Franklin

From 0 to 1: Hive for Processing Big Data [electronic resource] / Loonycorn.

Author/Creator:
Loonycorn, author.
Publication:
Packt Publishing, 2017.
Format/Description:
Video
1 online resource (1 video file, approximately 15 hr., 16 min.)
Edition:
1st edition
Status/Location:
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Form/Genre:
Electronic videos.
System Details:
video file
Summary:
End-to-End Hive: HQL, Partitioning, Bucketing, UDFs, Windowing, Optimization, Map Joins, Indexes About This Video Analytical Processing: Joins, Subqueries, Views, Table Generating Functions, Explode, Lateral View, Windowing and more Tuning Hive for better functionality: Partitioning, Bucketing, Join Optimizations, Map Side Joins, Indexes, Writing custom User Defined functions in Java. UDF, UDAF, GenericUDF, GenericUDTF, Custom functions in Python, Implementation of MapReduce for Select, Group by and Join In Detail Hive is like a new friend with an old face (SQL). This course is an end-to-end, practical guide to using Hive for Big Data processing. Let's parse that A new friend with an old face: Hive helps you leverage the power of Distributed computing and Hadoop for Analytical processing. Its interface is like an old friend: the very SQL like HiveQL. This course will fill in all the gaps between SQL and what you need to use Hive. End-to-End: The course is an end-to-end guide for using Hive: whether you are analyst who wants to process data or an Engineer who needs to build custom functionality or optimize performance - everything you'll need is right here. New to SQL? No need to look elsewhere. The course has a primer on all the basic SQL constructs, Practical: Everything is taught using real-life examples, working queries and code.
Notes:
Online resource; Title from title screen (viewed December 15, 2017)