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Nowadays, with the comprehensive popularization of computer technology, digital data has played a closely related role in people's lives. Everyone also often pays attention to the development of the technology circle. Many Java engineers are worried about how to go along the road of technology development suitable for them. Now there is a direction.

Introduction to Big Data

BIG DATA refers to a collection of data that cannot be captured, managed and processed by conventional software tools within a certain time range. It is a massive, high-growth and diversified information asset that requires a new processing model to have stronger decision-making power, insight and process optimization capabilities.

Big data is also data in essence, and it also has the following new characteristics:

Volume: The size of the data determines the value and potential information of the data under consideration;

Variety: Diversity of data types;

Velocity: the speed at which data is acquired;

Variability: hinders the process of processing and effectively managing data.

Veracity: Quality of data;

Complexity: large amount of data, multiple sources;

Value: Rational use of big data to create high value at low cost.

Big data is the future direction of development, is challenging our analytical capabilities and cognitive way of the world, so we keep pace with the times, meet the changes, and continue to grow! Big Data Learning Group: 868847735 Discuss Progressive Learning Together

And the corresponding tool appeared:

Hadoop ecosystem

· HDFS ====> Solving storage problems

· MapReduce ====> Solving Computational Problems

· Yarn ====> Resource Coordinator

Zookeeper ====> Distributed Application Coordination Services

· Flume ====> Log Collection System

Hive ====> Hadoop-based Warehouse Tools

· HBase ===> Distributed, column-oriented open source database

· Sqoop ====> Data Transfer Tool

Scala ====> Features of multi-paradigm programming languages, object-oriented and functional programming

· Spark ====> Batch offline/real-time computing engine commonly used by enterprises

· Flink ====> The hottest stream processing framework at present, which supports both stream processing and batch processing

Elasticsearch ====> Big Data Distributed Elastic Search Engine

Python: This is used when writing scripts.

·Offline/real-time projects

These are the tools commonly used in the big data ecosystem and the corresponding problems.

Big Data Jobs

·Big Data Development Engineer

·Big Data Cleaning Development Engineer

·Big Data Warehouse Development Engineer

·Big Data Operations Development Engineer

·Big Data Platform Development Engineer

Big data is the future.

Of course, Java development is also a good choice, but in terms of the current development of the industry, big data is a big trend, plus Hadoop is developed in Java, and the salary of Hadoop engineers is generally 3-4K higher than that of Java development alone, so there are many Java developers who are switching to big data. And Java engineers have a good foundation for big data.

From the above, we can understand that in the development of the industry, the development trend of technology is very important. Through the trend, we can get a new round of tickets and embark on higher development, so that we can grow well enough.

Big data development space and everyone's most concerned about income issues

Most Java engineers work for 3-5 years, and the salary is at most 1- 25,000 yuan. Then 25,000 is already the limit for Java technicians, and of course Java architects or developers who do low-level salaries are higher than technicians. But 20,000-plus is just so-so for technicians working in the Hadoop industry. Taking Hadoop development engineers as an example, the monthly salary of Hadoop entry has reached more than 8K, the monthly salary of 1 year of work can reach more than 1.2W, and the annual salary of hadoop talents with 2-3 years of work experience can reach 300,000 - 500,000. So big data has a lot of room for development. I think this is a very clever idea, horizontal development, broaden their knowledge breadth, the future may be able to grasp more opportunities.

Java development, what else can you learn besides Java?

Big data development may be a good way to go.

So what basic skills do you need to transform deep into big data?

Java: Programming is the foundation of big data development, Java programming is a necessary skill!

Python is a computer programming language supported in big data processing frameworks.

Scala is a multi-paradigm programming language, similar to java.

Go: (also known as Golang) syntax is close to C, but the declarations for variables are different.

R: A language and operating environment for statistical analysis and plotting.

So whether you're a beginner or an experienced programmer, you should focus on what language you're talking about, not what language you're talking about, because that's the only way to get to grips with it, pick up any language you can basically use, and write high-quality code.

At the technical level, they are all tools of big data. In fact, as long as there is some basic programmer transformation big data, there are natural advanced advantages, even if you have not learned any programming language zero foundation, but also can learn.

What is the big data market demand?

According to the Big Data Talent Report, there are only 460,000 big data talents in China at present. In the field of artificial intelligence alone, India has about 150,000 employees, the United States has 850,000, and China has only 50,000. With the continuous development of science and technology, in just 3-5 years, the gap of big data talents in China will increase to 1.5 million.

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