Pyspark serves as a Python interface to Apache Spark, enabling the execution of Python and SQL-like instructions for the manipulation and analysis of data within a distributed processing framework.
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Updated
Dec 12, 2023 - Jupyter Notebook
Pyspark serves as a Python interface to Apache Spark, enabling the execution of Python and SQL-like instructions for the manipulation and analysis of data within a distributed processing framework.
This repo contains my learnings and practices Zepplin notebooks on Spark using Scala. All the notebooks in the repo can be used as template code for most of the ML algorithms and can be built upon it for more complex problems.
Assignments in R programming (data analysis, clustering) and Spark within Big Data Programming course in my master's program.
Explains the implementation of spark concepts using pyspark API from jupyter notebook
This is our final project for SFU's CMPT 353 taught by Greg Baker during Summer 2023
Treat Spark like pandas.
Big Data - Split a large CSV file into N smaller ones and save them into the local disk
Implementation of Hadoop and Spark
This series explores the basics of Apache Spark with the application of some practical elements of Spark, PySpark & SparkSQL
Predict the success of Kickstarter campaigns using machine learning. Analyze project data including financial goals, pledge amounts, categories, and outcomes. Perform data cleaning, queries, visualizations, and build models to forecast campaign success, helping entrepreneurs optimize their funding strategies
BCG GAMMA CASE STUDY
This repository contains the implementation of a wide variety of BigData Projects in different applications of NoSQL databases, Spark, Data Pipelines, and map-reduce. These projects include university projects and projects implemented due to interest in BigData.
This Repo contains analysis of large data using Spark
Spark BigQuery Parallel
A collection of small projects exploring PySpark features and functionality including packages and modules, algorithms, and general data science techniques.
Use this project to join data from multiple csv files. Currently in this project we support one to one and one to many join. Along with this you can find how to use kafka producer efficiently with spark.
UMSI-Bosch Manufacturing Line Failure Analysis
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