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The results of geo-filters are not cached by default, for two reasons:
- Geo-filters are usually used to find entities that are near to a user’s current location. The problem is that users move, and no two users are in exactly the same location. A cached filter would have little chance of being reused.
- Filters are cached as bitsets that represent all documents in a segment. Imagine that our query excludes all documents but one in a particular segment. An uncached geo-filter just needs to check the one remaining document, but a cached geo-filter would need to check all of the documents in the segment.
That said, caching can be used to good effect with geo-filters. Imagine that your index contains restaurants from all over the United States. A user in New York is not interested in restaurants in San Francisco. We can treat New York as a hot spot and draw a big bounding box around the city and neighboring areas.
This geo_bounding_box filter can be cached and
reused whenever we have a
user within the city limits of New York. It will exclude all restaurants
from the rest of the country. We can then use an uncached, more specific
geo_bounding_box or geo_distance filter to narrow the remaining results to those that are close to the user:
GET /attractions/restaurant/_search
{
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"geo_bounding_box": {
"type": "indexed",
"_cache": true, 
"location": {
"top_left": {
"lat": 40,8,
"lon": -74.1
},
"bottom_right": {
"lat": 40.4,
"lon": -73.7
}
}
}
},
{
"geo_distance": { 
"distance": "1km",
"location": {
"lat": 40.715,
"lon": -73.988
}
}
}
]
}
}
}
}
}
| The cached bounding box filter reduces all results down to those in the greater New York area. |
|
The more costly |