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Repository of sample Databricks notebooks

Home Page: https://databricks.com/resources/selected-notebooks#databricks-jump-start

Python 1.21% HTML 96.96% Jupyter Notebook 0.72% Scala 1.02% R 0.08%

databricks's Introduction

Databricks Jump Start Sample Notebooks

This repository contains sample Databricks notebooks found within the Databricks Selected Notebooks Jump Start and other miscellaneous locations.

The notebooks were created using Databricks in Python, Scala, SQL, and R; the vast majority of them can be run on Databricks Community Edition (sign up for free access via the link).

Highlights

###On-Time Flight Performance On-Time Flight Performance with GraphFrames for Apache Spark: Provides a jump start into Graph using GraphFrames for Apache Spark on flight departure performance data.

On-Time Flight Performance D3 Visualization

ADAM Genomic Analysis

ADAM Genomic Analysis using K-Means Clustering: Applying k-means clustering to predict population sample location based on genomic sequences using ADAM.

ADAM Genomic Sequence K-means Clustering Confusion Matrix

Streaming Meetup RSVPs

Streaming Meetup RSVPs is a series of notebooks showcasing how streaming on Databricks including the use of DataFrames and mapWithState.

Available Notebooks

  • adam: Genomic Sequencing using Apache Spark and ADAM

  • blog books: Notebooks to support the Databricks blog ebooks.

  • content: Various notebooks including

    • Data Exploration on Databricks
    • Salesforce Leads with Machine Learning, Spark SQL, and UDFs
    • Streaming Meetup RSVPs
  • demo: Various notebooks including

    • OR Block Scheduling using Linear Regression
    • Mobile Sample SQL Notebook
    • Population vs. Price Linear Regression and SQL notebooks
    • Spark 1.6 Notebooks (describing the various enhancements for Spark 1.6)
  • dogfood: Various notebooks including

    • AdTech Sample Notebook
    • Quick Start using Python | Scala
  • examples: Example notebooks in various stages of completion including Iris dataset k-means vs. bisecting k-means

  • flights: Various notebooks working with on-time flight performance

  • reporting: Example reporting notebooks including dashboard views

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