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How to Become Hadoop-Big Data tester

September 8, 2016
big data hadoop, handoop big data, hadoop testing, Hadoop Big Data

For analysis purposes, companies often rely on data from different sources. For example, an e-commerce website gathers users’ browsing pattern and uses information from different social networking platforms to evaluate or make assumptions for the different products or services customers might be interested in. Such data generally range in terabytes & it is called as Hadoop Big Data. Companies break-down all this data gathered, in the form of data sets which are further refined and evaluated using different computing techniques.

In order to test such a system, testers have to use different tools and framework, to test data creation, storage, transformation, and data retrieval. In this article, we talk about the different qualities that are expected of a Hadoop Big Data tester. We would mention the technologies required and how a tester can learn about Hadoop Big Data testing.

Testing strategies involved

  • For a Hadoop Big Data, verification of processed data is of utmost importance. To successfully achieve this, testers basically rely on performance and functional testing. QA then processes terabytes of data set using parallel computing at a faster pace.
  • Generally, these processing occurs in batches, real-time or manually, whenever required.
  • To ensure complete testing of the application, the quality of the data to needs to be tested. Data from various sources are sampled for accuracy and consistency. So, database testing also becomes a part of the overall quality check process.

How to learn Hadoop Big Data Testing?

In one of the previous article, we have mentioned the perks of a Hadoop Big Data. It not only provides a tester a vibrant career option but ensures a great position in the software industry. Now that we are well aware of the basic practices and responsibilities of a Hadoop tester, we would list the different ways one can gain such testing knowledge.

  • Learning for Java Professionals

For Hadoop Big Data testing, one should possess basic programming knowledge. For professionals, who possess Java Programming know-how, the learning experience would be very smooth. MapReduce scripts, which are widely used in Hadoop testing, are written using Java. This would provide added advantage to testers who are already familiar with Java.

  • Learning for Non-Java Professionals

IT Professionals who are not that familiar with Java need not worry. Hadoop supports a number of different tools which can help non-Java professionals to contribute to Hadoop Big Data testing. Tools like Pig, Hive, and  Sqoop can be used for Hadoop testing, without requiring any prior Java experience. Testing can be carried out using these tools, as they rely on SQL

  • Different testing practices to be aware of

While most testing disciplines are prominently data driven, big data testing is mostly driven by scenarios. So to be a good at Hadoop testing, testers must be able to come up with apt test scenarios for large and complex data sets.

  • Online courses and certifications

For a profile in Hadoop Big Data testing, having profound testing knowledge is the basic necessity. IT professionals who already have testing experience can opt for one or the other online courses or certification to update their Hadoop Big Data skill. There are a lot of online courses provided by technical tutorial websites like, HelpingTesters.com which can help cover the basics of Big Data.

Challenges Faced by Big Data Testers

Even when a tester has gained ample knowledge and experience over Hadoop, one can face a few hurdles. All these challenges in Big Data testing creep in due to the sheer enormity of the data sets under test. Some of the notable ones are:

  • Automation

Using scripts to automate test cases is quite different for Big Data applications. It requires a lot of technical expertise to automate generic Big Data test cases as a lot of unexpected data inputs needs to be processed and errors need to be averted. It even requires special test environments due to big data sets.

  • Handling real-time data

As earlier mentioned, high-velocity real-time data is one of the primary characteristics of Big Data. As testing is performed in virtual environments, data processing and analyzing might not keep up with the constant influx of data. Such machine latency can create timing problems in big data test results.


  • Good analytical skill, sturdy testing background, basic programming and Big Data knowledge is enough to provide testers a head start in Big Data testing.
  • For Hadoop Big Data testing the application needs to be thoroughly tested from functional and performance standpoint. Also, database entries need to be verified to ensure data consistency.
  • Hadoop testing is can be learned by professionals from Java or non-Java background, who has hands on experience in Linux system.
  • Hadoop Big Data tools like Pig, Hive, and MapReduce scripts are some of the basic tools used in Hadoop testing and can be learned easily from different online tutorials and similar courses.

About the author

arindam bandyopadhyay author

Arindam Bandyopadhyay is an automation tester with over 5 years of experience in software testing. While during the day he juggles between Eclipse and spreadsheets, at night he lets his fingers do the talking as he writes about anything and everything his paradoxical mind desires.

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