Understanding Flink DataSetAPI and DataStreamAPI
This article introduces Apache Flink's DataSetAPI and DataStreamAPI, explains their source, transformation, and sink concepts, highlights the key differences in transformation handling, and notes the series' goal of publishing over 500 big‑data tutorials for learners from beginner to expert.
Introduction: This lesson covers two key APIs in Apache Flink’s programming model – DataSetAPI and DataStreamAPI – and briefly mentions the concept of window broadcasting, which will be detailed in later chapters.
This section is about Flink’s programming model APIs.
1. DataSetAPI
Source: Creation of an initial dataset from data sources such as files or Java collections.
Transformation: Converting one or more DataSets into new DataSets.
Sink: Storing or returning the computation results.
2. DataStreamAPI
DataStream operators transform one or more DataStreams into new DataStreams, allowing the composition of complex data‑flow topologies.
The main difference between DataStreamAPI and DataSetAPI lies in the transformation stage.
The series plans to publish more than 500 articles, with over 100 already released.
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Big Data Technology & Architecture
Wang Zhiwu, a big data expert, dedicated to sharing big data technology.
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