Pig is great for data discovery as you don't need schema on top of data, you can tell Pig how to consume the raw data by specifying delimeters. With Hive you still need to cleanse the data a bit before you can apply some sort of schema. So for dirty data, Pig is the first tool to use and then for familiar SQL functionality you can switch to Hive. Both can consume same datasets. Hadoop is designed to be a generic data processing framework and for that it's designed so schema is applied at read stage as opposed to relational sources where schema is applied on write. Check out a few of the intro tutorials we have on Pig and Hive and you will see right away the concepts in action. its unlike anything you've worked with before.
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