The main data analysis plug-ins used by JD are as follows:

1. JD Big Data Platform: JD's self-developed big data analysis platform provides massive data storage and processing capabilities, supporting real-time data analysis and offline data mining.

2. Hadoop: Hadoop is an open source distributed storage and computing framework. JD uses Hadoop to store and process large-scale data to achieve data analysis and mining.

3. Hive: Hive is a data warehouse tool based on Hadoop. It can map structured data to Hadoop's file system and provide a query language similar to SQL to facilitate data analysts to query and analyze data.

4. Spark: Spark is a fast and general big data processing engine. JD uses Spark to process and analyze large-scale data. It has efficient memory computing capabilities and supports multiple data sources.

5. Tableau: Tableau is a data visualization tool that can display data in the form of charts. JD uses Tableau to perform data visualization analysis to help decision makers better understand and use data.

6. Python and R: JD.com also uses Python and R, two commonly used data analysis programming languages, and uses their rich data analysis libraries and tools for data processing, modeling, and visual analysis.

The above are JD.com's commonly used data analysis plug-ins. Through these tools and platforms, JD.com can effectively mine and analyze massive amounts of data and provide strong support for corporate decision-making.