This repository contains the source of the Big Data Analytics book, as well as supplementary online resources. The book is built using bookdown.
The R_code_examples folder contains R-scripts with all code examples and tutorials shown in the book.
The corresponding sections in the book contain typically contain detailed instructions of where and how the datasets used in the code examples can be downloaded from the original sources.
To ensure data availability for the code examples and tutorials in the long run, you find (smaller scale) versions for all key datasets discussed in the book in this S3-bucket:
https://bda-examples.s3.eu-central-1.amazonaws.com/air_final.sqlite
https://bda-examples.s3.eu-central-1.amazonaws.com/airline_id.csv
https://bda-examples.s3.eu-central-1.amazonaws.com/airports.csv
https://bda-examples.s3.eu-central-1.amazonaws.com/carriers.csv
https://bda-examples.s3.eu-central-1.amazonaws.com/data_for_tables.dta
https://bda-examples.s3.eu-central-1.amazonaws.com/economics.csv
https://bda-examples.s3.eu-central-1.amazonaws.com/flights_sep_oct15.txt
https://bda-examples.s3.eu-central-1.amazonaws.com/flights.csv
https://bda-examples.s3.eu-central-1.amazonaws.com/ga.csv
https://bda-examples.s3.eu-central-1.amazonaws.com/inflation.csv
https://bda-examples.s3.eu-central-1.amazonaws.com/marketing_data.csv
https://bda-examples.s3.eu-central-1.amazonaws.com/mydb.sqlite
https://bda-examples.s3.eu-central-1.amazonaws.com/tlc_trips.csv
Note that the AWS bucket is configured such that the requester pays for requests and transfer costs.
Here you find additional resources and hints regarding the installation of some of the tools used in the book.
gpuR: The package is not anymore available viainstall.packages(). However, you can install it withdevtools::install_github("cdeterman/gpuR"). For additional installation instructions (in particular regarding dependencies), see the wiki here: https://github.com/cdeterman/gpuR/wiki.- Install Apache Spark via
sparklyr: https://spark.rstudio.com/get-started/ - Install Tensorflow and Keras via the
tensorflowandkeraspackages (from within R): https://tensorflow.rstudio.com/install/