Our style guide for writing readable and maintainable PySpark code.
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Updated
Dec 21, 2021
Our style guide for writing readable and maintainable PySpark code.
This repository contains the Notes for Pyspark
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Repositorio para realizar el curso en Udemy llamado "Airflow2.0 De 0 a Héroe", de la academia "Datapath".
Batch Processing using Apache Spark and Python for data exploration
Objective: Perform word count tasks and joins using spark SQL within a Docker container
This notebook contains the usage of Pyspark to build machine learning classifiers (note that almost ml_algorithm supported by Pyspark are used in this notebook)
twitter real-time sentiment analysis
Project based on application of azure databricks
PySpark House Price Prediction features a PySpark-based Linear Regression model for predicting median house prices. It showcases data preprocessing, model training, and evaluation, yielding an RMSE of around 0.11. The code offers insights into building robust predictive models using PySpark.
Problems on Hadoop-MapReduce, Hive and PySparkSQL
Inventory value is also important for determining a company's liquidity, or its ability to meet its short-term financial obligations. A high inventory value can indicate that a company has too much money tied up in inventory, which could make it difficult for the company to pay its bills.
Big data management with PySpark
Worked on Pyspark file streaming
Utilizing Apache Spark & PySpark to analyze a movie dataset. Tasks include data exploration, identifying top-rated movies, training a linear regression model, and experimenting with Airflow.
This is a Big Data project using AWS, pyspark-sql, pyspark and Google Collaboratory to determine if there is any bias in the reviews of vine and non-vine reviewers on Amazon.
Data analysis project with Pyspark on Jupyter Notebook
This notebook performs EDA over a movie ratings dataset via pyspark sql.
This script builds a linear regression model using PySpark to predict student admissions at Unicorn University.
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