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This article focuses on "the main functions of Apache Spark development", interested friends may wish to have a look. The method introduced in this paper is simple, fast and practical. Let's let the editor take you to learn the main functions of Apache Spark development.

1. You can link to SQL Server. This toolkit enables you to connect PySpark jobs and submit them to the SQL Server 2019 big data cluster.

2. Python editing. Develop PySpark applications with native Python authoring support, such as IntelliSense, automatic formatting, error checking, and so on.

3. Jupyter Notebook integration. Import and export .ipynb files.

4. PySpark interactive. Run selected lines of code, or run notebooks such as PySpark cells, and interactive visualization.

5. PySpark batch submits the PySpark application to the PySpark 2019 big data cluster.

6. PySpark surveillance. Integrate with Apache Spark History Server to view job history, debug, and diagnose Spark jobs.

At this point, I believe you have a deeper understanding of the "main functions of Apache Spark development". You might as well do it in practice. Here is the website, more related content can enter the relevant channels to inquire, follow us, continue to learn!

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