Spark First Principles | Rock the JVM

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Spark Essentials with Scala

Welcome

Welcome (10:59)
Spark Setup for Windows (5:53)
How to Make the Best out of This Course (2:32)
Scala Recap (25:05)
A Note on Scala Best Practice (2:21)
Spark First Principles (8:59)

Spark Structured API with DataFrames

DataFrames Basics (23:09)
DataFrames Basics: Exercises (8:16)
How DataFrames Work (6:22)
Data Sources (13:25)
Data Sources, Part 2 + Exercises (27:43)
DataFrame Columns and Expressions (24:33)
Columns and Expressions: Exercises (17:12)
DataFrame Aggregations (28:13)
DataFrame Joins (20:23)
Joins: Exercises (17:27)
User Defined Functions (UDFs) (13:48)
User Defined Aggregate Functions (UDAFs) (26:49)

Spark Types and Datasets

Working with Spark Types (28:31)
Advanced Spark Types (21:17)
Managing Nulls in Data (17:14)
Type-Safe Processing: Datasets (24:17)
Datasets, Part 2 + Exercises (15:40)
The Variant Type (16:30)

Spark SQL

The Spark SQL Shell (13:46)
Programmatic Spark SQL (17:11)
Spark SQL: Exercises (19:53)
Advanced Spark SQL: ANSI, Pipes, SQL UDFs and More (25:50)

Spark Low-Level

RDDs (17:05)
RDDs, Part 2 + Exercises (26:48)

Practical Spark

How Spark Runs on a Cluster (30:11)
Deploying Spark Applications on a Cluster (20:44)

A Real Big Data Project

A Big Data Problem (14:07)
Investigative Data Analysis on Big Data (27:48)
Investigative Data Analysis on Big Data, Part 2 (35:38)
Gathering Answers and Running our Solution on Amazon EMR (20:20)

Epilogue

You ROCK! (0:30)

Spark First Principles

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