, you will find that dkhadoop integrates the entire hadoop ecosystem. Of course, it is not simply integrated, but deeply optimized and rewritten into a complete, higher-performance big data computing platform. This is very different from other domestic releases of the big data platform, DKH is to do the original ecological development, other domestic distributions are only simple secondary development.

2. DKhadoop simplifies the complex configuration of big data cluster to three kinds of nodes (master node, management node and computing node) through middleware technology, which greatly simplifies the management, operation and maintenance of the cluster and enhances the high availability, high maintainability and high stability of the cluster. (data middleware is the core of big fast DKH data exchange layer)

3. DKH is developed on the basis of the original ecology, and maintains all the advantages of the open source system, and is 100% compatible with the open source system. In this way, big data applications developed on the open source platform can run efficiently on DKH without any changes.

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