【开源之夏】基于openEuler构建大数据体验平台-Update Spark Version to 3.3.0

**项目标题：基于openEuler构建大数据体验平台-Update Spark Version to 3.3.0** 
【项目难度】：进阶
【项目描述】：基于openEuler构建一站式大数据体验平台,可以对接Spark、Flink等大数据平台。Apache Spark是一种多语言引擎，用于在单节点机器或集群上执行数据工程、数据科学和机器学习。通过构建大数据体验平台发现并完善openEuler在大数据场景的不足，打造基于openEuler的大数据开源解决方案的雏形。此Issues为部分内容。详情见：https://summer-ospp.ac.cn/#/org/prodetail/22b970113
【产出标准】：
1、**引入基于openEuler22.03的Spark3.3.0的容器镜像。** 
2、对不满足条件的操作系统软件包进行升级和添加，并上传至：https://gitee.com/src-openeuler。
【技术要求】：	
1、掌握java/scala编程语言。对Dockerfile熟悉的同学优先。
2、熟练使用Linux。
3、对容器化有一定了解。使用（了解）过Spark、Flink、Kyuubi的同学优先。
【导师姓名/导师邮箱】：yikunkero/yikunkero@gmail.com
【成果提交仓库】：
https://gitee.com/src-openeuler/spark
https://gitee.com/src-openeuler
【相关参考资料】：https://spark.apache.org

**project name：Building Bigdata Experience Platform Based on Openeuler-Update Spark Version to 3.3.0**  
【Difficulty】：Advanced
【Description】：Build a one-stop big data experience platform based on openeuler, which can connect with spark, Flink and other big data platforms. Apache spark is a multilingual engine for performing data engineering, data science, and machine learning on single node machines or clusters. Discover and improve the deficiencies of openeuler in big data scenarios by building a big data experience platform, and create the prototype of big data open source solutions based on openeuler.This issues is part of the project.Full details: https://summer-ospp.ac.cn/#/org/prodetail/22b970113
【Output Requirements】：
1、Establish the docker image of spark3.3.0 based on openeuler22.03.
2、Upgrade and add the operating system software package that does not meet the conditions, and upload it to: https://gitee.com/src-openeuler.
【Technical Requirements】：
1. Master Java/Scala and be familiar with dockerfile.
2. Proficient in Linux.
3. Have a certain understanding of containerization. Students who have used (learned) spark, Flink and Kyuubi are preferred.
【Mentor/Email】：yikunkero/yikunkero@gmail.com
【Project Repository】：
https://gitee.com/src-openeuler/spark
https://gitee.com/src-openeuler
【Notes】：https://spark.apache.org

src-openEuler/spark

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