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This article introduces the relevant knowledge of "is Java important in the big data industry?". In the operation of actual cases, many people will encounter such a dilemma. Then let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

First, big data talents who have been robbed by the heat.

According to the industry authority, the demand for positions in Java big data or data workers in big data's industry has soared in recent years, among which the gap of Java big data engineer is also very large, and what is even more unexpected is that the position gap for analysts and managers who know how to use big data to make decisions will reach millions! From the analysis of the current situation, big data talents mainly live in first-tier cities, but big data talents are unevenly distributed, mainly concentrated in the Internet and finance, resulting in an extreme lack of big data talents in the process of transformation and upgrading of manufacturing and other industries. On the whole, the construction of digital China, the transformation and upgrading of industries, and the use of cloud by enterprises all have a huge demand for big data talents and the demand is growing rapidly, while the number and speed of talent training are difficult to meet the actual demand. as a result, the talent gap of big data continues to increase, and it is predicted that the gap of big data's core talents will reach 2.3 million by 2025.

Second, which career direction do you choose big data?

If we want to subdivide the talent positions needed by big data industry, there are many positions in the market, but generally speaking, they are divided into two categories: one is big data application category, the other is big data system category. In these two types of career choices, from the perspective of career growth path, the development prospect of big data system class will be better, and the technical content will also be higher. Of course, the demand for talents will be even higher. But in big data industry, if you choose the technically difficult one as your future career plan, you will find that you will receive more and more goods. In addition to a high salary, there are also your abilities and future relationships, which will make your development path smoother and longer-term.

Third, you must learn Java from big data.

Java is the most widely used programming language at present, and it has many features, so it is especially suitable to be used as a development language for big data applications.

Java not only absorbs the advantages of C++ language, but also abandons the concepts of multi-inheritance and pointers which are difficult to understand in C++, so Java language has two characteristics: powerful and easy to use.

The cross-platform application ability of Java is easier to use and easier to use than C # and C++. At the same time, it also has the characteristics of simplicity, object-oriented, distributed, robust, security, platform independence and portability, multi-threading, dynamic and so on.

But Java language is only a technology selection under big data's technical system, and programming languages such as Python, Scala, R, Go can also complete a lot of big data's development, analysis and application tasks.

At present, big data's positions are mainly concentrated in the development, analysis, and operation and maintenance fields, of which big data development is relatively dependent on the Java language, so if you want to work in the development post of big data, it is still necessary to learn the Java language. at present, many big data development teams are using the Java language. Java language has been recognized by a large number of development teams because of its perfect technical ecology and strong expansibility.

Most importantly, Hadoop and other big data processing techniques use Java, such as Apache's Java-based HBase and Accumulo, as well as ElasticSearchas, so one of the first conditions for learning Hadoop is to master Java programming. In other words, to learn from big data, you must have a Java foundation.

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