Spark-with-Python
Fundamentals of Spark with Python (using PySpark), code examples
파일 탐색기
최종 버전 다운로드 (.zip)- appl_stock.csv
- chinook.db
- chinook.zip
- ContainsNull.csv
- Moby-Dick.txt
- people.json
- sales_info.csv
- sqlite_latest.jar
- users.parquet
- Components.png
- RDD-1.png
- RDD_dependency_graph.PNG
- Readme.md
- Spark ecosystem.png
- SparkSQL-1.png
- customer_churn.csv
- dataset_Facebook.csv
- dog_food.csv
- Facebook_metrics.txt
- hack_data.csv
- Creating Fake Data.ipynb
- fake_customers.csv
- hello.csv
- new_customers.csv
- test.csv
- Python Crash Course Exercises - Solutions.ipynb
- Python Crash Course Exercises.ipynb
- Python Crash Course.ipynb
- Introduction to Spark Streaming.ipynb
- TweetRead.py
- Spark DataFrames Project Exercise - SOLUTIONS.ipynb
- Spark DataFrames Project Exercise.ipynb
- walmart_stock.csv
- appl_stock.csv
- ContainsNull.csv
- DataFrame_Basic_Operations.ipynb
- DataFrame_Basics.ipynb
- Dates_and_Timestamps.ipynb
- GroupBy_and_Aggregate_Functions.ipynb
- Missing_Data.ipynb
- people.json
- sales_info.csv
- Clustering Code Along.ipynb
- Clustering_Code_Example.ipynb
- Clustering_Consulting_Project.ipynb
- Clustering_Consulting_Project_SOLUTIONS.ipynb
- hack_data.csv
- sample_kmeans_data.txt
- seeds_dataset.csv
- seeds_dataset.txt
- cruise_ship_info.csv
- Data_Transformations.ipynb
- Ecommerce_Customers.csv
- fake_customers.csv
- Linear_Regression_Code_Along.ipynb
- Linear_Regression_Consulting_Project.ipynb
- Linear_Regression_Consulting_Project_SOLUTIONS.ipynb
- Linear_Regression_Example.ipynb
- sample_linear_regression_data.txt
- customer_churn.csv
- Logistic_Regression_Consulting_Project.ipynb
- Logistic_Regression_Consulting_Project_SOLUTIONS.ipynb
- Logistic_Regression_Example.ipynb
- new_customers.csv
- sample_libsvm_data.txt
- titanic.csv
- Titanic_Log_Regression_Code_Along.ipynb
- readme
- SMSSpamCollection
- NLP_Code_Along.ipynb
- Tools_for_NLP.ipynb
- Consulting Project - Recommender Systems.ipynb
- Meal_Info.csv
- movielens_ratings.csv
- Recommender_Code_Along.ipynb
- College.csv
- dog_food.csv
- sample_libsvm_data.txt
- Tree Methods Code Along.ipynb
- Tree_Methods_Consulting_Project.ipynb
- Tree_Methods_Consulting_Project_SOLUTION.ipynb
- Tree_Methods_Doc_Example.ipynb
- Course_Notes.zip
- README.md
- Readme.md
- Spark-with-Python.md
- .gitignore
- _config.yml
- Dataframe_introduction.ipynb
- DataFrame_operations_basics.ipynb
- Dataframe_SQL_query.ipynb
- GroupBy_aggregrate.ipynb
- Key-Value RDD basics.ipynb
- LICENSE
- notebook.tex
- Partioning and Gloming.ipynb
- RDD_Chaining_Execution.ipynb
- README.md
- Row_column_objects.ipynb
- SparkContext and RDD Basics.ipynb
- SparkContext_Workers_Lazy_Evaluations.ipynb
- Word_Count.ipynb
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/tirthajyoti/Spark-with-Python
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd Spark-with-Python
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. 공식 설치 스크립트
쉬움 추천사전 준비물
- APT (Debian/Ubuntu 계열) Debian/Ubuntu 계열 리눅스에 기본 내장된 패키지 매니저입니다.
sudo apt-get install oracle-java8-installer
APT 패키지 저장소에서 바로 설치합니다 (Debian/Ubuntu 계열).
sudo apt-get install oracle-java8-set-default
APT 패키지 저장소에서 바로 설치합니다 (Debian/Ubuntu 계열).
설치 후 새 터미널을 열고, 프로그램의 버전 확인 명령(예: --version)으로 정상 설치됐는지 확인하세요.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
// repository documentation
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