## Not run:
# library(bigQueryR)
#
# ## Auth with a project that has at least BigQuery and Google Cloud Storage scope
# bqr_auth()
#
# ## make a big query
# job <- bqr_query_asynch("your_project",
# "your_dataset",
# "SELECT * FROM blah LIMIT 9999999",
# destinationTableId = "bigResultTable")
#
# ## poll the job to check its status
# ## its done when job$status$state == "DONE"
# bqr_get_job("your_project", job$jobReference$jobId)
#
# ##once done, the query results are in "bigResultTable"
# ## extract that table to GoogleCloudStorage:
# # Create a bucket at Google Cloud Storage at
# # https://console.cloud.google.com/storage/browser
#
# job_extract <- bqr_extract_data("your_project",
# "your_dataset",
# "bigResultTable",
# "your_cloud_storage_bucket_name")
#
# ## poll the extract job to check its status
# ## its done when job$status$state == "DONE"
# bqr_get_job("your_project", job_extract$jobReference$jobId)
#
# ## to download via a URL and not logging in via Google Cloud Storage interface:
# ## Use an email that is Google account enabled
# ## Requires scopes:
# ## https://www.googleapis.com/auth/devstorage.full_control
# ## https://www.googleapis.com/auth/cloud-platform
# ## set via options("bigQueryR.scopes") and reauthenticate if needed
#
# download_url <- bqr_grant_extract_access(job_extract, "your@email.com")
#
# ## download_url may be multiple if the data is > 1GB
#
# ## End(Not run)
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