InfoQ Homepage Presentations The Mechanics of Testing Large Data Pipelines
The Mechanics of Testing Large Data Pipelines
Summary
Mathieu Bastian explores the mechanics of testing large, complex data workflows and tries to identify the most common challenges developers face. He looks at good practices to develop unit, integration, data and performance tests for data workflows. In terms of tools, he looks at what exists today for Hadoop, Pig and Spark with code examples.
Bio
Mathieu Bastian spent the last four years building data products at LinkedIn. He joined LinkedIn's Data Science team in late 2010 and first worked on InMaps, a system that served millions of complex graph visualizations to users. Previously, Bastian co-founded and led the development of Gephi, an award-winning open-source software to visualize and analyze large graphs.
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This content is in the AI, ML & Data Engineering topic
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