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

Recently, I began to prepare systematically to put my knowledge of big data theory into practice and applied for a training class. In order to urge their own practice of learning, will learn some of the contents of the practice process to do a summary. On the one hand, comb their theoretical knowledge, on the other hand, strengthen the effective link between theory and practice.

virtual machine

This can be said to be the first step towards the practice of big data, first of all to install a virtual machine on your PC. I am using VMware 12, the virtual machine is installed, this step is still relatively easy. However, it is stuck in setting the IP and gateway of the relevant virtual machine. This piece is estimated to have to be further studied today to get a better answer.

Virtual machine installation, loading, and settings are the foundation of big data, and this part is completely new to itself. Because big data analysis is basically more analysis on the server side, it is bound to implement remote and proximal links on the virtual machine in the later stage. An understanding of virtual machines and basic Python programming should also have a general understanding.

Two days ago, I carefully watched the basic video of big data, but I still feel that I haven't fully mastered it. These two days and more practice a few times, see if you can run up. After all, it is only after these basic things are installed that the relevant components will understand the overall business scenario better. The solution consists mainly of the following steps:

1. Reinstall a VMware client and open the virtual machine that has been loaded on it.

2. Learn the IP settings of the relevant virtual machine according to the video. Make sure the network works.

3. CRT software on the host side can remotely monitor relevant virtual machines to ensure that relevant commands can be loaded.

4, load mapreduce, hadoop components

Deadline: This week.

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