| Introduction to Big Data & Apache Spark |
- Introduction of Big Data
- Introduction & a brief history of Apache Spark
- Components of Apache Spark unified stack
- Who uses Apache Spark?
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| Getting started with Apache Spark |
- Downloading & installing Apache Spark
- Running the examples & shell (Python & Scala)
- Introduction to core Apache Spark concepts
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| Introduction to Online Lab |
- What is Online Lab
- Components of Online Lab
- Logging into Online Lab
- First Hands-On using Online Lab
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| Understanding resilient distributed datasets (RDD) |
- RDD basics
- Creating RDDs
- Working with RDD operations
- Passing functions to Apache Spark
- Common transformations and actions
- Persistence (caching)
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| Working with key/value pairs |
- Creating pair RDDs
- Transformations on pair RDDs
- Actions available on pair RDDs
- Data partitioning (advanced)
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| Loading and saving your data |
- Various file formats & file systems
- Structured data with Apache Spark SQL
- Databases
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| Advanced Apache Spark programming |
- Introduction
- Accumulators
- Broadcast variables
- Working on a per-partition basis
- Piping to external programs
- Numeric RDD operations
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| Running Apache Spark on a cluster |
- Introduction
- Apache Spark runtime architecture
- Submitting applications with Apache Spark-submit
- Packaging your code and dependencies
- Scheduling within and between Apache Spark applications
- Cluster managers
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| Introduction to Apache Spark libraries |
- Understanding Apache Spark SQL
- Using Apache Spark SQL in applications
- Machine learning basics
- Machine learning with MLlib, GraphX
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| Apache Spark streaming |
- A simple example
- Architecture and abstraction
- Transformations & output operations
- Input sources
- Streaming UI
- Performance considerations
- Kafka basics
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