Issue with select and group_by _PARTITIONTIME

[ncuriale]

Having issues using _PARTITIONTIME with both dplyr::select and dplyr::group_by

It works with dplyr::distinct

> tbl %>% 
+     dplyr::filter(
+       dplyr::sql("_PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 30 DAY)")
+     ) %>%
+     dplyr::distinct(`_PARTITIONTIME`)
Complete
Billed: 0 B
Downloading first chunk of data.
First chunk includes all requested rows.
# Source:   lazy query [?? x 1]
# Database: BigQueryConnection
   `_PARTITIONTIME`   
   <dttm>             
 1 2023-04-18 00:00:00
 2 2023-04-25 00:00:00
 3 2023-04-17 00:00:00
 4 2023-04-27 00:00:00
 5 2023-04-16 00:00:00
 6 2023-04-30 00:00:00
 7 2023-04-11 00:00:00
 8 2023-04-23 00:00:00
 9 2023-04-14 00:00:00
10 2023-05-07 00:00:00
# ℹ more rows
# ℹ Use `print(n = ...)` to see more rows

Trying with select

> tbl %>% 
+     dplyr::filter(
+       dplyr::sql("_PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 30 DAY)")
+     ) %>%
+     dplyr::select(pt = `_PARTITIONTIME`) 
Error in `dplyr::select()`:
! Can't subset columns that don't exist.
✖ Column `_PARTITIONTIME` doesn't exist.
Run `rlang::last_trace()` to see where the error occurred.

Trying with group_by

> tbl %>% 
+     dplyr::filter(
+       dplyr::sql("_PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 30 DAY)")
+     ) %>%
+     dplyr::group_by(`_PARTITIONTIME`) %>%
+     dplyr::summarize(
+       MinReceived = min(dplyr::sql("Received"), na.rm = TRUE),
+       MaxReceived = max(dplyr::sql("Received"), na.rm = TRUE)
+     )
Error in `dplyr::group_by()`:
! Must group by variables found in `.data`.
✖ Column `_PARTITIONTIME` is not found.
Run `rlang::last_trace()` to see where the error occurred.

Any idea on whats going on here? If this is meant to work, what would be the correct syntax?

[hadley]

Can you give me a reprex? Or at least find a public partitioned table that I could try this out on?

[hadley]

I've closed this issue due to lack of requested reprex. If you still care about this bug, please open a new issue with a reprex.