2026数据科学与大数据技术一套基于SparkSQL的北京市人力资源数据分析与可视化3.04-AI11.92(论文+程序代码源码+运行指导txt)定稿.zip

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大小 15.08 MB
共368文件
2026-09-18
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2205034305_程欣娜_数据科学与大数据技术专业_基于SparkSQL的北京市人力资源数据分析与可视化
- bdu26bd305chengxinnaSparkSQLProject
  - bdu26bd305chengxinna.idea
    - bdu26bd305chengxinnainspectionProfiles
      - profiles_settings.xml(174 B)
    - .gitignore(109 B)
    - misc.xml(367 B)
    - modules.xml(289 B)
    - SparkSQLProject.iml(575 B)
    - workspace.xml(9.41 KB)
  - bdu26bd305chengxinna.vscode
    - settings.json(4 B)
  - bdu26bd305chengxinnaanalyzer
    - bdu26bd305chengxinnaqueries
      - bdu26bd305chengxinna__pycache__
        education_salary.cpython-313.pyc(2.13 KB)
        employment_potential.cpython-313.pyc(2 KB)
        enterprise_type.cpython-313.pyc(1.75 KB)
        region_industry.cpython-313.pyc(2.74 KB)
        top_industries.cpython-313.pyc(2.81 KB)
        yearly_trend.cpython-313.pyc(1.98 KB)
        __init__.cpython-313.pyc(243 B)
      - education_salary305chengxinna.py(1.74 KB)
      - employment_potential305chengxinna.py(1.55 KB)
      - enterprise_type305chengxinna.py(1.42 KB)
      - region_industry305chengxinna.py(2.14 KB)
      - top_industries305chengxinna.py(2.17 KB)
      - yearly_trend305chengxinna.py(1.57 KB)
      - __init__.py(100 B)
    - bdu26bd305chengxinna__pycache__
      - json_uploader.cpython-313.pyc(11.04 KB)
      - result_serializer.cpython-313.pyc(10.17 KB)
      - schemas.cpython-313.pyc(1.92 KB)
      - schemas305chengxinna.cpython-313.pyc(1.96 KB)
      - spark_session.cpython-313.pyc(1.73 KB)
      - __init__.cpython-313.pyc(277 B)
    - json_uploader305chengxinna.py(11.37 KB)
    - json_uploader_pyarrow_backup305chengxinna.py(8.22 KB)
    - json_uploader_webhdfs305chengxinna.py(11.35 KB)
    - README_JSON_UPLOADER.md(5.86 KB)
    - result_serializer305chengxinna.py(8.02 KB)
    - schemas305chengxinna.py(3.12 KB)
    - spark_session305chengxinna.py(1.38 KB)
    - __init__.py(103 B)
  - bdu26bd305chengxinnacommon
    - bdu26bd305chengxinna__pycache__
      - logger.cpython-313.pyc(4.16 KB)
      - logger305chengxinna.cpython-313.pyc(4.21 KB)
      - __init__.cpython-313.pyc(247 B)
    - logger305chengxinna.py(3.67 KB)
    - __init__.py(75 B)
  - bdu26bd305chengxinnaconfig
    - bdu26bd305chengxinna__pycache__
      - settings.cpython-313.pyc(4.44 KB)
      - settings305chengxinna.cpython-313.pyc(4.48 KB)
      - __init__.cpython-313.pyc(217 B)
    - settings305chengxinna.py(7.36 KB)
    - __init__.py(45 B)
  - bdu26bd305chengxinnacrawler
    - bdu26bd305chengxinnaparsers
      - bdu26bd305chengxinna__pycache__
        html_parser.cpython-313.pyc(6.79 KB)
        html_parser305chengxinna.cpython-313.pyc(7 KB)
        pdf_parser.cpython-313.pyc(5.45 KB)
        pdf_parser305chengxinna.cpython-313.pyc(5.62 KB)
        __init__.cpython-313.pyc(297 B)
      - dynamic_parser305chengxinna.py(3 KB)
      - html_parser305chengxinna.py(5.3 KB)
      - pdf_parser305chengxinna.py(3.93 KB)
      - __init__.py(103 B)
    - bdu26bd305chengxinna__pycache__
      - compliance.cpython-313.pyc(7.14 KB)
      - compliance305chengxinna.cpython-313.pyc(7.19 KB)
      - spider.cpython-313.pyc(12.35 KB)
      - spider305chengxinna.cpython-313.pyc(12.46 KB)
      - storage.cpython-313.pyc(3.08 KB)
      - storage305chengxinna.cpython-313.pyc(3.25 KB)
      - __init__.cpython-313.pyc(286 B)
    - compliance305chengxinna.py(6.03 KB)
    - spider305chengxinna.py(10.14 KB)
    - storage305chengxinna.py(2.32 KB)
    - __init__.py(113 B)
  - bdu26bd305chengxinnadata
    - bdu26bd305chengxinnaanalysis
      - cluster_result.json(5.82 MB)
    - bdu26bd305chengxinnacsv_archive
      - .gitkeep(0 B)
      - beijing_hr_data_20260408_175528.csv(32.59 KB)
      - hr_sample_data_20260210.csv(3.92 MB)
    - bdu26bd305chengxinnaerror_records
      - .gitkeep(0 B)
    - bdu26bd305chengxinnafigures
      - wcss_elbow.png(161.39 KB)预览内容
    - bdu26bd305chengxinnahdfs_storage
      - hr_data.parquet(706.76 KB)
    - bdu26bd305chengxinnajson_results
      - .gitkeep(0 B)
      - education_salary.json(3.62 KB)
      - employment_potential.json(1.52 KB)
      - enterprise_type.json(710 B)
      - region_industry.json(41.49 KB)
      - top_industries.json(2.78 KB)
      - yearly_trend.json(1.16 KB)
    - bdu26bd305chengxinnalogs
      - .gitkeep(0 B)
      - analyzer.log(14.31 KB)
      - analyzer_error.log(3.36 KB)
      - crawler.log(9.19 KB)
      - crawler305chengxinna.log(1.88 KB)
      - crawler_error.log(0 B)
      - predictor.log(10.29 KB)
      - predictor305chengxinna.log(108.59 KB)
      - predictor_error.log(299 B)
      - preprocessor.log(30.27 KB)
      - preprocessor305chengxinna.log(410 B)
      - preprocessor_error.log(0 B)
      - visualizer.log(23.75 KB)
      - visualizer305chengxinna.log(149.09 KB)
      - visualizer_error.log(8.65 KB)
    - bdu26bd305chengxinnamodels
      - .gitkeep(0 B)
      - cluster_model_20260419_031620.joblib(162.38 KB)
      - cluster_model_20260419_031620_meta.json(526 B)
      - cluster_model_20260419_034412.joblib(162.38 KB)
      - cluster_model_20260419_034412_meta.json(526 B)
      - cluster_model_20260419_035024.joblib(162.38 KB)
      - cluster_model_20260419_035024_meta.json(526 B)
      - cluster_model_20260419_035809.joblib(162.38 KB)
      - cluster_model_20260419_035809_meta.json(526 B)
      - cluster_model_20260419_041522.joblib(201.45 KB)
      - cluster_model_20260419_041522_meta.json(348 B)
      - cluster_model_20260419_041818.joblib(201.45 KB)
      - cluster_model_20260419_041818_meta.json(348 B)
      - cluster_model_20260419_044359.joblib(201.45 KB)
      - cluster_model_20260419_044359_meta.json(348 B)
      - cluster_model_20260419_044958.joblib(201.45 KB)
      - cluster_model_20260419_044958_meta.json(348 B)
      - cluster_model_20260419_053204.joblib(198.54 KB)
      - cluster_model_20260419_053204_meta.json(348 B)
      - cluster_model_20260419_053952.joblib(198.54 KB)
      - cluster_model_20260419_053952_meta.json(348 B)
      - cluster_model_20260419_054018.joblib(198.54 KB)
      - cluster_model_20260419_054018_meta.json(348 B)
      - cluster_model_20260419_065143.joblib(198.54 KB)
      - cluster_model_20260419_065143_meta.json(348 B)
      - cluster_model_20260419_070059.joblib(2.64 KB)
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      - cluster_model_20260419_072006.joblib(2.64 KB)
      - cluster_model_20260419_072006_meta.json(429 B)
      - cluster_model_20260419_072728.joblib(2.64 KB)
      - cluster_model_20260419_072728_meta.json(429 B)
      - cluster_model_20260419_072957.joblib(2.64 KB)
      - cluster_model_20260419_072957_meta.json(429 B)
      - cluster_model_20260419_073257.joblib(198.54 KB)
      - cluster_model_20260419_073257_meta.json(348 B)
      - cluster_model_20260422_201100.joblib(198.6 KB)
      - cluster_model_20260422_201100_meta.json(348 B)
      - cluster_model_20260422_201733.joblib(198.6 KB)
      - cluster_model_20260422_201733_meta.json(348 B)
      - risk_model_20260210_224449.joblib(4.33 MB)
      - risk_model_20260210_224449_meta.json(566 B)
      - risk_model_20260210_230845.joblib(4.33 MB)
      - risk_model_20260210_230845_encoders.joblib(1.1 KB)
      - risk_model_20260210_230845_meta.json(566 B)
      - risk_model_20260408_162808.joblib(4.33 MB)
      - risk_model_20260408_162808_encoders.joblib(1.1 KB)
      - risk_model_20260408_162808_meta.json(566 B)
      - risk_model_20260408_163516.joblib(7.3 KB)
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      - risk_model_20260419_023629.joblib(208.42 KB)
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      - risk_model_20260419_024227.joblib(758.71 KB)
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      - risk_model_20260419_024339.joblib(758.68 KB)
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      - salary_model_20260210_224448.joblib(921 B)
      - salary_model_20260210_224448_meta.json(475 B)
      - salary_model_20260210_230845.joblib(921 B)
      - salary_model_20260210_230845_encoders.joblib(1.66 KB)
      - salary_model_20260210_230845_meta.json(475 B)
      - salary_model_20260408_162807.joblib(142.42 KB)
      - salary_model_20260408_162807_meta.json(1.01 KB)
      - salary_model_20260408_163516.joblib(142.42 KB)
      - salary_model_20260408_163516_meta.json(1.01 KB)
      - salary_model_20260419_022433.joblib(142.42 KB)
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  - bdu26bd305chengxinnapredictor
    - bdu26bd305chengxinna__pycache__
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    - cluster_model305chengxinna.py(5.07 KB)
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  - bdu26bd305chengxinnapreprocessor
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    - __init__.py(126 B)
  - bdu26bd305chengxinnascripts
    - crawl_beijing_hr_to_csv305chengxinna.py(29.79 KB)
    - generate_sample_data305chengxinna.py(4.2 KB)
  - bdu26bd305chengxinnatests
    - bdu26bd305chengxinna__pycache__
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    - test_json_uploader305chengxinna.py(11.23 KB)
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  - bdu26bd305chengxinnavisualizer
    - bdu26bd305chengxinnaapi
      - bdu26bd305chengxinna__pycache__
        cluster305chengxinna.cpython-313.pyc(4.38 KB)
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2026数据科学与大数据技术一套基于SparkSQL的北京市人力资源数据分析与可视化3.04-AI11.92(论文+程序代码源码+运行指导txt)定稿.zip