Create the connection to the database with DBI::dbConnect() then use dplyr::tbl() to connect to tables within that database. Generally, it's best to provide the fully qualified name of the table (i.e. project.dataset.table) but if you supply a default dataset in the connection, you can use just the table name. (This, however, will prevent you from making joins across datasets.)

src_bigquery(project, dataset, billing = project, max_pages = 10)

## Arguments

project project id or name dataset name billing project, if different to project (IGNORED) maximum pages returned by a query

## Examples

# NOT RUN {
library(dplyr)

# To run this example, replace billing with the id of one of your projects
# set up for billing
con <- DBI::dbConnect(bigquery(), project = bq_test_project())

shakespeare <- con %>% tbl("publicdata.samples.shakespeare")
shakespeare
shakespeare %>%
group_by(word) %>%
summarise(n = sum(word_count, na.rm = TRUE)) %>%
arrange(desc(n))
# }