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",
  ...
)

The updated table

To look up or combine data for analysis, use dplyr joins (left_join() and friends). Joins read from the lake and build a new result; they never modify a lake table.
To append, correct, or remove specific rows, use rows_insert(), rows_update(), or rows_delete(). 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.
To update rows that exist and insert the ones that don't in one atomic statement, use rows_upsert().
For conditional merge logic or deletes driven by a staging table, use merge_into().
To change a table's shape without touching its data – add, drop, or rename columns, widen a type – use the schema evolution family (add_table_column() and friends): metadata-only changes that rewrite nothing.
For bulk transformations that touch most rows, use replace_table(). It collects the transformed data into R and rewrites the whole table – heavier than the row operations, and it resets the row lineage that the in-place operations preserve in the change feed.

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