Cloudera Training for Apache Hive and Pig

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Course Summary

Hive and Pig are higher-level abstractions on top of MapReduce that allow those without Java programming knowledge to manage and manipulate data in a Hadoop cluster.

Cloudera's two-day course on Apache Hive and Pig is designed for people with a basic understanding of how Hadoop works and who want to use these languages for analysis of their data.

Download the full agenda for Cloudera's Training for Apache Hive and Pig.

[top] Duration

2 days.

[top] You Will Learn

  • How Hive augments MapReduce
  • How to create and manipulate tables using Hive
  • Hive's basic and advanced data types
  • Partitioning and bucketing data with Hive
  • Advanced features of Hive
  • How to load and manipulate data using Pig
  • Features of the PigLatin programming language
  • Solving real-world problems with Pig

[top] Prerequisites

This course is suitable for developers, data analysts and business analysts. Experience with SQL and scripting languages is recommended, but is not required. No pre­‐existing knowledge of Hadoop is required.

[top] Outline

  • Introduction
  • Introduction to Hadoop and Hive
  • Getting Data into Hive
  • Manipulating Data with Hive
  • Partitioning and Bucketing Data
  • Advanced Hive Features
  • Hive Best Practices
  • Introduction to Pig
  • Pig's Architecture
  • Reading and Writing Data with Pig
  • Pig Latin Basics
  • Advanced Pig Latin
  • Debugging Pig Scripts
  • Pig Best Practices
  • Bringing it All Together
  • Appendix: Hive and HBase

Training Schedule

United States May 2013 Jun 2013 Jul 2013 Aug 2013
Chicago, IL Jun 6 - Jun 7
Phoenix, AZ Jun 13 - Jun 14
Sacramento, CA Jun 13 - Jun 14
San Francisco Bay Area, CA Jun 13 - Jun 14
Jun 3 - Jun 4
Online May 2013 Jun 2013 Jul 2013 Aug 2013
Virtual Classroom Jun 13 - Jun 14
Jun 27 - Jun 28
International May 2013 Jun 2013 Jul 2013 Aug 2013
Amsterdam, Netherlands May 28 - May 29
     
Madrid, Spain   Jun 26 - Jun 27
   
Shanghai, China   Jun 28 - Jun 29
   
Warsaw, Poland     Jul 10 - Jul 11