- The architecture of Apache Flink
- Features of the DataSet API
- Using POJO classes for DataSet typing
- Working with joins in Flink
- Using MySQL with Flink
- Using broadcast variables to share and collect data
Skill Level Advanced
- [Instructor] Apache Flink is one of the rising stars among the plethora of big data processing technologies available today. It's flexibility across batch and stream processing combined with simplicity of development has propelled it to the top of the big data pyramid where it competes with the likes of Apache Spark and Hadoop. Apache Flink is an essential skill today for any developer in the big data world. My name is Kumaran Ponnambalam. In this course, I will show you how to build batch data processing pipelines with Apache Flink. I will start off by showing you how to install and set up Apache Flink in various modes. Then, I will demonstrate how to use Apache Flink for data transformation and application operations. I will then help you use these skills in a use case project. We will use Java and IntelliJ IDEA for building the course exercises. Please refer to other related Flink courses for capabilities like stream processing, SQL and machine learning. That being said, let's explore how to build batch processing pipelines with Apache Flink.
Batch mode engineering1m 16s
1. Apache Flink
2. Setting Up Flink
3. Dataset API
4. Advanced Capabilities
5. Use Case Project
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