| copy_to.src_sql | R Documentation | 
This is an implementation of the dplyr dplyr::copy_to() generic and it mostly
a wrapper around DBI::dbWriteTable().
It is useful for copying small amounts of data to a database for examples, experiments, and joins. By default, it creates temporary tables which are only visible within the current connection to the database.
## S3 method for class 'src_sql'
copy_to(
  dest,
  df,
  name = deparse(substitute(df)),
  overwrite = FALSE,
  types = NULL,
  temporary = TRUE,
  unique_indexes = NULL,
  indexes = NULL,
  analyze = TRUE,
  ...,
  in_transaction = TRUE
)
| dest | remote data source | 
| df | A local data frame, a  | 
| name | Name of new remote table. Use a string to create the table
in the current catalog/schema. Use  | 
| overwrite | If  | 
| types | a character vector giving variable types to use for the columns. See https://www.sqlite.org/datatype3.html for available types. | 
| temporary | if  | 
| unique_indexes | a list of character vectors. Each element of the list will create a new unique index over the specified column(s). Duplicate rows will result in failure. | 
| indexes | a list of character vectors. Each element of the list will create a new index. | 
| analyze | if  | 
| ... | other parameters passed to methods. | 
| in_transaction | Should the table creation be wrapped in a transaction? This typically makes things faster, but you may want to suppress if the database doesn't support transactions, or you're wrapping in a transaction higher up (and your database doesn't support nested transactions.) | 
Another tbl_lazy. Use dplyr::show_query() to see the generated
query, and use collect() to execute the query
and return data to R.
copy_inline() to use small data in an SQL query without actually
writing to a table.
library(dplyr, warn.conflicts = FALSE)
df <- data.frame(x = 1:5, y = letters[5:1])
db <- copy_to(src_memdb(), df)
db
df2 <- data.frame(y = c("a", "d"), fruit = c("apple", "date"))
# copy_to() is called automatically if you set copy = TRUE
# in the join functions
db %>% left_join(df2, copy = TRUE)
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