A user reported that the same query that takes ~900ms when querying an index
pattern only takes ~50ms when only querying indices that have matches. The
query is a date range query and we confirmed that the `can_match` phase works
as expected. I was able to reproduce this issue locally with a single node: with
900 1-shard indices, a query to an index pattern that matches all indices runs
in ~90ms while a query to the only index that has matches runs in 0-1ms.
This ended up not being related to the `can_match` phase but to the cost of
resolving aliases when querying an index pattern that matches lots of indices.
In that case, we first resolve the index pattern to a list of concrete indices
and then for each concrete index, we check whether it was matched through an
alias, meaning we might have to apply alias filters. Unfortunately this second
per-index operation runs in linear time with the number of matched concrete
indices, which means that alias resolution runs in O(num_indices^2) overall.
So queries get exponentially slower as an index pattern matches more indices.
I reorganized alias resolution into a one-step operation that runs in linear
time with the number of matches indices, and then a per-index operation that
runs in linear time with the number of aliases of this index. This makes alias
resolution run is O(num_indices * num_aliases_per_index) overall instead. When
testing the scenario described above, the `took` went down from ~90ms to ~10ms.
It is still more than the 0-1ms latency that one gets when only querying the
single index that has data, but still much better than what we had before.
Closes#40248
670e76669c