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Apache flink

APACHE FLINK TRAINING

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Product Description

What is Apache Flink?

Apache Flink is an open source stream processing framework developed by the Apache Software Foundation. The core of Apache Flink is a distributed streaming dataflow engine written in Java and Scala. Apache Flink’s dataflow programming model provides event-at-a-time processing on both finite and infinite datasets. At a basic level, Flink programs consist of streams and transformations. Conceptually, a stream is a (potentially never-ending) flow of data records, and a transformation is an operation that takes one or more streams as input, and produces one or more output streams as a result. Programs can be written in Java, Scala, Python, and SQL and are automatically compiled and optimized into dataflow programs that are executed in a cluster or cloud environment.

Why Apache Flink?

Flink provides a high-throughput, low-latency streaming engine as well as support for event-time processing and state management. Flink applications are fault-tolerant in the event of machine failure and support exactly-once semantics. Flink executes arbitrary dataflow programs in a data-parallel and pipelined manner. Flink’s pipelined runtime system enables the execution of bulk/batch and stream processing programs. Furthermore, Flink’s runtime supports the execution of iterative algorithms natively.

Flink Introduction

Architecture

Distributed Execution

Job Manager

Task Manager

Features

Deploying Flink on Google Cloud and AWS

Data Stream API 

Execution environment

Data sources

Transformations

Data sinks

Connectors

Batch Processing API

Data sources

Transformations

Broadcast Variable

Connectors to various Systems

Iterations

Structure data handling using Table API 

Registering tables

Accessing the registered table

Operators

Data types

SQL

Complex event processing

Introduction to CEP and Flink CEP

Event Streams

Pattern API

Continuity

Selecting from Pattern

Graph API

Flink Graph Library – Gelly

Graph Representation

Graph Properties

Graph Transformations

Graph Mutations

Iterative Graph Processing

Scatter-Gather Processing

Integration between Flink and Hadoop

Flink-Yarn Session

Job Submission to Flink

Execution of a Flink job on YARN

Flink and YARN interaction details

Duration & Timings :

Duration – 30 Hours.

Course Fee : $300    Discount Offer  

Training Type: Online Live Interactive Session.

Faculty: Experienced.

Weekend Session – Sat & Sun  9:30 AM – 12:30 PM (EST) – 5 Weeks. December 16, 2017.

Weekend Session – Sat & Sun  9:30 AM – 12:30 PM (EST) – 5 Weeks. January 20, 2017.

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