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Mastering SparkSQL with Scala Video Course
Part 1: Getting Started
Local development setup (6:59)
Develop first application (15:26)
Part 2: Working with the SparkSQL API
Getting to know DataFrames: Schema (i) (6:12)
Introduction to the Dataset API (6:37)
SparkSQL DSL (i): Working with Columns (6:52)
SparkSQL DSL (ii): Column functions (10:44)
SparkSQL DSL (iii): sql.functions (5:47)
SparkSQL DSL (iv): SQL expressions (10:18)
First assignment: Solving a business question using SparkSQL (12:19)
Concepts (i): What is Spark? (8:35)
Working with groupBy, sort and aggregations (11:01)
Understanding window functions (6:31)
Concepts (ii): Partitions, AST, Logical Plan & Optimizations (13:04)
Joining DataFrames (10:28)
Union on DataFrames (4:11)
Using map and flatMap (9:20)
MapGroups on DataFrames (10:59)
Working with UDFs (user-defined functions) (10:42)
Concepts (iii): The relation of SparkSQL and Spark Core (3:04)
Part 3: Writing Tests
Why testing is essential (3:13)
Testable code and writing a first test (11:13)
Writing a DataFrame test (17:26)
Part 4: Reading and Writing Files
Reading and Writing data (16:12)
The CSV file format (2:57)
The Parquet file format (4:27)
Optimizations with Parquet files (5:20)
Part 5: The Dataset API
Introduction to the Dataset API (3:22)
Datasets and Encoders (12:31)
Datasets are views on DataFrames (5:13)
Using filter with Datasets (3:04)
Using map with Datasets (4:16)
Joining Datasets (5:02)
MapGroups on Datasets (6:52)
Part 6: Software Engineering with SparkSQL
How to write high-quality code (20:26)
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Getting to know DataFrames: Schema (i)
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