What is the future of a Hadoop Developer?- Hadoop Online Training

What is the future of a Hadoop Developer?

The question is why this type of question arises when Hadoop is such a great technology. In this article, we will find the difference between Hadoop and Spark, and finally, sort out the future of a Hadoop developer. We will find though Spark is better technology, the use of Hadoop is not going to seize anytime near in the future. And finally, we will list all the details of the future of the Hadoop developer. We start with use cases for Hadoop and Spark. And then we find the answer to the question Hadoop or Spark. After proving the importance of Hadoop still post Spark era, we will discuss in detail the future scope of Hadoop. So, let’s begin our article. And if you want to learn all this, you can contact Naresh I Technologies. We offer complete Hadoop training for all. Naresh I Technologies also is the number one computer training institute in Hyderabad. And it is among the top five computer training institutes in India.

Hadoop and Spark Use Cases:

Some of the use cases for Hadoop are as below:

It's used in large dataset processing, and where the available memory shortage due to data size Is found. Also, if we have a limited budget and want to perform data analysis, we make use of Hadoop. Also, Hadoop is used when results are not expected immediately, and time is not a factor. It's used for batch processing of the jobs that exploit the disk r/w operations. Its also used for historic and archive data analysis.

Spark is on the other hand used, when we need to analyze the real-time data stream. Also, when time becomes important, Spark is preferred as it provides us results in less time through in-memory computation. Also, it performs a sequence of parallel operations through iterative algorithms. It models the data through Graph parallel processing and is best for machine learning algorithms.

So, the question arises, which to choose out of the above or there are specific conditions for each like we discussed above. And on that account, we will find the future scope of Hadoop.

So, Spark or Hadoop?

Both of these are used for big data handling. However, they are different frameworks on account of management and data processing. It does look that Spark is the hero. This is true to a large extent; however, both are not made to compete, and in fact counterparts. And in the majority of conditions, Hadoop and Spark together look better. Spark is not a replacement for Hadoop but it uses Hadoop features for the development of a fresh and better ecosystem.

If we combine both, then Spark can take advantage of the missing features like a file system. Hadoop can save a large amount of data with the help of cheap hardware and it can later do the analytics part. However, Spark bring with-it real-time processing for handling the data that is coming in. If Spark does not integrate with Hadoop the business apps will miss the historical data which is not handled by Spark.

If both work in cooperation, then Spark take advantage of the resource management and the security features of the Hadoop as well. The Spark clustering as well as the management of the data is much simpler with YARN. The spark workloads run automatically through the resources available.

This collaboration ensures better results in the analysis of the retrospective transactional data as well and more advanced analytics. It's great for IoT data processing as well. And these use cases are imaginable in one environment.

The maker of both of these technologies is meant to ensure these two platforms are compatible and provides the best results which are best for business requirements.

And hence, Spark is not going to replace Hadoop and both of them in the future will be seen working in collaboration.

Hence, Apache Hadoop is an irreplaceable framework and will exist for quite a while still. Businesses need big data badly, and Big data analytics is incomplete without Apache Hadoop. We will see that below.

We now examine the future in Big data world of Hadoop and see how good it is for big data analytics still. We will also see the job options in Hadoop, and the list of companies that are adopting Hadoop. Its used in various domains like health care, the financial sector, and various others. We will also see some of the Big data Hadoop job profiles.

Let’s start with the companies which are making use of Hadoop.

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