Feature Request / Improvement
For time partitioning, we can express time range expressions and they lead to partition pruning when planning an Arrow scan:
scan = table.scan(
row_filter=And(
GreaterThanOrEqual("event_ts", start),
LessThan("event_ts", end),
)
)
arrow_table = scan.to_arrow()
It would be useful to be able to filter by other hidden partitioning transforms, such as buckets -- e.g. filtering on bucket[16](user_id) in {0, 1, 2, 3}, and getting partition pruning whenever possible based on the underlying table partitioning specs (falling back to filtering rows when files cannot be pruned).
Feature Request / Improvement
For time partitioning, we can express time range expressions and they lead to partition pruning when planning an Arrow scan:
It would be useful to be able to filter by other hidden partitioning transforms, such as buckets -- e.g. filtering on
bucket[16](user_id) in {0, 1, 2, 3}, and getting partition pruning whenever possible based on the underlying table partitioning specs (falling back to filtering rows when files cannot be pruned).