Optimizing DISTANCE using projections

Hi folks,

I am currently using the DISTANCE function in vertica. I'm not getting great performance, so wanted to get your opinion on if this can be optimized. If anyone has optimized DISTANCE using projections before, your opinion would be greatly appreciated.

My Query:

SELECT Date_trunc('month', modified_date),
      APPROXIMATE_COUNT_DISTINCT(userId)  AS distinct_user_count
FROM   mySchema.userProjection
WHERE modified_date BETWEEN '2021-01-01' AND '2022-01-31'
       AND country = 'US'
       AND DISTANCE(40.71427, -74.00597, userLatitude, userLongitude) < 160
GROUP BY 1 ORDER BY 1

My Projection:

CREATE PROJECTION mySchema.userProjection
    (
     country ENCODING RLE,
     modified_date ENCODING ZSTD_FAST_COMP,
     userLatitude ENCODING ZSTD_FAST_COMP,
     userLongitude ENCODING ZSTD_FAST_COMP,
     userId ENCODING ZSTD_FAST_COMP
     )
    AS
        SELECT myTable.country,
               myTable.modified_date,
               myTable.userLatitude,
               myTable.userLongitude,
               myTable.userId,
        FROM mySchema.myTable
        ORDER BY myTable.country,
                 myTable.userLatitude,
                 myTable.userLongitude
    SEGMENTED BY hash(myTable.country, myTable.userId, myTable.modified_date) ALL NODES;

The table is partitioned by modified_date. Query currently takes about 16s, I was really aiming for <5s.

My guess is DISTANCE might not be using the projection correctly.

Appreciate any help!