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Recently, I have been in contact with the content about hadoop, from the blank when I first came into contact, to be able to explain some issues clearly. I am afraid that only those who have passed through it will realize what they have experienced. A few days ago, I saw someone ask "what is the basis for learning hadoop?". It seems that this question has not been carefully thought about. It may be because there is a great god around me to study hadoop, so I have not thought about such a simple question.

The hadoop version we are currently using is not the original version, we are using a domestic commercial release called DKhadoop. Big fast search launched an original ecological development of the Hadoop integrated ecological environment. From the effect of use, DKhadoop can be fully compatible with the open source environment. Be prepared to take some time later and try to write about what basics you need to master to learn hadoop from the DKhadoop starting point.

[DKhadoop basic Technology Architecture Diagram]

On the question of what basics you need to learn hadoop, I think it's still a good article to see an introduction to the sharing of native hadoop. It is also shared here for your reference.

With regard to the basic knowledge needed to learn hadoop, we should first understand hadoop as a whole, including what hadoop is, what problems can help us solve, and the usage scenarios of hadoop. After you have an overall understanding, you can begin to learn hadoop systematically. Of course, if you can combine some practical things to learn will be more helpful to understand hadoop.

What are the basics needed to learn hadoop:

Linux:

① needs to be proficient in operating linux commands and network configuration.

② is familiar with user and rights management operations.

③ needs to be familiar with software packages and system command management.

④ also needs to learn shell programming.

Java:

⑤ needs some basic knowledge of javase.

It would be better for ⑥ to have knowledge of java web and various frameworks.

Virtual machines:

⑦ needs to master virtual machine

⑧ requires linux operating system to be installed

⑨ needs to configure virtual machine network

In addition to the above aspects, we also need to understand the stand-alone mode, pseudo-distributed mode and distributed mode of hadoop. Understand MapReduce distributed computing framework, Yarn cluster resource management and scheduling platform, hdfs distributed file system, hive data warehouse, HBase real-time distributed database, Flume log collection tool, sqoop database ETL tool, zookeeper distributed collaboration service, Mahout data mining library, etc.

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