Apache Flink

1.Demystify Scala

Introduction to Scala

Setup, Installation and configuration of Scala

Develop and execute Scala Programs

Scala operators and features

Different Functions, procedures and Anonymous functions

Deep dive into Scala APIs

Collections Array, Map, Lists, Tuples and Loops

Advanced operations - Pattern matching

Eclipse IDE with Scala

2. Object Oriented and Functional Programming

Object oriented programming

Oops concepts

Constructor, getter, setter, singleton, overloading and overriding

Type Inference, Implicit Parameters, Closures

Lists, Maps and Map Operations

Nested Classes, Visibility Rules

Functional Structures

Functional programming constructs

3. Introduction to Apache Flink

Learn What and why Apache Flink

Understand Features of Apache Flink

Apache Flink architecture and Flink design principles

Work of master process - JobManager

Role of worker process - TaskManager

Workers, Slots and Resources

Overview of Apache Flink APIs

Understand difference between Apache Spark and Apache Flink to learn Flink vs Spark.

4. Master Flink Stack

Distributed Streaming DataFlow at Runtime with Flink

Apache Flink APIs

Apache Flink Libraries

Data Flow in Apache Flink

Fault tolerance in Apache Flink

5. Setup and Installation of single node Flink

Setup of Apache Flink environment and pre-requisites

Installation and configuration of Flink on single node

Troubleshooting the encountered problems

6. Setup and Installation of multi node Flink cluster and Cloud

Setup environment on Cloud

Install pre-requisites on all nodes

Deploy Apache Flink on cluster and Cloud

Play with Flink in cluster mode

7. Master DataStream API for Unbounded Streams

Introduction to Flink DataStream API

Different DataStream Transformations in Flink

Various Data Sources - File based, Socket based, Collection based, Custom

Responsibility of Data Sink in Apache Flink

Iterations in DataStream APIs

DataStream Execution Parameters - Fault tolerance, Controlling Latency

8. Learn Flink DataSet APIs for Static Data

Overview of DataSet APIs in Flink

Various DataSet Transformations in Flink

Different Data Sources - File based, Collection based, Generic

Responsibility of Data Sink in Flink DataSet APIs

Iteration Operators in DataSet APIs

Operating on Data Objects in Functions - Object Reuse Disabled/Enabled

9. Play with Flink Table APIs and SQL Beta

Registering Tables in Flink

Table Access and various Table API operators in Flink

SQL on batch tables and Streaming Tables

Writing Flink Tables to external sinks

10. Apache Flink Libraries

Overview of Flink Libraries

Flink CEP - Complex Event Processing library

Apache Flink Machine Learning library

Apache Flink Gelly -Graph processing API and Library

11. Flink Integration with other Big data tools

Integrate Flink with Hadoop

Process existing HDFS data with Flink

Yarn and Flink integration

Flink Data Streaming with Kafka

Consume data in real time from Kafka

12. Programming in Flink

Parallel Data Flow in Flink

Develop complex Streaming applications in Flink

Handle Batch processing in Flink using DataSet APIs

Troubleshooting and Debugging Flink Programs

Best Practices of development in Flink

Real time Apache Flink Project