Apache Flink | A Real Time & Hands-On course on Flink
- 6 hours on-demand video
- 34 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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- 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.
- Basic knowledge of Distributed Frameworks.
- Basic knowledge of OOPS.
- Rest everything about Apache Flink is covered in this course with Practicals.
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.
- 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.
This is the pilot lecture to get you familiar with Flink. The video will explain What is Apache Flink and what functionalities it provides.
This lecture will tell you the difference between stream processing and batch processing.
Tumbling window is a time based window. It can be created using processing and event time notions. This video shows how to implement tumbling windows in a Flink program.
Flink provides us a fault tolerance to its applications. Means upon any node failures the app can be restored exactly from the same point where it failed.
Flink provides Fault tolerance using State and checkpointing. So this is the first lecture which explains what is a State in flink.
Incremental checkpointing is a new feature in Apache Flink. It was included form flink 1.3. It gives us better performance than conventional checkpointing.
What is Value State in Flink and how to implement it in a Flink program.