Replace a table with modified data and create a new snapshot

Replace a table with modified data and create a new snapshot

Usage

replace_table(.data, table_name, .quiet = TRUE)

Arguments

.data

A dplyr query object (tbl_lazy) with transformations

table_name

Table name to replace

.quiet

Logical, whether to suppress messages (default TRUE)

Value

Invisibly returns NULL

Details

This function is designed for schema changes or bulk transformations that should create a new versioned snapshot. It:

1. Collects the transformed data

2. Drops the existing table

3. Creates a new table with the updated schema/data

All operations happen within the current transaction context. Use begin_transaction() and commit_transaction() to ensure proper versioning.

When to use replace_table():

• Adding new columns - DuckLake UPDATE cannot add columns; use replace_table()

• Removing columns - Restructure schema with select()

• Complex transformations - Apply full dplyr pipelines naturally

When to use ducklake_exec() instead:

• Modifying existing column values only (no schema changes)

• Making targeted corrections to specific rows without rewriting the table

Both paths create a snapshot: replace_table() via DROP + CREATE, and ducklake_exec() via the in-place UPDATE/DELETE it runs, so either way the change is available for time travel.

See also

Other table operations: create_table(), ducklake_exec(), get_ducklake_table(), get_metadata_table(), show_ducklake_query()

Examples

if (FALSE) { # \dontrun{
# Add new derived columns with versioning
begin_transaction()
get_ducklake_table("adsl") |>
  mutate(
    AGE65FL = if_else(AGE >= 65, "Y", "N"),
    AGECAT = case_when(
      AGE < 65 ~ "<65",
      AGE >= 65 & AGE < 75 ~ "65-74",
      AGE >= 75 ~ ">=75"
    )
  ) |>
  replace_table("adsl")
commit_transaction()

# Remove columns and create new snapshot
begin_transaction()
get_ducklake_table("adsl") |>
  select(-AGE65FL, -AGECAT) |>
  replace_table("adsl")
commit_transaction()
} # }