Insert rows into a DuckLake table

A wrapper around dplyr::rows_insert() with in_place = TRUE as the default, since DuckLake is designed for in-place modifications.

Usage

rows_insert(
  x,
  y,
  by = NULL,
  copy = TRUE,
  in_place = TRUE,
  conflict = "ignore",
  ...
)

Arguments

x: Target table (from get_ducklake_table())
y: Data frame with new rows
by: Column(s) to match on (for conflict detection)
copy: Whether to copy y to the same source as x (default TRUE)
in_place: Whether to modify the table in place (default TRUE for DuckLake)
conflict: How to handle conflicts (default "ignore")
...: Additional arguments passed to dplyr::rows_insert()

Value

The updated table

Details

When to use `rows_*()` vs `replace_table()`

Use the rows_*() functions for targeted, incremental changes: appending a batch of new records, correcting a handful of values, or removing specific rows. Each call is a single SQL statement against the existing table – no data leaves the database, and with data inlining enabled (DuckLake's default) small changes land in the catalog without creating tiny Parquet files.

Use replace_table() for structural or bulk changes: adding or removing columns, or transformations that touch most rows. It collects the transformed data into R and rewrites the table, which is simpler for schema changes but heavier for small edits.

Examples

if (FALSE) { # \dontrun{
rows_insert(
  get_ducklake_table("my_table"),
  data.frame(id = 99, value = "new row"),
  by = "id"
)
} # }