From 0 to 1: Hive for Processing Big Data | Data Science Online Course by Udemy

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End-to-End Hive: HQL, Partitioning, Bucketing, UDFs, Windowing, Optimization, Map Joins, Indexes

An excellent training about Data Science

From 0 to 1: Hive for Processing Big Data

Prerequisites: Hive requires knowledge of SQL. The course includes and SQLprimer at the end. Please do that first if you don’t know SQL. You’ll need to know Java ifyou want to follow the sectionson custom functions. Taught bya 4 person team including 2Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with large-scaledata. Hive islike anew 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 thatA new friend with an old face: Hive helps you leverage the power of Distributed computing and Hadoop for Analytical processing. It’s interface is like an old friend: the very SQLlike HiveQL. This course will fill in all the gaps between SQLand what you need to use Hive. End-to-End: The course is anend-to-end guide for using Hive: whether you are analyst who wants to process dataor 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 hasa primer on all the basic SQLconstructs, .Practical: Everything is taught using real-lifeexamples, workingqueries and code. What’s Covered: Analytical Processing: Joins, Subqueries, Views, Table GeneratingFunctions, Explode, Lateral View, Windowing and moreTuning Hive for better functionality: Partitioning, Bucketing, Join Optimizations, Map Side Joins, Indexes, Writingcustom User Definedfunctions in Java. UDF, UDAF, GenericUDF, GenericUDTF, Custom functions in Python, Implementation of MapReduce for Select, Group by and JoinFor SQLNewbies: SQL In Great Depth

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