In our articles on JavaRush, we never tire of saying that Java, which will soon turn 25 years old, is now experiencing its second youth and has brilliant prospects in the near future. There are a number of reasons for this, and one of them is that Java is the main programming language in a number of trending and rapidly growing niches of the IT market. Most often, in the context of deep affection and tender feelings for Java, the Internet of Things (IoT) and big data are mentioned, as well as Business intelligence (business intelligence, BI) and Real Time Analytics (real-time analytics). We recently discussed the connection between Java and the Internet of Things and talked about how a Java developer can “tailor” himself and his skills to this niche. Now it’s time to pay attention to the second super trending area, which - that’s right - also loves Java and can’t imagine life without it. So, today we are analyzing big data: why Java, and therefore its faithful coders, is in great demand in this niche too, how exactly this language is used in projects with “big data,” what to learn in order to have the necessary skills for employment and work in this niche and what trends are relevant for big data right now, on the eve of 2020. And in between all this, here are the opinions of world-class experts about big data, after which even Homer Simpson will want to learn how to work with “big data.”
“I keep saying that in the next 10 years, girls will not be chasing athletes and stockbrokers, but guys who work with data and statistics. And I'm not kidding."
Big Data is conquering the planet
But first, a little about big data and why this niche is so promising for building a career in it. In short, big data inevitably and steadily, and most importantly very quickly, penetrates the business processes of companies around the world, and they, in turn, are forced to look for professionals to work with data (these are not only programmers, of course), luring them with high salaries and other goodies. According to Forbes, the use of big data in enterprises has grown from 17% in 2015 to 59% in 2018. Big Data is rapidly spreading to different sectors of the economy, including sales, marketing, research and development, logistics and everything. According to an IBM study, the number of jobs for professionals in this field in the United States alone will exceed 2.7 million by 2020. Promising? Still would.
Big Data and Java
And now about why Big Data and Java have so much in common. The thing is that many basic tools for big data are written in Java. Moreover, almost all of these tools are open source projects. This means that they are available to everyone and for the same reason they are actively used by the largest IT companies around the world. “To a large extent, Big Data is Java. Hadoop, and quite a large portion of the Hadoop ecosystem, is written in Java. The MapReduce interface for Hadoop is also Java. So it will be quite easy for a Java developer to move into big data by simply creating Java solutions that will run on top of Hadoop. There are also Java libraries such as Cascading that make the job easier. Java is also very useful for debugging, even if you're using something like Hive [Apache Hive is a Hadoop-based database management system],” said Marcin Mejran, data scientist and vice president of data engineering at the company Eight. “Besides Hadoop, Storm is written in Java, and Spark (i.e. the likely future of Hadoop) is written in Scala (which, in turn, runs on the JVM, and Spark has a Java interface). As you can see, Java plays a huge role in big data. These are all open source tools, which means that developers within companies can create extensions for them or add functionality. This work very often includes Java development,” the expert added. As we see, in big data, as well as in the Internet of things, machine learning and a number of other niches that continue to gain popularity, knowledge of Java will be simply irreplaceable.
“Every company now has big data plans. And all of these companies will end up in the big data business.”
And now a little more about the above-mentioned big data tools that are widely used by Java developers.
Apache Hadoop
Apache Hadoop is one of the fundamental technologies for big data, and it is written in Java. Hadoop is a free and open source set of utilities, libraries, and frameworks managed by the Apache Software Foundation. Originally designed for scalable and distributed yet reliable computing and storage of huge amounts of different information, Hadoop is naturally becoming the center of the “big data” infrastructure for many companies. Companies around the world are actively seeking Hadoop talent, and Java is a key skill required to master this technology. According to Developers Slashdot, in 2019, many large companies, including JPMorgan Chase with its record salaries for programmers, were actively looking for Hadoop specialists at the Hadoop World conference, but even there they could not find enough experts with the skills they needed (in particular, this knowledge of the programming model and framework for writing Hadoop MapReduce applications). This means that salaries in this area will rise even more. And they are already very big. In particular, Business Insider estimates the average cost of a Hadoop specialist at $103 thousand per year, while for big data specialists in general this figure is $106 thousand per year. Recruiting managers looking for Hadoop experts highlight Java as one of the most important skills for successful employment. Hadoop has been used for a long time or was implemented relatively recently by many large corporations, including IBM, Microsoft and Oracle. Currently, Amazon, eBay, Apple, Facebook, General Dynamic and other companies also have many positions for Hadoop specialists.
“Just as there is no fire without smoke, now there is no business without big data.”
Apache Spark
Apache Spark is another key big data platform that seriously competes with Hadoop. With its speed, flexibility, and developer-friendliness, Apache Spark is becoming the leading framework for large-scale SQL, batch and streaming data, and machine learning. Being a framework for distributed processing of big data, Apache Spark works on a similar principle to the Hadoop MapReduce framework and is gradually taking away the palm from it in terms of use in the field of big data. Spark can be used in many different ways and has links to Java, as well as a number of other programming languages such as Scala, Python and R. Today, Spark is widely used by banks, telecommunications companies, video game developers and even governments. Of course, IT giants such as Apple, Facebook, IBM and Microsoft love Apache Spark.
Apache Mahout
Apache Mahout is an open source Java machine learning library from Apache. Mahout is precisely a scalable machine learning tool with the ability to process data on one or more machines. Implementations of this machine learning are written in Java, some parts are built on Apache Hadoop.
Apache Storm
Apache Storm is a framework for distributed real-time streaming computing. Storm makes it easy to reliably process unlimited streams of data, doing in real time what Hadoop does for batches of data. Storm integrates with any queuing system and any database system.
Java JFreechart
Java JFreechart is an open source library developed in Java for use in Java-based applications to create a wide range of charts. The fact is that data visualization is a fairly important task for successful big data analysis. Since big data involves working with large volumes of data, it can be difficult to identify any trend and simply come to certain conclusions by looking at raw data. However, if the same data is displayed in a graph, it becomes more understandable and it is easier to find patterns and identify correlations. Java JFreechart actually helps in creating graphs and charts for big data analysis.
Deeplearning4j
Deeplearning4j is a Java library that is used to build various types of neural networks. Deeplearning4j is implemented in Java and runs in an environment that is compatible with Clojure and includes an API for the Scala language. Deeplearning4j technologies include implementations of restricted Boltzmann machine, deep belief network, deep autoencoder, stacked autoencoder with noise filtering, recursive tensor neural network, word2vec, doc2vec and GloVe.
“Big data is becoming the new raw material for business.”
Big Data on the threshold of 2020: the latest trends
2020 should be another year of rapid growth and evolution of big data, with widespread adoption of big data by companies and organizations in various fields. Therefore, we will briefly highlight the big data trends that should play an important role in the next year.
Internet of Things - big data is getting even bigger
It would seem that the Internet of Things (IoT) is a slightly different story, but it’s not. IoT continues to “trend”, gaining momentum and spreading around the world. Consequently, the number of “smart” devices installed in homes and offices, which, as they should be, transmit all sorts of data where necessary, is also growing. Therefore, the volume of “big” data will only increase. As experts note, many organizations already have a lot of data, primarily from the IoT sector, which they are not yet very ready to use, and in 2020 this avalanche will become even greater. Consequently, investments in big data projects will also increase rapidly. Well, let us remind you that IoT also loves Java very much . Well, who doesn't love him?
Digital twins
Digital twins are another interesting trend of the near future, which is directly related to both the Internet of Things and big data. And therefore, the use of Java in it will be more than enough. What is a digital twin? This is a digital image of a real object or system. A software analogue of a physical device allows you to simulate internal processes, technical characteristics and behavior of a real object under conditions of interference and the environment. The operation of a digital twin is impossible without a huge number of sensors in the real device operating in parallel. It is expected that by 2020 there will be more than 20 billion connected sensors in the world, transmitting information to billions of digital twins. In 2020, this trend should gain momentum and come to the fore.
Digital transformation will become smarter
Digital transformation has been mentioned as an important trend for several years now. But the problem is, experts say, that many companies and top managers had an extremely vague understanding of what this phrase even means. For many, digital transformation has meant finding ways to sell the data a company collects to create new sources of profit. By 2020, more and more companies are realizing that digital transformation is all about applying data correctly to every aspect of their business to create a competitive advantage. Therefore, we can expect that companies will increase the budgets of projects related to the correct and conscious use of data.
“We are slowly moving towards an era in which Big Data is the starting point, not the end.”
Results
Big Data is another truly huge area of activity with a lot of opportunities in which a Java developer can find use. Just like the Internet of Things, this field is booming and is experiencing a severe shortage of programmers, as well as other technical experts. Therefore, now is the time to stop reading such long articles and start learning Java!
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