gbifdb (version 1.0.0)

gbif_remote: gbif remote

Description

Connect to GBIF remote directly. Can be much faster than downloading for one-off use or when using the package from a server in the same region as the data. See Details.

Usage

gbif_remote(
  version = gbif_version(),
  bucket = gbif_default_bucket(),
  safe = TRUE,
  unset_aws = getOption("gbif_unset_aws", TRUE),
  endpoint_override = Sys.getenv("AWS_S3_ENDPOINT", "s3.amazonaws.com"),
  backend = c("arrow", "duckdb"),
  ...
)

Value

a remote tibble tbl_sql class object.

Arguments

version

GBIF snapshot date

bucket

GBIF bucket name (including region). A default can also be set using the option gbif_default_bucket, see options.

safe

logical, default TRUE. Should we exclude columns mediatype and issue? varchar datatype on these columns substantially slows downs queries.

unset_aws

Unset AWS credentials? GBIF is provided in a public bucket, so credentials are not needed, but having a AWS_ACCESS_KEY_ID or other AWS environmental variables set can cause the connection to fail. By default, this will unset any set environmental variables for the duration of the R session. This behavior can also be turned off globally by setting the option gbif_unset_aws to FALSE (e.g. to use an alternative network endpoint)

endpoint_override

optional parameter to arrow::s3_bucket()

backend

duckdb or arrow

...

additional parameters passed to the arrow::s3_bucket()

Details

Query performance is dramatically improved in queries that return only a subset of columns. Consider using explicit select() commands to return only the columns you need.

A summary of this GBIF data, along with column meanings can be found at https://github.com/gbif/occurrence/blob/master/aws-public-data.md

Examples

if (FALSE) { # interactive()

gbif <- gbif_remote()
gbif()
}