With the practice of big data technology in full swing in the corporate world, companies are becoming more and more urgent to form big data teams, and the demand for high-end talents related to big data is also becoming more and more urgent. But data engineers cannot be forged in a short time. Before learning big data, you still need to have a certain foundation!
1. Understand the theory of big data
To learn big data, you should at least know what big data is. In what fields is data generally used? Only with a general understanding of big data can you know whether you are interested in big data. If you start learning without knowing anything about big data, you may learn that you don't actually like it, which is a waste of time and energy. , and probably a waste of money. So if you want to learn big data, you need to have a general understanding of big data first.
2, java
90% of big data frameworks are written in Java. Such as:
●MongoDB--the most popular, cross-platform, document-oriented database.
● Hadoop - an open source software framework written in Java for distributed storage and distributed processing of very large data sets.
● Spark - the most active project in the Apache Software Foundation, is an open source cluster computing framework.
Hbase - open source, non-relational, distributed database, modeled after Google's BigTable, written in Java, and runs on HDFS.
Need to understand Java design and programming ideas; Java object-oriented; Java advanced; Web front-end development; HTML basics; CSS3; JS script programming; JavaEE program development; JavaWeb back-end development.
3. MySQL (must be mastered)
4. Linux
The big data framework is installed and operated on Linux System
５, Hadoop, Scala, HBase, Hive, Spark
In the learning process, invest time and energy and drive learning with interest. Practical coding is a must. What you look at is other people's code, and what you write is your own.
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