From 0 to 1: Hive for Processing Big Data [Video]
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Free ChapterYou, Us & This Course
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Introducing Hive
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Hadoop and Hive Install
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Hadoop and HDFS Overview
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Hive Basics
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Built-in Functions
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Sub-Queries
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Partitioning
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Bucketing
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Windowing
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Understanding MapReduce
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MapReduce logic for queries: Behind the scenes
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Join Optimizations in Hive
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Custom Functions in Python
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Custom functions in Java
- Introducing UDFs - you're not limited by what Hive offer
- The Simple UDF: The standard function for primitive types
- The Simple UDF: Java implementation for replacetext()
- Generic UDFs, the Object Inspector and DeferredObjects
- The Generic UDF: Java implementation for containsstring()
- The UDAF: Custom aggregate functions can get pretty complex
- The UDAF: Java implementation for max()
- The UDAF: Java implementation for Standard Deviation
- The Generic UDTF: Custom table generating functions
- The Generic UDTF: Java implementation for namesplit()
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SQL Primer - Select Statements
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SQL Primer - Group By, Order by and Having
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SQL Primer – Joins
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Appendix
About this
video
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.
- Publication date:
- December 2017
- Publisher
- Packt
- Duration
- 15 hours 16 minutes
- ISBN
- 9781788995054
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