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This article is about the relationship between big data and Hadoop. The editor thinks it is very practical, so share it with you as a reference and follow the editor to have a look.

If you want to work in big data's field, there are some essential keywords in your resume, including: Hadoop, MapReduce, Distributed System, Spark and so on. At present, the price tag for an Hadoop engineer on the market is at least 115k per year.

Hadoop is a distributed system architecture for dealing with massive data. The core design of Hadoop's framework is: HDFS and MapReduce.

HDFS provides storage for massive data, while MapReduce provides computing for massive data.

As for Spark, if Hadoop is a toolbox, then Spark is just a tool, so as long as you learn how to get started with Hadoop,Spark, it is also very fast!

What practical projects can be done with Hadoop?

First of all, based on the Haoop framework, we can use the top k algorithm commonly used in the interview algorithm to screen hot topics, such as "Hot topic of Weibo Today", "Jinri Toutiao" and so on.

Thank you for reading! This is the end of the article on "what is the relationship between big data and Hadoop". I hope the above content can be of some help to you, so that you can learn more knowledge. if you think the article is good, you can share it for more people to see!

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