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Set partitioning keys for a table

Source: R/partitioning.R
set_table_partitioning.Rd

Declares how newly written data files for a table should be split up. Partitioning lets DuckLake prune files during query planning, which can speed up filtered reads on large tables considerably.

Usage

set_table_partitioning(table_name, partition_by)

Arguments

table_name

The name of the table to partition.

partition_by

Character vector of partition expressions. Each entry must be one of:

  • a column name, e.g. "region" (identity transform)

  • "year(col)", "month(col)", "day(col)", or "hour(col)" for timestamp columns

  • "bucket(n, col)" for hash bucketing into n buckets

Value

Invisibly returns NULL.

Details

Partitioning only affects data written after the keys are set; previously written files keep their layout. To re-partition existing data, set the keys and then rewrite the table with replace_table(): the rewrite carries the keys over to the new table and writes every row through them.

Runs ALTER TABLE ... SET PARTITIONED BY (...). The expressions are validated against the transforms DuckLake supports before any SQL is built.

See also

reset_table_partitioning(), get_table_partitions()

Other partitioning: get_table_partitions(), reset_table_partitioning()

Examples

lake_dir <- tempfile("part_lake_")
dir.create(lake_dir)
attach_ducklake("part_lake", lake_path = lake_dir)
create_table(mtcars, "cars")

# Plain column partitioning
set_table_partitioning("cars", "cyl")
#> Table "cars" is now partitioned by "cyl".
#> ℹ Only newly written data is partitioned; existing files keep their layout.

# Compound key
set_table_partitioning("cars", c("gear", "cyl"))
#> Table "cars" is now partitioned by "gear" and "cyl".
#> ℹ Only newly written data is partitioned; existing files keep their layout.

# Timestamp columns can be split by year(), month(), day(), or hour()

detach_ducklake("part_lake", shutdown = TRUE)
unlink(lake_dir, recursive = TRUE)