Introduction: Data Analytics
Introduction: Spark Architecture
Introduction: Spark Shell
Introduction: Web UI
Essentials: Hello World
Essentials: Resilient Distributed Datasets
Essentials: Three Ways to Create an RDD
Essentials: RDD Transformations
Essentials: RDD Actions
Connecting Spark: Reading Data From Cassandra
Connecting Spark: Processing Cassandra Data
Connecting Spark: Converting Cassandra Data
Connecting Spark: Saving Data Back to Cassandra
Optimization: Broadcast Variables
Optimization: Accumulator Variables
Optimization: RDD Persistence
Key/Value Pairs: Introduction to Pair RDDs
Key/Value Pairs: Aggregation
Key/Value Pairs: Grouping and Sorting
Key/Value Pairs: Joins
Key/Value Pairs: Set Operations
Tuning Partitioning: Understanding Partitioning
Tuning Partitioning: Partitioning Rules
Tuning Partitioning: Controlling Partitioning
Tuning Partitioning: Data Shuffling
Spark/Cassandra Connector: Count
Spark/Cassandra Connector: Group By Key
Spark/Cassandra Connector: Joining Tables
Spark/Cassandra Connector: Cassandra-Aware Partitioning
Spark Streaming: Discretized Stream
Spark Streaming: Architecture
Spark Streaming: First App
Spark Streaming: Stateless Transformations
Spark Streaming: Stateful Transformations
Spark Streaming: Window Transformation
Spark Streaming: Output Operations
Spark Streaming: Checkpointing and Recovery
Spark Streaming: Persistence
Spark Streaming: Controlling Parallelism
Spark SQL: Spark SQL Basics
Spark SQL: Creating DataFrames
Spark SQL: Accessing DataFrame Schema and Rows
Spark SQL: RDD Operations on DataFrames
Spark SQL: Language-Integrated Queries
Spark SQL: Saving DataFrames to Cassandra
Spark SQL: Querying Cassandra with SQL
Spark SQL: Writing Efficient SQL Queries
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DSE Version: 5.x

Introduction: Data Analytics



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