This is a first post, so please bear with me!
I'm running a 3 replica cluster with client node on ES 1.7 on 8 core/60Gb machines. I have an index containing various analysed fields and a nested geoshape. The stored geoshapes are generally "circles" of up to 400000 metres (~250 miles) radius.
Previously the index was mapped with the default geoshape precision/tree_levels setting (50 metres) which I believe equates to a tree_levels value of 12.
The index contains nearly 4 million documents (roughly 48 million due to nesting) and memory usage was around 30Gb.
Performance was good, average query between 100 - 200ms, but I was looking to reduce the memory usage.
I reindexed the data into another index with the mapping geoshape precision value of 500m (equating to tree_levels 7). The data is identical, but query times are now double at 400 - 900 ms. Memory usage of this index has halved however!
I would have thought a lower tree_levels value would have improved query times as there are fewer geohash terms in the prefix tree. The "performance considerations" section in the documentation cautions the use of high tree_levels values, however i'm seeing quite a degradation in query performance with lower values.
I can't find any similar issues by searching. Any experience or wisdom would be greatly appreciated.
Thanks in advance.