bqr_grant_extract_access | R Documentation |
To access the data created in bqr_extract_data. Requires the Google account email of the user.
bqr_grant_extract_access(extractJob, email)
extractJob |
An extract job from bqr_extract_data |
email |
email of the user to have access |
Uses cookie based auth.
URL(s) to download the extract that is accessible by email
Other BigQuery asynch query functions:
bqr_download_extract()
,
bqr_extract_data()
,
bqr_get_job()
,
bqr_query_asynch()
,
bqr_wait_for_job()
## 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(job$jobReference$jobId, "your_project")
##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(job_extract$jobReference$jobId, "your_project")
## 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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