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The testing process is understandably the most important aspect of any software domain. The Testing Engineer role extends to different domains when the organization chooses to adapt itself to an improved technology. In this blog post, let’s discuss why a Software Testing Engineer should learn Big Data and Hadoop ecosystem technologies.
Let’s get straight to the nitty-gritty details of this topic;
The above chart is self-explanatory. It clearly shows that the growth rate of Hadoop related job are much higher than that of software testing jobs. The maximum growth rate of software testing related jobs is at approximately 1.6% but the growth rate of Hadoop based testing jobs are at a whopping 5% (approximately.)
80% of people who learn Hadoop are from a non-development background. You too can be one of them.
Limitations of current Testing practices while testing Applications to solve Big Data problems:
For mid-sized data, the data can be exposed as HBase tables and verified from input data set by applying business logic on small set of input.
For large scale data, Big data techniques provide engineers with unique skill sets that are used for testing large and complex data sets and find numerous opportunities in the field of meteorology, genomics, connectomics, complex physics simulations and biological and environmental research.
Scott Barber, a renowned tester, speaker and writer on testing related topic; specializing in the area of System Performance Testing has quoted some really powerful and impacting words about the current situation in the Testing field.
There has been numerous talks on different social medias about the possibility of Testing becoming a “Dying profession” and Scott does agree that Testing as a profession is in the middle of a dramatic transformation.
Well, that statement was dramatic enough, let take a look at the facts and see for ourselves what is going on in the Testing field.
Below is a requirement placed by a certain organization for their Hadoop Tester requirement:
When looking at the above requirement, we can see that Testing skills are largely needed and form the foundation of this job profile. Now, all that is required of a Software testing engineer to become a Big Data or a Hadoop Tester is to update himself with Big Data/Hadoop skills.
For those who are experts in Java, the transition is a cake walk as is an open-source, Java-based programming framework. The MapReduce scripts used here are written in Java. Now, it is pretty obvious that to work on Hadoop, knowledge in Java is imperative.
By saying the above, It doesn’t mean that non-Java experts have a rough journey ahead. The beauty of Hadoop is that it has an array of tools that a ‘Non-Java’ expert can use. Some of the Hadoop tools like Hive, Pig and Sqoop don’t require Java knowledge as they rely heavily on SQL.
The idea of moving from out comfort zone to a new domain like Big Data/ Hadoop might be a little overwhelming at first. But one has to realise that Testing and Hadoop are not mutually exclusive. Here is a list of skills and platforms that are used between them can be used according to http://www.itjobswatch.co.uk. One or more of these skills, can also be used in alignment with Big Data and Hadoop skills. Thus, making it is easier to make a smooth transition.
A good Testing Engineer possess sharp analytical skills, strong technical skill, great attitude, detail oriented and willingness to learn. These are the exact traits required for anyone to switch over to Hadoop. It is irrefutable that Testing is undergoing transformation but it is not going to be the end of it. But with the changing times, it is prudent to sail the high wave – Hadoop, considering all its features and flexibility.
Still not convinced you can learn Hadoop? Don’t trust anyone. Judge yourself. Click below to watch a sample class recording of a Big Data and Hadoop class conducted by Edureka.
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