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IT & Software Other IT & Software Apache Flink

Apache Flink | A Real Time & Hands-On course on Flink

Complete, In-depth & HANDS-ON practical course on a technology better than Spark for Stream processing i.e. Apache Flink
Rating: 4.1 out of 54.1 (825 ratings)
6,881 students
Created by J Garg - Hadoop Real Time Learning
Last updated 12/2020
English
English
30-Day Money-Back Guarantee

What you'll learn

  • Learn a cutting edge and Apache's latest Stream processing framework i.e. Flink.
  • Learn a technology which is much faster than Hadoop and Spark.
  • Understand the working of each and every component of Apache Flink with HANDS-ON Practicals.
  • Even learn those concepts which are not properly explained in Flink's official documentation.
  • Solve Real-Time Business case studies using Apache Flink.
  • Data-sets and Flink codes used in lectures are available in resources tab. This will save your typing efforts.
Curated for the Udemy for Business collection

Requirements

  • Basic knowledge of Distributed Frameworks.
  • Basic knowledge of OOPS.
  • Rest everything about Apache Flink is covered in this course with Practicals.

Description

Apache Flink is the successor to Hadoop and Spark. It is the next generation Big data engine for Stream processing. If Hadoop is 2G, Spark is 3G then Apache Flink is the 4G in Big data stream processing frameworks. Actually Spark was not a true Stream processing framework, it was just a makeshift to do it but Apache Flink is a TRUE Streaming engine with added capacity to perform Batch, Graph, Table processing and also to run Machine Learning algorithms.

Apache Flink is the latest Big data technology and is rapidly gaining momentum in the market. It is assumed that same like  Apache Spark replaced Hadoop, Flink can also replace Spark in the coming near future.

Demand of Flink in market is already swelling. Big companies like Capital One (Bank), Alibaba (eCommerce), Uber (Transportation) have already started using Apache Flink to process their Real-time Big data and thousands other are diving into.

What's included in the course ?

  • Complete Apache Flink concepts explained from Scratch to Real-Time implementation.

  • Each and Every Apache Flink concept is explained with a HANDS-ON Flink code of it.

  • Include even those concepts, the explanation to which is not very clear even in Flink official documentation.

  • For Non-Java developer's help, All Flink Java codes are explained line by line in such a way that even a non -technical person can understand.

  • Flink codes and Datasets used in lectures are attached in the course for your convenience.

Who this course is for:

  • Students who want to learn Apache Flink from SCRATCH to its Live Project Implementation.
  • Who are new to Stream processing and want to learn a Stream processing framework which is better than Spark.
  • Software engineers who feel they missed an early opportuninty to get into Hadoop & Spark.
  • Hadoop & Spark Developers who want to upgrade themseleves to Apache's latest Big Data Streaming Engine.

Featured review

Abu Bakar Siddiqur Rahman
Abu Bakar Siddiqur Rahman
2473 courses
5 reviews
Rating: 4.5 out of 53 weeks ago
This is an excellent course. Instructor provides good lecture. However, it will be plus if you have a basic knowledge on Apache flink, otherwise you can complete the course: it will take some time more.

Course content

14 sections • 55 lectures • 5h 48m total length

  • Preview04:14
  • Announcement
    01:01
  • Preview04:14
  • Hadoop Vs Streaming Engines (Spark & Flink)
    05:55
  • Spark Vs Flink
    11:19
  • Flink Architecture/Ecosystem
    02:55
  • Flink's programming model | Flow of a Flink program
    12:00
  • Installing Flink
    07:41

  • Default Code structure of a Flink Program
    04:49
  • WordCount using Map, Flatmap, Filter, groupby | Part 1
    11:31
  • WordCount using Map, Flatmap, Filter, groupby | Part 2
    03:48
  • Joins - Inner join
    07:00
  • Joins - Left, Right & Full Outer Join
    05:30
  • Preview06:29

  • Data Sources & Sinks of Datastream API
    10:06
  • First program using Datastream API
    05:04
  • Reduce Operation
    06:41
  • Fold Operation
    02:46
  • Aggregation Operations in Flink
    05:47
  • Split Operation
    03:30
  • Iterate Operator
    05:39
  • Assignment 1
    1 question

  • Introduction to Windowing
    04:39
  • Window Assigners
    01:55
  • Various Time Notions of Windows in Flink
    03:36
  • Preview06:37
  • Sliding Windows Implementation
    02:43
  • Session Windows Implementation
    05:15
  • Global Windows Implementation
    03:41

  • Triggers in Windows
    07:47
  • Evictors for Windows
    05:41

  • Watermarks, Late Elements & Allowed Lateness
    08:41
  • How to generate Watermarks
    05:48
  • Quiz 1
    5 questions

  • What is a State in Flink
    05:48
  • Checkpointing and Barrier Snapshoting
    08:38
  • Preview04:18
  • Types of States
    02:37
  • Preview08:08
  • List State Implementation
    02:26
  • Reducing State Implementation
    02:22
  • Assignment
    1 question
  • Managed Operator State Implementation
    06:50
  • Implement Checkpointing in a Flink Program
    08:38
  • The Broadcast State Implementation
    09:49
  • Queryable State (Beta Version)
    10:47

  • Getting Twitter data using its APIs
    13:39
  • Adding Kafka to Flink as a Data source
    05:09

  • Twitter data analysis using Flink
    12:34

  • Identifying Fraud transactions in Real-Time
    14:48

Instructor

J Garg - Hadoop Real Time Learning
Hadoop Trainer
J Garg - Hadoop Real Time Learning
  • 4.3 Instructor Rating
  • 2,002 Reviews
  • 13,476 Students
  • 4 Courses

At Hadoop Real time Learning, the courses are made keeping in mind the Real-time implementation of Big data technologies in Live Projects. We make courses which majorly consist of Hands-On & Practicals. All our courses contain a detailed knowledge of a technology from Scratch to Advance level. Course's lectures explain the codes in such a way that even a Non-technical person can understand.

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