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)



project id or name


dataset name


billing project, if different to project


(IGNORED) maximum pages returned by a query


if (FALSE) { 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)) }