The Big Data Certification Training Bundle

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9 Courses & 64.5 Hours
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What's Included

From 0 to 1 : Hive for Big Data Processing
  • Certification included
  • Experience level required: All levels
  • Access 86 lectures & 15 hours of content 24/7
  • Length of time users can access this course: Lifetime

Course Curriculum

86 Lessons (15h)

  • You, Us & This Course
    You, Us & This Course2:02
  • Introducing Hive
    Hive: An Open-Source Data Warehouse12:59
    Hive and Hadoop9:19
    Hive vs Traditional Relational DBMS13:52
    HiveQL and SQL7:20
  • Hadoop and Hive Install
    Hadoop Install Modes8:32
    Setting up a Virtual Linux Instance - For Windows Users13:50
    Hadoop Install Step 1 : Standalone Mode9:33
    Hadoop Install Step 2 : Pseudo-Distributed Mode14:25
    Hive install12:05
    Code-Along: Getting started6:24
  • Hadoop and HDFS Overview
    What is Hadoop?7:25
    HDFS or the Hadoop Distributed File System11:01
  • Hive Basics
    Primitive Datatypes17:07
    Collections Arrays Maps9:28
    Structs and Unions5:57
    Create Table13:15
    Insert Into Table12:05
    Insert into Table 26:51
    Alter Table7:22
    HDFS9:25
    HDFS CLI - Interacting with HDFS10:59
    Code-Along: Create Table9:54
    Code-Along : Hive CLI3:06
  • Built-in Functions
    Three types of Hive functions6:45
    The Case-When statement, the Size function, the Cast function10:09
    The Explode function13:07
    Code-Along : Hive Built - in functions4:28
  • Sub-Queries
    Quirky Sub-Queries7:13
    More on subqueries: Exists and In15:13
    Inserting via subqueries5:23
    Code-Along : Use Subqueries to work with Collection Datatypes5:57
    Views12:18
  • Partitioning
    Indices6:40
    Partitioning Introduced6:36
    The Rationale for Partitioning6:16
    How Tables are Partitioned9:52
    Using Partitioned Tables5:27
    Dynamic Partitioning: Inserting data into partitioned tables12:44
    Code-Along : Partitioning4:03
  • Bucketing
    Introducing Bucketing11:56
    The Advantages of Bucketing4:54
    How Tables are Bucketed
    Using Bucketed Tables7:22
    Sampling11:13
  • Windowing
    Windowing Introduced12:59
    Windowing - A Simple Example: Cumulative Sum9:39
    Windowing - A More Involved Example: Partitioning11:55
    Windowing - Special Aggregation Functions15:08
  • Understanding MapReduce
    The basic philosophy underlying MapReduce8:49
    MapReduce - Visualized and Explained9:03
    MapReduce - Digging a little deeper at every step10:21
  • MapReduce logic for queries: Behind the scenes
    MapReduce Overview: Basic Select-From-Where11:33
    MapReduce Overview: Group-By and Having9:12
    MapReduce Overview: Joins14:17
  • Join Optimizations in Hive
    Improving Join performance with tables of different sizes13:12
    The Where clause in Joins4:52
    The Left Semi Join12:11
    Map Side Joins: The Inner Join9:41
    Map Side Joins: The Left, Right and Full Outer Joins11:36
    Map Side Joins: The Bucketed Map Join and the Sorted Merge Join7:52
  • Custom Functions in Python
    Custom functions in Python10:40
    Code-Along : Custom Function in Python5:45
  • Custom functions in Java
    Introducing UDFs - you're not limited by what Hive offers4:38
    The Simple UDF: The standard function for primitive types7:03
    The Simple UDF: Java implementation for replacetext()8:34
    Generic UDFs, the Object Inspector and DeferredObjects13:50
    The Generic UDF: Java implementation for containsstring()9:11
    The UDAF: Custom aggregate functions can get pretty complex14:09
    The UDAF: Java implementation for max()9:21
    The UDAF: Java implementation for Standard Deviation10:47
    The Generic UDTF: Custom table generating functions7:38
    The Generic UDTF: Java implementation for namesplit()10:21
  • SQL Primer - Select Statemets
    Select Statements11:46
    Select Statements 214:11
    Operator Functions6:55
  • SQL Primer - Group By, Order By and Having
    Aggregation Operators Introduced18:15
    The Group By Clause17:19
    More Group By Examples19:46
    Order By16:15
    Having19:52
  • SQL Primer - Joins
    Introduction to SQL Joins9:54
    Cross Joins aka Cartesian Joins17:02
    Inner Joins19:52
    Left Outer Joins15:31
    RIght, Full Outer Joins, Natural Joins, Self Joins16:08

From 0 to 1 : Hive for Big Data Processing

L
LoonyCorn

Loonycorn is comprised of four individuals—Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh—who have honed their tech expertises at Google and Flipkart. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

Description

Hive is a Big Data processing tool that helps you leverage the power of distributed computing and Hadoop for analytical processing. Its interface is somewhat similar to SQL, but with some key differences. This course is an end-to-end guide to using Hive and connecting the dots to SQL. It's perfect for both professional and aspiring data analysts and engineers alike. Don't know SQL? No problem, there's a primer included in this course! Upon completion of this course, and all courses included in the bundle, you'll also receive a certification of completion validating your new skills! This is especially useful for including in your portfolio or resume, so future employers can feel confident in your skill set.

  • Access 86 lectures & 15 hours of content 24/7
  • Write complex analytical queries on data in Hive & uncover insights
  • Leverage ideas of partitioning & bucketing to optimize queries in Hive
  • Customize Hive w/ user defined functions in Java & Python
  • Understand what goes on under the hood of Hive w/ HDFS & MapReduce
  • Includes a certification of completion

Specs

Details & Requirements

  • Length of time users can access this course: lifetime
  • Access options: web streaming, mobile streaming
  • Certification of completion not included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: all levels, but knowledge of SQL and Java would be helpful

Terms

  • Unredeemed licenses can be returned for store credit within 30 days of purchase. Once your license is redeemed, all sales are final.