# Update to `filter()` behaviour in bcdata v0.4.0

#### 2026-07-08

This vignette describes a change in `{bcdata}` v0.4.0 related to using locally-executed functions in a `filter()` query with `bcdc_query_geodata()`:

When using `bcdc_query_geodata()` with `filter()`, many functions are translated to a query plan that is passed to and executed on the server - this includes the CQL Geometry predicates such as `INTERESECTS()`, `CROSSES()`, `BBOX()` etc, as well as many base R functions. However you sometimes want to include a function call in your `filter()` statement which should be evaluated locally - i.e., it’s an R function (often an `{sf}` function) with no equivalent function on the server. Prior to version 0.4.0, `{bcdata}` did a reasonable (though not perfect) job of detecting R functions inside a `filter()` statement that needed to be evaluated locally. In order to align with recommended best practices for `{dbplyr}` backends, as of v0.4.0, function calls that are to be evaluated locally now need to be wrapped in `local()`.

For example, say we want to create a bounding box around two points and use that box to perform a spatial filter on the remote dataset, to give us just the set of local greenspaces that exist within that bounding box.

    library(sf)
    library(bcdata)

    two_points <- st_sfc(st_point(c(1164434, 368738)),
                         st_point(c(1203023, 412959)),
                         crs = 3005)

Previously, we could just do this, with `sf::st_bbox()` embedded in the call:

    bcdc_query_geodata("local-and-regional-greenspaces") %>%
      filter(BBOX(st_bbox(two_points, crs = st_crs(two_points))))

    ## Error:
    ## ! Error : Cannot translate a <sfc_POINT> object to SQL.
    ## ℹ Do you want to force evaluation in R with (e.g.) `!!x` or `local(x)`?

However you must now use `local()` to force local evaluation of `st_bbox()` on your machine in R, before it is translated into a query plan to be executed on the server:

    bcdc_query_geodata("local-and-regional-greenspaces") %>%
      filter(BBOX(local(st_bbox(two_points, crs = st_crs(two_points)))))

    ## Querying 'local-and-regional-greenspaces' record
    ## • Using collect() on this object will return 1236 features and 19 fields
    ## • At most six rows of the record are printed here
    ## ────────────────────────────────────────────────────────────────────────────────────────────────────
    ## Simple feature collection with 6 features and 19 fields
    ## Geometry type: MULTIPOLYGON
    ## Dimension:     XY
    ## Bounding box:  xmin: 1199043 ymin: 387901.5 xmax: 1199503 ymax: 390352.7
    ## Projected CRS: NAD83 / BC Albers
    ## # A tibble: 6 × 20
    ##   id      LOCAL_REG_GREENSPACE…¹ PARK_NAME PARK_TYPE PARK_PRIMARY_USE REGIONAL_DISTRICT MUNICIPALITY
    ##   <chr>                    <int> <chr>     <chr>     <chr>            <chr>             <chr>
    ## 1 WHSE_B…                   7806 Beach Ac… Local     Water Access     Capital           District of…
    ## 2 WHSE_B…                   8020 Balmacar… Local     Water Access     Capital           District of…
    ## 3 WHSE_B…                   7871 Vantreig… Local     Park             Capital           District of…
    ## 4 WHSE_B…                   7844 Montague… Local     Park             Capital           District of…
    ## 5 WHSE_B…                   7882 Houlihan… Local     Park             Capital           District of…
    ## 6 WHSE_B…                   7895 Casa Mar… Local     Green Space      Capital           District of…
    ## # ℹ abbreviated name: ¹​LOCAL_REG_GREENSPACE_ID
    ## # ℹ 13 more variables: CIVIC_NUMBER <chr>, CIVIC_NUMBER_SUFFIX <chr>, STREET_NAME <chr>,
    ## #   LATITUDE <dbl>, LONGITUDE <dbl>, WHEN_UPDATED <date>, WEBSITE_URL <chr>,
    ## #   LICENCE_COMMENTS <chr>, FEATURE_AREA_SQM <dbl>, FEATURE_LENGTH_M <dbl>, OBJECTID <int>,
    ## #   SE_ANNO_CAD_DATA <chr>, geometry <MULTIPOLYGON [m]>

There is another illustration in the “querying spatial data vignette”.