What is Hadoop, Where and Why is it Used

If you study the topic of Big Data in detail, sooner or later you will come across the term Hadoop/”Hadup”. This word denotes a set of open-source programs or processes (that is, free for the user) that are used as a basis for building Big Data systems and subsequent work with them.

The use of big data today is required for medium and large companies that are trying to improve business processes and improve the quality of their service. The available information about customers, financial performance, operations, or transactions needs permanent storage, processing, and analysis. It is for such operations that special services and applications are used.

Hadoop is one of the most popular solutions for performing operations with Big Data. It is actively used by such giants as Google, Facebook, eBay, and many others. It is worth noting that Hadoop is great for businesses in any industry that work with data volumes larger than a terabyte. The program has many advantages, including scalability and easy optimization on a VM. Many cloud providers offer it as a cloud service.

Let’s figure out what such a tool represents, what functions it has, and which organizations should use it.

What is “Hadoop”

In simple terms, Hadoop is a special constructor that allows you to build data warehouses for the needs of a company. With its help, you can store and process large amounts of information, upload them to other tools, collect statistics and build a unified display system.

Such a tool is suitable for use with unstructured information — that is, information that has not been organized, has no structure, and is difficult to categorize. For example, messages, file documents, or photos are examples of such data.

The system will help you find the information you need in the archive and get meaningful analytics for your organization. All of this may become necessary when defining a business development strategy or developing a new product. For example, many retailers use Hadup to collect information about consumer preferences. Often, the data obtained is combined with sales data, which makes it possible to assess exactly what actions on the site lead to the purchase of a product.

The Main Advantages Include:

  • Scalability. The system is easily scalable, you can always add new nodes when the number of information increases.
  • Simple job. The data does not need to be processed before being saved. The Hadoop platform is great for processing any type of unstructured data, including text, images, and video.
  • Fault tolerance. Copies of all files are automatically backed up, so in the event of a failure, all information will be redirected to the working site.
  • Computing power. Hadup allows you to process information at high speed. The power depends on the number of computing nodes used: the more they are used, the higher the performance.
  • Data storage capability. The tool can be configured to process files from various resources, company social networks, financial reports, etc. In addition, the solution allows you to efficiently store data. The platform archives are arranged in such a way that you can get the necessary access to them at any time.

Hadoop is a collection of freely redistributable utilities, frameworks, and libraries. It is these components that help develop and distribute programs that run on clusters of hundreds of nodes. This technology is fundamental for working with Big Data.

How Hadoop came to be

The problem of storing and analyzing large amounts of data has long been ripe. Large corporations are faced with the fact that it is impossible to store all information on one physical device, so the approach of storing information in distributed systems began to actively develop.

At the beginning of the 21st century, special software is being developed that would allow storing data on smaller but parallel devices. This eliminated the need for high-volume physical devices while also increasing the efficiency of working with large information.

In 2005, the non-profit organization Apache created open-source software. We are talking about the Hadoop technology, which made it possible to “parallelize” work with Big Data. It is curious that the instrument got its name in honor of a toy elephant, which belonged to the son of one of the creators. The system was quite nontrivial for its time and therefore became in demand. There were no similar solutions that would provide work with Big Data.

The feature of “Hadup” is that the system allows you to add or change data based on the current needs of the company. This information storage and processing system can be used on commercially available equipment.

Large Internet companies often use Hadoop for convenience, as the system can change based on the goals and requirements of the organization. At the same time, any changes are often returned to the developer community, which allows them to be used for another product. That is, in fact, such a form allows for joint software development for various purposes.

Features of the architecture

big dataThe tool was originally developed in Java using the MapReduce computational paradigm. According to it, the application is divided into many elementary tasks, each of which is performed on separate nodes. Then all the received data is combined into a single result.

There are four main modules within the project:

  • HDFS. It is a distributed file system that stores data on different servers. By replicating files, the system stores even large amounts of information and distributes them block-by-block between the cluster nodes.
  • Common. It is a collection of infrastructure utilities and libraries that serve for related projects. For example, they are used to manage distributed files.
  • YARN. Separate job scheduling and cluster management system. It is a set of system programs that ensure the sharing of distributed data and their scalability, if necessary. Basically, it is the interface between hardware resources and applications.
  • MapReduce. A separate platform for programming and distributed computing. During the procedures, a large number of nodes are used, which form a separate cluster.

Today Hadoop represents an entire ecosystem for big data processing and data mining. In particular, this technology can use machine learning.

Technology functions

The solution is used to regulate the risks and security of infrastructure, in addition, it is necessary to optimize business processes, conduct financial analysis, perform marketing analysis and study unstructured information that was collected during sales.

Unsystematic information gathered from various sources is often referred to as a “data lake”. As a rule, the company does not need such information but is obliged to keep it by law. Some organizations, after completing their analysis of the data, find a use for them for future projects or tasks.

When storing information in different sources and formats, its analysis, modeling, and forecasting is difficult. In fact, a “data lake” is unnecessary for the company, as it cannot provide any practical benefit. However, with the help of Hadup technology, it is possible to distribute and classify information, and then conduct their analytics and obtain various results.

Hadoop is often used for the following purposes:

Exploring data from social networks

Typically, information from social media can help an organization better understand the needs of its audience. With the help of Hadoop, interests, income level, education level is analyzed. This approach allows you to set up targeted ads, manage brand reputation, and increase response from groups and accounts.

Analysis of the attitude towards the company

If we talk about what Hadoop is used for, then we cannot fail to mention this parameter. The technology allows you to analyze the opinions of customers that they express in social networks, blogs, reviews.

It is possible to analyze the attitude of buyers towards individual products/services and the entire brand as a whole. This helps to predict purchases, adjust the marketing promotion of a product or assess the existing reputation in the market.

Maintaining the security of the infrastructure

The solution allows you to monitor server logs and identify any security breaches. With the help of Hadup, you can identify possible risks, detect network attacks and predict possible problems.

Geodata exploration

It is not uncommon for retail and manufacturing companies (with customer consent) to collect location information. The information obtained allows us to predict user visits in the future or select products based on geolocation. With the help of the platform, it optimizes and processes such as geodata, which simplifies the whole procedure and reduces the time it takes to complete it.

Collecting information about customer behavior

The technology is often useful in collecting and processing data about the behavior and engagement of users on the site. For example, the platform helps to process information about where users went to the site from, which page they came to, how much time they spent watching the content, and which pages they most often left. The analysis of such data also allows the organization to increase the conversion of the resource and make it more convenient from the point of view of users.

What companies need Hadoop

What is HadoopLet’s list the areas of the organization’s activities in which the use of the Hadup platform is practically indispensable:

  • Retail/sale of services. The use of such a solution is important for collecting information about sales, customer behavior, warehouse balances, etc. This allows companies to select personalized offers for an individual customer, offer popular products and develop a loyalty program.
  • Private clinics. Almost 4/5 of medical data is unstructured, which is why many healthcare organizations neglect to process it. Meanwhile, the collection and analysis of information allows you to increase profits, reduce the risks of insurance fraud and assess the efficiency of the clinic.
  • Financial organizations. In this area, the platform is used to analyze financial information and risks, as well as identify possible fraudulent transactions. Hadup successfully analyzes information about customers, transactions, cash balances in ATMs, etc.
  • Transport companies. Hadoop is also actively used to analyze information about cargo transportation and delivery times. It also helps to reduce fuel costs and find the best delivery routes.

Conclusion

We hope that you have a good understanding of what Hadoop is and what this application is for. Today, the platform is most often used as a cloud service. This simplifies implementation and avoids initial capital expenditures.

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