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assets
docs
.Renviron
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01-database-access.Rmd
02-dplyr-basics.Rmd
03-data-transformation.Rmd
04-visualizations.Rmd
05-modeling.Rmd
06-advanced-operations.Rmd
07-intro-to-sparklyr.Rmd
08-spark-pipelines.Rmd
09-dashboards.Rmd
10-drill-thru.Rmd
11-publish-work.Rmd
12-textmining.Rmd
README.md
bigdataclass2018.Rproj
config.yml
options.R
query-example.sql

README.md

Big Data class

Abstract

A two-day workshop. We will cover how to connect to and analyze data that exists outside of R. For databases, we will focus on the dplyr, DBI and odbc packages. For Big Data clusters, we will also learn how to use the sparklyr package to run models inside Spark and return the results to R. These packages enable us to use the same dplyr verbs inside R but are translated to SQL queries. We also will review recommendations for connection settings, security best practices and deployment options. Throughout the workshop, we will take advantage of RStudio’s professional tools such as RStudio Server Pro, the new professional data connectors, and RStudio Connect.

You should take this workshop if you want to learn how to use R with databases, such as SQL Server, Oracle, or PostgreSQL, and/or other scalable external data sources, such as Hadoop clusters with Hive and Spark.

Contents

  • Workbook R Notebooks - RMarkdown files at the top of the repository. They contain scaffold exercises for the students to practice during the class.

  • Full workbook - A version of the exercise chapters with all of the code completed is available under the book folder. They are available as html files created by the bookdown package.

  • Presentation deck - The PDF version of the deck that compliments the exercises. It is under assets/presentation_deck.