What is Hadoop Testing?
Testing of these datasets includes different devices, methods, and structures to process. Big Data identifies with Data creation, Storage, recovery, and investigation that is surprising as far as volume, assortment, and speed. By Hadoop Testing, we can recognize, examine and resolve the errors in Hadoop structure. Data which are stored in Hadoop should check that data if any faults are there should be resolve so testers can do this.
What does a Hadoop Tester do?
- Responsible for constructing positive and negative test cases in Hadoop/Pig/Hive elements to arrest all bugs.
- Report defects to the development team or manager and driving them to closure.
- Consolidate all the defects and make defect reports
Why learn Hadoop Testing?
Hadoop is being organized across the board in enterprises around the world. With each passing day, the scale and complexities of the task that Hadoop big data is expected to achieve are getting larger.
With more and more Hadoop developers and Hadoop architects deployed on Hadoop projects, there's an equal and urgent necessity of Hadoop testers.
Hadoop Testing Professionals gets a very good salary with proper certification and skills. In the US a certified Hadoop testing professional gets an average salary of about $132,000 a year – indeed.com.
Companies have high demands for Testers for their products and applications, so the career opportunities for Hadoop Testers are also big in numbers.
This big data testing training can make sure that you gain the proper skills which are able to open up opportunities in the big data testing domain as a Hadoop Tester.
What you’ll learn in Big Data Hadoop Testing Training?
- Understand the Hadoop and Hadoop ecosystems
- HDFS architecture, the flow of data, data replication, Namenode, and Datanode
- Master MapReduce concepts, mapper and Reducer functions, Concurrency, Shuffle, and Ordering
- Unit Testing of Hadoop mapper on a MapReduce application
- Deploy Pig for big data analysis and Hive for relational data analysis and test the application
- Deep understanding of Hadoop Testing and the workflow method
- Design, formulate and implement Hadoop test situations, test cases, and test scripts
- Use of big data testing tools for detecting bugs and fixing it
- Learn MR Unit framework for testing MapReduce jobs without Hadoop clusters
- Get trained for the Cloudera Hadoop Certification
Who should take this course?
- Big Data and Hadoop professionals
- Quality Assurance professionals
- Hadoop developers and testers
- Tech support personnel and system administrators
- Those aspiring for a career in Big Data and Hadoop
Hadoop Testing Course Highlights
- Introduction to Hadoop and its ecosystem, MapReduce and HDFS
- Hands-on Exercises
- Introduction to Pig & its features
- Introduction to Hive
- Hadoop Stack Integration Testing
- Roles and Responsibilities of Hadoop Testing
- Framework is known as MR Unit for Testing of MapReduce Programs
- Unit Testing
- Test Execution of Hadoop _customized
- Test plan Strategy Test Cases of Hadoop Testing
- Hadoop Testing projects
- Working on real-life industry-based projects
- Mock interview sessions, resume services and Interview questions to prepare you to attend interviews with confidence.
- Access to the instructor through email to address any questions.
- No prerequisite is required to learn Hadoop testing.
- Having a basic knowledge of big data will help.
How EnhanceLearn Training can help you
- 48 Hours of hands-on session per batch and once enrolled you can take any number of batches for 90 days
- 24x7 Expert Support and GTA (Global Teaching Assistant, SME) support available even to schedule a one on one session for doubt clearing
- Project Based learning approach with evaluation after each module
- Project Submission mandatory for Certification and thoroughly evaluated
- 3 Months Experience Certificate on successful project completion
For becoming a Big Data Hadoop Tester expert, choose our best Training and Placement Program. If you are interested in joining the EnhanceLearn team, please email at email@example.com.