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Pig Tutorial: Process Big Data
Transform unstructured data into structured, predictable, and useful information that is ready for reporting and analysis, using Pig
Pig is aptly named. It will devour any data that you feed it and bring home the bacon!
Let's parse that
Omnivorous: Pig works with unstructured data. Many of Pig's operations are very similar to SQL. But it can perform operations on data which do not have fixed schema. Pig is awesome at wrangling data into a form which is both clean and storable in a data warehouse. This structured data can then be readily utilized for tasks such as reporting and analysis.
Brings home the bacon: With Pig, you can transform data in such a way that makes it organized, predictable and handy, ready for consumption.
Pig Basics: Operating modes, running a Pig script, the Grunt shell, loading data and creating your first relation, scalar data types, complex data types such as the tuple, Bag and Map, partial schema specification for relations, and displaying and storing relations (the dump and store commands)
By the end of this Pig tutorial, you will:
- Extract information, transform and store unstructured data in a usable form
- Munge data by writing intermediate-level Pig scripts
- Work on large data sets by optimizing Pig operations
Prerequisites and Target Audience
The prerequisites for this Pig course are:
- You should know the basics of SQL and working with data
- You should know the basics of the Hadoop eco-system and MapReduce tasks