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Big data testing (1)
The document discusses testing challenges with big data and proposes the test pyramid approach. It provides an overview of big data concepts like Hadoop, HDFS, MapReduce and HBase. Testing big data is challenging due to long feedback cycles and data dependencies. The test pyramid advocates automating basic tests like unit tests while using techniques like sampling and test automation to counter long test cycles. It also provides a high level example of using a Hive query validator as part of the testing approach.
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Big data testing (1)
- 1. TESTING BIG DATA AdoniramMishra Benazeer Khan
- 2. Agenda ❖ What isBig Data? ❖ Hadoop Ecosystem ❖ Testing Challenges ❖ Test Pyramid
- 3. What is BigData?
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- 9. High Level Example Data Source HBaseHiveData Source Data Source I M P O R T HQL UI Reports Other applications M R M R M R
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- 15. Countering Challenges ❖ Sampling. ❖Basic testing concepts - Boundary Value testing, Equivalence class partitioning. ❖ Automation
- 16. Nightly Build Tests Hive Query Validator UnitTests UI Test Test Pyramid
- 17. Hive Query Validator HiveQuery Validator Query 1 Query 2 Query 3 Correct Correct Incorrect
- 18. Nightly tests &Smoke Tests SMOKE MODULE 3MODULE 1 MODULE 2 MODULE 4
- 20. About Us ● AdoniramMishra (adoniram@thoughtworks.com) ● Benazeer Khan (benak@thoughtworks.com) Follow us at: Facebook: https://www.facebook.com/groups/vodqa/ Twitter: https://twitter.com/vodqancr