The app development profession has undergone a radical shift in the last five years. One of the biggest changes facing app developers is the profound influence of big data. Big data advances have helped accelerate market growth, which is why the demand for app development services are expected to be worth $407 billion by 2026. Experienced developers understand the importance of Hadoop.
App developers must understand the role of big data and Hadoop will play in the future of their profession. They must be proficient with it and use sensible development practices to incorporate it into their development processes.
Hadoop is one of the most data-intensive open source projects that is used by data scientists all over the world. Hadoop is the open-source software framework that stores massive amounts of data. This platform has enormous processing power, which allows data scientists to handle numerous tasks concurrently. App developers have started relying on it more heavily in recent years.
What is Hadoop?
Hadoop originated from Nutch, an open-source search engine that was created between the 1990s and the 2000s. Nutch was created by Doug Cutting and Mike Cafarella. It is a contemporary Google search engine.
In 2006, Cutting joined Yahoo and became a primary contributor to the Nutch project, which was divided into two parts. One part remained a search engine, while the other, the computing and distributed processing part, became the platform we now recognize as Hadoop. Today, Hadoop is managed and maintained by a global community of software developers, through the Apache Software Foundation (ASF).
Why Should App developers Be Interested in Hadoop?
Application developers are always looking for new technology to streamline their processes and bolster efficiency. They have discovered that Hadoop has a lot to offer. Its great capacity to store and instantly process huge amounts of data is one of its greatest advantages.
Hadoop is incredibly fast at processing data. This is due to its immense computing power and macro data processing features, which make it invaluable for handline big data. In other words, the more computation nodes you use, the more processing power the Hadoop platform has.
There is no need to pre-process the data before storing it. It is totally flexible and can handle text, images, videos and much more. You can set up generic data classes before determining the exact type of data that you would like to handle and decide how to use them in the future.
Since Hadoop is open-source, it is free to use the structural part of Hadoop. Fortunately, due to the growing scalability of commercial hardware, it can store large amounts of data. In addition, Hadoop has intelligence against hardware failures. In the event that a node fails, jobs are automatically redirected to others. Multiple copies of all data are automatically created and distributed processing is prevented from failing.
How can Hadoop be so useful for app developers? In order to answer this question, we must understand the limitations of big data with previous data management technology.
Big data has created many opportunities for app developers. They are using big data for many different purposes. One of the biggest advantages of big data is that it expedites the coding process, so applications can be developed far more quickly. Big data has also improved the effectiveness of the market research process, which makes it easier for app developers to identify profitable opportunities.
Big data can easily be scaled and stored without issue. Unfortunately, extracting and processing big data is complicated without the right interface. Geneva Lake of MapR Technologies Inc. discussed the limitations of traditional database management systems.
This illustrates why Hadoop is so versatile. Here are some reasons that app developers are investing in Hadoop:
Node replication minimizes failure rates
Hadoop creates a copy of data whenever it is sent to a node. This means that multiple nodes have access to the same data copy. In the event of a failure, there will be another copy of the data to use instead. This reduces the failure rate of apps using Hadoop.
Improved efficiency with mapping
Hadoop also has a unique data mapping feature. When data is sent to a node, the architecture has a precise location of every piece of information. This makes it much easier for it to extract that data for future purposes.
Ability to handle heterogenous data sets
Traditional database management systems had to create separate files for every type of data they intended to process. Databases couldn’t easily communicate with each other or merge different types of data. This is no longer an issue with Hadoop. This infrastructure can handle both structured and unstructured data sets, which means that it can combine data from many different sources.
All of these benefits have proven themselves to be invaluable to app developers. They will utilize Hadoop to create more robust apps that satisfy the expectations of their users without exceeding their budgets.
