bziobrowski commented on code in PR #14628:
URL: https://github.com/apache/pinot/pull/14628#discussion_r1879603841
##########
pinot-core/src/main/java/org/apache/pinot/core/operator/filter/H3IndexFilterOperator.java:
##########
@@ -78,7 +78,15 @@ public H3IndexFilterOperator(IndexSegment segment,
QueryContext queryContext, Pr
assert _h3IndexReader != null;
int resolution =
_h3IndexReader.getH3IndexResolution().getLowestResolution();
_h3Id = H3Utils.H3_CORE.geoToH3(coordinate.y, coordinate.x, resolution);
- _edgeLength = H3Utils.H3_CORE.edgeLength(resolution, LengthUnit.m);
+
+ // choose current hexagon's longest edge instead of average for the
resolution;
Review Comment:
Calculating precise edge length for each ring would most likely defeat any
potential performance gains coming from using H3. That's because we could end
up calculating distances for up to 30k hexagons even if we don't have any
points belonging to them. For finger-grained precisions (7+) using current
edge length should be fine because edge length shouldn't change much within the
boundary of 100 rings (or 30k closest hexagons). For coarse-grained precisions,
if center is placed near icosahedron edge and distance is large it could end up
producing more results because hexagons far from it would be visibly bigger
(and we claim them even though we shouldn't ).
In general - I don't think this application of H3 makes too much sense.
It'd be better to expose library functions such as geoToH3, h3Distance, etc.
and let users express geo queries in terms of hexagon distances, e.g.
```sql
SELECT COUNT(*)
FROM testTable
WHERE geoToH3(indexed_point) = geoToH3(ST_Point(-122, 37.5, 1))
```
or
```sql
SELECT COUNT(*)
FROM testTable
WHERE h3Distance( geoToH3(indexed_point),geoToH3(ST_Point(-122, 37.5, 1)) )
< 10
```
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