Some computing tools about feature tool and ml model.
Project description
Mega Spark说明
该项目旨在通过spark进行一站式数据分析与模型训练,保证最终落地的只有分析报告,可视化,以及模型训练评估结果,其次 该项目将pysaprk封装成mega对象来延续pandas的使用方法,进而实现在大数据场景下的使用pandas方法进行 数据分析和模型训练,消除相关同学在spark上投入的学习成本
目前提供以下模块:
mlmega_xgboost
sqlmegaframe
tomega
本地安装
如果要给该项目贡献代码,在本地调试好后测试,本地安装方法
$ git clone .
$ cd megaspark
$ python install .
在线安装
建议使用官方镜像,安装最新版本。
$ pip install mega-spark -i https://pypi.Python.org/simple/
使用教程
以tomega模块为例,安装完成之后,可以使用以下方法导入使用
import megaspark.tomega as mg
data_df = mg.read_csv("path/to/file.csv")
data_df.mega.head(5)
打包发布
$ cd /path/to/megaspark
$ python3 setup.py sdist bdist_wheel
$ pip3 install twine
$ python3 -m twine upload dist/*
注意事项
如果使用ml模块中的xgboost,需要在SPARK_HOME/jar中添加xgboost4j-0.72.jar以及xgboost4j-spark-0.72.jar
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