5f23bb7e65
* switch to sparse collection for histogram Replaces histogram vec collection with a hashmap. This approach works much better for sparse data and enables use cases like drill downs (filter + small interval). It is slower for dense cases (1.3x-2x slower). This can be alleviated with a specialized hashmap in the future. closes #1704 closes #1370 * refactor, clippy * fix bucket_pos overflow issue
Contributing
When adding new bucket aggregation make sure to extend the "test_aggregation_flushing" test for at least 2 levels.
Code Organization
Tantivy's aggregations have been designed to mimic the aggregations of elasticsearch.
The code is organized in submodules:
bucket
Contains all bucket aggregations, like range aggregation. These bucket aggregations group documents into buckets and can contain sub-aggregations.
metric
Contains all metric aggregations, like average aggregation. Metric aggregations do not have sub aggregations.
agg_req
agg_req contains the users aggregation request. Deserialization from json is compatible with elasticsearch aggregation requests.
agg_req_with_accessor
agg_req_with_accessor contains the users aggregation request enriched with fast field accessors etc, which are used during collection.
segment_agg_result
segment_agg_result contains the aggregation result tree, which is used for collection of a segment. The tree from agg_req_with_accessor is passed during collection.
intermediate_agg_result
intermediate_agg_result contains the aggregation tree for merging with other trees.
agg_result
agg_result contains the final aggregation tree.