End-to-End Hive: HQL, Partitioning, Bucketing, UDFs, Windowing, Optimization, Map Joins, Indexes
About This Video
End-to-End Hive: HQL, Partitioning, Bucketing, UDFs, Windowing, Optimization, Map Joins, Indexes
About This Video
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.
Chapter 1 : You, Us & This Course
You, Us & This Course 00:02:03
Chapter 2 : Introducing Hive
Hive: An Open-Source Data Warehouse 00:12:59
Hive and Hadoop 00:09:19
Hive vs Traditional Relational DBMS 00:13:52
HiveQL and SQL 00:07:21
Chapter 3 : Hadoop and Hive Install
Hadoop Install Modes 00:08:33
Hadoop Install Step 1: Standalone Mode 00:15:47
Hadoop Install Step 2: Pseudo-Distributed Mode 00:11:45
Hive install 00:12:05
Code-Along: Getting started 00:06:25
Chapter 4 : Hadoop and HDFS Overview
What is Hadoop? 00:07:25
HDFS or the Hadoop Distributed File System 00:11:01
Chapter 5 : Hive Basics
Primitive Datatypes 00:17:08
Collections_Arrays_Maps 00:09:29
Structs and Unions 00:05:58
Create Table 00:13:15
Insert Into Table 00:12:05
Insert into Table 2 00:06:51
Alter Table 00:07:22
HDFS 00:09:25
HDFS CLI - Interacting with HDFS 00:10:59
Code-Along: Create Table 00:09:54
Code-Along: Hive CLI 00:03:07
Chapter 6 : Built-in Functions
Three types of Hive functions 00:06:46
The Case-When statement, the Size function, the Cast function 00:10:10
The Explode function 00:13:07
Code-Along: Hive Built - in functions 00:04:28
Chapter 7 : Sub-Queries
Quirky Sub-Queries 00:07:14
More on subqueries: Exists and In 00:15:14
Inserting via subqueries 00:05:23
Code-Along: Use Subqueries to work with Collection Datatypes 00:05:57
Views 00:12:18
Chapter 8 : Partitioning
Indices 00:06:41
Partitioning Introduced 00:06:37
The Rationale for Partitioning 00:06:16
How Tables are partitioned 00:09:53
Using Partitioned Tables 00:05:27
Dynamic Partitioning: Inserting data into partitioned tables 00:12:44
Code-Along: Partitioning 00:04:04
Chapter 9 : Bucketing
Introducing Bucketing 00:11:57
The Advantages of Bucketing 00:04:55
How Tables are bucketed 00:12:37
Using Bucketed Tables 00:07:22
Sampling 00:11:13
Chapter 10 : Windowing
Windowing Introduced 00:12:59
Windowing - A Simple Example: Cumulative Sum 00:09:39
Windowing - A More Involved Example: Partitioning 00:11:55
Windowing - Special Aggregation Functions 00:15:08
Chapter 11 : Understanding MapReduce
The basic philosophy underlying MapReduce 00:08:50
MapReduce - Visualized and Explained 00:09:04
MapReduce - Digging a little deeper at every step 00:10:21
Chapter 12 : MapReduce logic for queries: Behind the scenes
MapReduce Overview: Basic Select-From-Where 00:11:34
MapReduce Overview: Group-By and Having 00:09:12
MapReduce Overview: Joins 00:14:17
Chapter 13 : Join Optimizations in Hive
Improving Join performance with tables of different sizes 00:13:12
The Where clause in Joins 00:04:53
The Left Semi Join 00:12:11
Map Side Joins: The Inner Join 00:09:42
Map Side Joins: The Left, Right and Full Outer Joins 00:11:36
Map Side Joins: The Bucketed Map Join and the Sorted Merge Join 00:07:52
Chapter 14 : Custom Functions in Python
Custom functions in Python 00:10:40
Code-Along: Custom Function in Python 00:05:45
Chapter 15 : Custom functions in Java
Introducing UDFs - you’re not limited by what Hive offers 00:04:38
The Simple UDF: The standard function for primitive types 00:07:04
The Simple UDF: Java implementation for replacetext() 00:08:35
Generic UDFs, the Object Inspector and DeferredObjects 00:13:51
The Generic UDF: Java implementation for containsstring() 00:09:11
The UDAF: Custom aggregate functions can get pretty complex 00:14:09
The UDAF: Java implementation for max() 00:09:21
The UDAF: Java implementation for Standard Deviation 00:10:48
The Generic UDTF: Custom table generating functions 00:07:38
The Generic UDTF: Java implementation for namesplit() 00:10:21
Chapter 16 : SQL Primer - Select Statements
Select Statements 00:11:47
Select Statements 2 00:14:12
Operator Functions 00:06:55
Chapter 17 : SQL Primer - Group By, Order by and Having
Aggregation Operators Introduced 00:18:16
The Group by Clause 00:17:20
More Group by Examples 00:19:47
Order by 00:16:15
Having 00:19:52
Chapter 18 : SQL Primer – Joins
Introduction to SQL Joins 00:09:54
Cross Joins and Cartesian Joins 00:17:03
Inner Joins 00:19:53
Left Outer Joins 00:15:31
Right, Full Outer Joins, Natural Joins, Self Joins 00:16:08
Chapter 19 : Appendix
[For Linux/Mac OS Shell Newbies] Path and other Environment Variables 00:08:26
Setting up a Virtual Linux Instance - For Windows Users 00:15:59