[ DevCourseWeb.com ] PySpark Cookbook - Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python (Packt)

Creation Time	Feb. 16, 2025, 3:32 a.m.
Last Access Time	Oct. 12, 2025, 9:40 a.m.
File Size	102.8 MB
Keywords	and 60 Python Packt for PySpark analytics big Over processing - data DevCourseWeb implementing Apache using Spark Cookbook com recipes
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~Get Your Files Here !/PySpark-Cookbook-master/Data/forest_coverage_type.csv 71.7 MB
~Get Your Files Here !/PySparkCookbook.pdf 11.1 MB
~Get Your Files Here !/PySparkCookbook.epub 9.9 MB
~Get Your Files Here !/PySpark-Cookbook-master/Data/census_income.csv 3.6 MB
~Get Your Files Here !/PySpark-Cookbook-master/Chapter08/GraphFrames - Graph Theory with PySpark.html 1.8 MB
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~Get Your Files Here !/PySpark-Cookbook-master/Chapter03/3. Abstracting data with DataFrames.ipynb 53.9 KB
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~Get Your Files Here !/PySpark-Cookbook-master/Data/fourier_signal.csv 4.8 KB
~Get Your Files Here !/PySpark-Cookbook-master/README.md 4.7 KB
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~Get Your Files Here !/PySpark-Cookbook-master/Chapter07/stateful_streaming_word_count.py 1.6 KB
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~Get Your Files Here !/PySpark-Cookbook-master/Chapter03/metastore_db/service.properties 985 bytes
~Get Your Files Here !/PySpark-Cookbook-master/Chapter03/metastore_db/README_DO_NOT_TOUCH_FILES.txt 608 bytes
~Get Your Files Here !/PySpark-Cookbook-master/Data/DataFrames_sample.json 563 bytes
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~Get Your Files Here !/PySpark-Cookbook-master/Chapter03/metastore_db/log/README_DO_NOT_TOUCH_FILES.txt 532 bytes
~Get Your Files Here !/Bonus Resources.txt 386 bytes
~Get Your Files Here !/PySpark-Cookbook-master/Data/DataFrames_sample.csv 286 bytes
Get Bonus Downloads Here.url 182 bytes
~Get Your Files Here !/PySpark-Cookbook-master/Chapter01/hosts.txt 98 bytes
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~Get Your Files Here !/PySpark-Cookbook-master/Chapter03/metastore_db/db.lck 38 bytes
~Get Your Files Here !/PySpark-Cookbook-master/Chapter03/metastore_db/dbex.lck 4 bytes

[ DevCourseWeb.com ] PySpark Cookbook - Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python (Packt)

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