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Update rows in a DuckLake table

Source: R/rows_operations.R
rows_update.Rd

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

Usage

rows_update(
  x,
  y,
  by = NULL,
  copy = TRUE,
  in_place = TRUE,
  unmatched = "ignore",
  ...
)

Arguments

x

Target table (from get_ducklake_table())

y

Data frame with updates

by

Column(s) to match on

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)

unmatched

How to handle unmatched rows (default "ignore")

...

Additional arguments passed to dplyr::rows_update()

Value

The updated table

Details

Choosing how to change a 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.

See also

Other row operations: merge_into(), rows_delete(), rows_insert(), rows_upsert()

Examples

if (FALSE) { # \dontrun{
# Update rows - in_place = TRUE by default
rows_update(
  get_ducklake_table("my_table"),
  data.frame(id = 1, value = "new"),
  by = "id"
)
} # }