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Fundamentals of Apache Flink
Rating: 4.1 out of 5(42 ratings)
324 students

Fundamentals of Apache Flink

Use Apache Flink and its ecosystem to process real-time big data
Created byPackt Publishing
Last updated 11/2019
English

What you'll learn

  • Build your own Flink development environment on a Linux server
  • Monitor your stream processing in real-time using the Flink UI
  • Organize your data comprehensively using data processing pipelines
  • Build end-to-end, real-time analytics projects
  • Design a distributed Flink environment to efficiently process, transform, and aggregate your data

Course content

6 sections • 21 lectures • 3h 14m total length

  • The Course Overview5:15

    This video will give you an overview about the course.

  • What Is Apache Flink?7:10

    You will be able to learn about Flink architecture and its components.

       •  Define Apache Flink

       •  Explore Flink architecture

       •  Learn about the components of the Flink framework

  • What Is Big Data and Why Does It Matter?7:08

    The aim of this video is to help you understand Big Data conceptually and also the importance of Big Data Analytics.

       •  Learn what Big Data is

       •  Explore the seven Vs of Big Data

       •  Explore Big Data Analytics

  • Installing Flink in Your Local System9:52

    In this video, you will learn how to install Flink in your local system.

       •  Download and Install Flink

       •  Start a cluster and shell

       •  Open cluster UI

  • Setting Up the AWS Environment6:50

    In this video, you will learn how to setup Flink in AWS.

       •  Create EC2 instance running Linux

       •  Download Flink

       •  Install Flink and start the cluster

  • Test Your Knowledge

Requirements

  • A basic knowledge of Hadoop and big data is assumed, and a reasonable knowledge of Java or Scala is expected.

Description

Have you heard of Apache Flink, but don't know how to use it to get on top of big data? Have you used Flink, but want to learn how to set it up and use it properly? Either way, this course is for you.

This course first introduces Flink concepts and terminology, and then moves on to building a Flink instance, collecting data, and using that data to generate output that can be used as processed data input into other systems. You will also use the Flink APIs to process data in batch and streaming modes.

By the end of the course, you will be capable of using the Apache Flink ecosystem to achieve complex tasks such as event processing and machine learning.

About the Author

Sridhar Alla is the co-founder and CTO of Blue Whale Consulting and is expert at helping companies (big and small) define their vision for systems and capabilities that will allow them to establish a strategic execution plan to deal with the ever-growing data collected to support analytics and product teams. He has very experienced at dealing with all aspects of data collection, security, governance, and processing as part of end-to-end big data analytics and machine learning initiatives (including predictive modeling, deep learning, and ML automation).

Sridhar is a published book author and an avid presenter at numerous conferences, including Strata, Hadoop World, and Spark Summit. He also has several patents filed with the US PTO on large-scale computing and distributed systems.

He has over 18 years' experience writing code in Scala, Java, C, C++, Python, R, and Go, and has extensive hands-on knowledge of Spark, Flink, TensorFlow, Keras, Hadoop, Cassandra, HBase, MongoDB, Riak, Redis, Zeppelin, Mesos, Docker, Kafka, ElasticSearch, Solr, H2O, machine learning, text analytics, distributed computing, and high-performance computing.

Sridhar lives with his wife and daughter in New Jersey and in his spare time loves blogging and coaching organizations on next-generation advancements in technology and their alignment with business goals.

Who this course is for:

  • This course targets big data developers keen to process batch and real-time data on distributed systems.

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