Sparkitecture
  • Welcome to Sparkitecture!
  • Cloud Service Integration
    • Azure Storage
    • Azure SQL Data Warehouse / Synapse
    • Azure Data Factory
  • Data Preparation
    • Reading and Writing Data
    • Shaping Data with Pipelines
    • Other Common Tasks
  • Machine Learning
    • About Spark MLlib
    • Classification
      • Logistic Regression
      • Naïve Bayes
      • Decision Tree
      • Random Forest
      • Gradient-Boosted Trees
    • Regression
      • Linear Regression
      • Decision Tree
      • Random Forest
      • Gradient-Boosted Trees
    • MLflow
    • Feature Importance
    • Model Saving and Loading
    • Model Evaluation
  • Streaming Data
    • Structured Streaming
  • Operationalization
    • API Serving
    • Batch Scoring
  • Natural Language Processing
    • Text Data Preparation
    • Model Evaluation
  • Bioinformatics and Genomics
    • Glow
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Welcome to Sparkitecture!

NextAzure Storage

Last updated 5 years ago

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Created by: Colby T. Ford, Ph.D.

PySpark Edition | A work in progress... | Created using GitBook.com

About

Sparkitecture is a collection of “cookbook-style” scripts for simplifying data engineering and machine learning in Apache Spark.

This is an open source project (GPL v3.0) for the Spark community. If you have ideas or contributions you'd like to add, submit a Feature Request or a write your code/tutorial/page and create a Pull Request in the GitHub repo.

How to Cite

BibTex

Text Citation

@misc{sparkitecture,

author = {Colby T. Ford},

title = {Sparkitecture - {A} collection of "cookbook-style" scripts for simplifying data engineering and machine learning in {Apache Spark}.},

month = oct,

year = 2019,

doi = {10.5281/zenodo.3468502},

url = {https://doi.org/10.5281/zenodo.3468502}

}

Colby T. Ford. (2019, October) Sparkitecture - A collection of "cookbook-style" scripts for simplifying data engineering and machine learning in Apache Spark., (Version v1.0.0). Zenodo.

http://doi.org/10.5281/zenodo.3468502
DOI