From 0 to 1: Hive for Processing Big Data

End-to-End Hive : HQL, Partitioning, Bucketing, UDFs, Windowing, Optimization, Map Joins, Indexes
4.45 (977 reviews)
Udemy
platform
English
language
Data Science
category
instructor
From 0 to 1: Hive for Processing Big Data
8 216
students
15.5 hours
content
Jan 2018
last update
$29.99
regular price

Why take this course?

🌟 From 0 to 1: Hive for Processing Big Data 🌟


Prerequisites:

  • Hive and SQL Knowledge: Comfortable with SQL fundamentals is a must. This course includes an SQL primer at the end for those who are not familiar with it. Java knowledge is recommended for understanding and implementing custom functions (UDFs).

Expert Instructors:

  • Taught by a team of 4 experts, including:
    • 2 Stanford-educated ex-Googlers with a wealth of practical experience.
    • 2 ex-Flipkart Lead Analysts who have honed their skills in large-scale data environments.

Course Overview:

  • Hive as a Familiar Interface to Big Data: Think of Hive as a new friend with an old face - it's the SQL you know, now supercharged for distributed computing and Hadoop. This course will bridge the gap between traditional SQL and the capabilities of Hive.

End-to-End Learning Experience:

  • For Everyone: Whether you're an analyst looking to process data or an engineer aiming to build custom functionality or optimize performance, this course covers it all.
  • SQL Primer Included: No prior SQL knowledge? No problem! The course includes a comprehensive primer on SQL basics.

Hands-On and Practical:

  • Real-World Scenarios: Learn with real-life examples, working queries, and code. Our practical approach ensures you can apply what you learn directly to your work.

Detailed Curriculum:

Analytical Processing:

  • Joins
  • Subqueries
  • Views
  • Table Generating Functions (TGF)
  • EXPLDE
  • LATERAL view
  • Windowing functions and more

Optimizing Hive Performance:

  • Partitioning
  • Bucketing
  • Join Optimizations
  • Map Side Joins
  • Indexes
  • Writing custom User Defined Functions (UDFs) in Java.
  • UDAF (User Defined Aggregate Functions)
  • GenericUDF and GenericUDTF for Python implementations
  • Implementation of MapReduce for SELECT, GROUP BY, and JOIN operations

For SQL Newbies:

  • SQL In Great Depth: The course concludes with an SQL primer, ensuring that even those starting from scratch can grasp the essentials before diving into Hive.

Join us on this comprehensive journey to master Hive for processing big data. With our team of seasoned professionals and a curriculum designed to cater to all levels, you're set to unlock the full potential of your data with Hive. 🚀📊✨

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857298
udemy ID
23/05/2016
course created date
22/11/2019
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