googleCloudStorageR

Mark Edmondson

2019-07-28

An R library for interacting with the Google Cloud Storage JSON API (api docs).

Setup

Google Cloud Storage charges you for storage (prices here).

You can use your own Google Project with a credit card added to create buckets, where the charges will apply. This can be done in the Google API Console

Configuring your own Google Project

The instructions below are for when you visit the Google API console (https://console.developers.google.com/apis/)

Activate API

  1. Click on “APIs”
  2. Select and activate the Cloud Storage JSON API if not already active

Set environment variables

By default, all cloudyr packages look for the access key ID and secret access key in environment variables. You can also use this to specify a default bucket, and auto-authentication upon attaching the library. For example:

These can alternatively be set on the command line or via an Renviron.site or .Renviron file (https://cran.r-project.org/web/packages/httr/vignettes/api-packages.html).

e.g.

In your .Renviron:

GCS_AUTH_FILE="/fullpath/to/service-auth.json"
GCS_DEFAULT_BUCKET=my-default-bucket

Auto-authentication

The best method for authentication is to use your own Google Cloud Project. You can specify the location of a service account JSON file taken from your Google Project:

    Sys.setenv("GCS_AUTH_FILE" = "/fullpath/to/auth.json")

This file will then used for authentication via gcs_auth() when you load the library:

Setting a default Bucket

To avoid specifying the bucket in the functions below, you can set the name of your default bucket via environmental variables or via the function gcs_global_bucket(). See the Setting environment variables section for more details.

Downloading objects from Google Cloud storage

Once you have a Google project and created a bucket with an object in it, you can download it as below:

Uploading objects < 5MB

Objects can be uploaded via files saved to disk, or passed in directly if they are data frames or list type R objects. By default, data frames will be converted to CSV via write.csv(), lists to JSON via jsonlite::toJSON.

If you want to use other functions for transforming R objects, for example setting row.names = FALSE or using write.csv2, pass the function through object_function

## upload a file - type will be guessed from file extension or supply type  
write.csv(mtcars, file = filename)
gcs_upload(filename)

## upload an R data.frame directly - will be converted to csv via write.csv
gcs_upload(mtcars)

## upload an R list - will be converted to json via jsonlite::toJSON
gcs_upload(list(a = 1, b = 3, c = list(d = 2, e = 5)))

## upload an R data.frame directly, with a custom function
## function should have arguments 'input' and 'output'
## safest to supply type too
f <- function(input, output) write.csv(input, row.names = FALSE, file = output)

gcs_upload(mtcars, 
           object_function = f,
           type = "text/csv")

Upload metadata

You can pass metadata with an object via the function gcs_metadata_object().

the name you pass to the metadata object will override the name if it is also set elsewhere.

meta <- gcs_metadata_object("mtcars.csv",
                             metadata = list(custom1 = 2,
                                             custom_key = 'dfsdfsdfsfs))
                                             
gcs_upload(mtcars, object_metadata = meta)

Resumable uploads for files > 5MB up to 5TB

If the file/object is under 5MB, simple uploads are used.

For files > 5MB, resumable uploads are used. This allows you to upload up to 5TB.

If you get an interrupted connection when uploading, gcs_upload will retry 3 times, if it fails it will return a Retry object, that you can try again later from where the upload stopped. Call this via gcs_retry_upload

## write a big object to a file
big_file <- "big_filename.csv"
write.csv(big_object, file = big_file)

## attempt upload
upload_try <- gcs_upload(big_file)

## if successful, upload_try is an object metadata object
upload_try
==Google Cloud Storage Object==
Name:            "big_filename.csv" 
Size:            8.5 Gb 
Media URL        https://www.googleapis.com/download/storage/v1/b/xxxx 
Bucket:          your-bucket 
ID:              your-bucket/"test.pdf"/xxxx
MD5 Hash:        rshao1nxxxxxY68JZQ== 
Class:           STANDARD 
Created:         2016-08-12 17:33:05 
Updated:         2016-08-12 17:33:05 
Generation:      1471023185977000 
Meta Generation: 1 
eTag:            CKi90xxxxxEAE= 
crc32c:          j4i1sQ== 


## if unsuccessful after 3 retries, upload_try is a Retry object
==Google Cloud Storage Upload Retry Object==
File Location:     big_filename.csv
Retry Upload URL:  http://xxxx
Created:           2016-08-12 17:33:05 
Type:              csv
File Size:        8.5 Gb
Upload Byte:      4343
Upload remaining: 8.1 Gb

## you can retry to upload the remaining data using gcs_retry_upload()
try2 <- gcs_retry_upload(upload_try)

Updating user access to objects

You can change who can access objects via gcs_update_acl to one of READER or OWNER, on a user, group, domain, project or public for all users or authenticated users.

By default you are “OWNER” of all the objects and buckets you upload and create.

## update access of object to READER for all public
gcs_update_object_acl("your-object.csv", entity_type = "allUsers")

## update access of object for user joe@blogs.com to OWNER
gcs_update_acl("your-object.csv", 
               entity = "joe@blogs.com", 
               role = "OWNER")

## update access of object for googlegroup users to READER
gcs_update_object_acl("your-object.csv", 
                      entity = "my-group@googlegroups.com", 
                      entity_type = "group")

## update access of object for all users to OWNER on your Google Apps domain
gcs_update_object_acl("your-object.csv", 
                      entity = "yourdomain.com", 
                      entity_type = "domain", 
                      role = OWNER)

Deleting an object

Delete an object by passing its name (and bucket if not default)

## returns TRUE is successful, a 404 error if not found
gcs_delete_object("your-object.csv")

Viewing current access level to objects

Use gcs_get_object_acl() to see what the current access is for an entity + entity_type.

R Session helpers

Versions of save.image(), save() and load() are implemented called gcs_save_image(), gcs_save() and gcs_load(). These functions save and load the global R session to the cloud.

## save the current R session including all objects
gcs_save_image()

### wipe environment
rm(list = ls())

## load up environment again
gcs_load()

Save specific objects:

cc <- 3
d <- "test1"
gcs_save("cc","d", file = "gcs_save_test.RData")

## remove the objects saved in cloud from local environment
rm(cc,d)

## load them back in from GCS
gcs_load(file = "gcs_save_test.RData")
cc == 3
[1] TRUE
d == "test1"
[1] TRUE

You can also upload .R code files and source them directly using gcs_source:

## make a R source file and upload it
cat("x <- 'hello world!'\nx", file = "example.R")
gcs_upload("example.R", name = "example.R")

## source the file to run its code
gcs_source("example.R")

## the code from the upload file has run
x
[1] "hello world!"

Uploading via a Shiny app

The library is also compatible with Shiny authentication flows, so you can create Shiny apps that lets users log in and upload their own data.

An example of that is shown below:

library("shiny")
library("googleAuthR")
library("googleCloudStorageR")

## you need to start Shiny app on port 1221
## as thats what the default googleAuthR project expects for OAuth2 authentication

## options(shiny.port = 1221)
## print(source('shiny_test.R')$value) or push the "Run App" button in RStudio

shinyApp(
  ui = shinyUI(
      fluidPage(
        googleAuthR::googleAuthUI("login"),
        fileInput("picture", "picture"),
        textInput("filename", label = "Name on Google Cloud Storage",value = "myObject"),
        actionButton("submit", "submit"),
        textOutput("meta_file")
      )
  ),
  server = shinyServer(function(input, output, session){

    access_token <- shiny::callModule(googleAuth, "login")

    meta <- eventReactive(input$submit, {

      message("Uploading to Google Cloud Storage")
      
      # from googleCloudStorageR
      with_shiny(gcs_upload,  
                 file = input$picture$datapath,
                 # enter your bucket name here
                 bucket = "gogauth-test",  
                 type = input$picture$type,
                 name = input$filename,
                 shiny_access_token = access_token())

    })

    output$meta_file <- renderText({
      
      req(meta())

      str(meta())

      paste("Uploaded: ", meta()$name)

    })

  })
)

Bucket administration

There are various functions to manipulate Buckets:

Object administration

You can get meta data about an object by passing meta=TRUE to gcs_get_object

gcs_get_object("your-object", "your-bucket", meta = TRUE)

Explanation of Google Project access

googleCloudStorageR has its own Google project which is used to call the Google Cloud Storage API, but does not have access to the objects or buckets in your Google Project unless you give permission for the library to access your own buckets during the OAuth2 authentication process.

No other user, including the owner of the Google Cloud Storage API project has access unless you have given them access, but you may want to change to use your own Google Project (that could or could not be the same as the one that holds your buckets).