Pascal Seitz
057e9d6618
If term aggregations don't have sub-aggregations, we don't need to carry BucketId(u32). ``` full terms_7 Memory: 46.5 KB Avg: 2.4024ms (+1.96%) Median: 2.4024ms (+1.96%) [2.4024ms .. 2.4024ms] terms_all_unique Memory: 11.5 MB (-9.93%) Avg: 4.7910ms (-22.62%) Median: 4.7910ms (-22.62%) [4.7910ms .. 4.7910ms] terms_all_unique_order_by_key Memory: 11.5 MB (-9.94%) Avg: 4.8056ms (-21.31%) Median: 4.8056ms (-21.31%) [4.8056ms .. 4.8056ms] terms_150_000 Memory: 2.7 MB (-9.90%) Avg: 5.7312ms (-5.96%) Median: 5.7312ms (-5.96%) [5.7312ms .. 5.7312ms] terms_many_top_1000 Memory: 5.3 MB Avg: 8.5912ms (-3.34%) Median: 8.5912ms (-3.34%) [8.5912ms .. 8.5912ms] terms_many_order_by_term Memory: 2.7 MB (-9.95%) Avg: 4.5581ms (-10.79%) Median: 4.5581ms (-10.79%) [4.5581ms .. 4.5581ms] terms_many_with_top_hits Memory: 48.9 MB Avg: 102.3672ms (-2.30%) Median: 102.3672ms (-2.30%) [102.3672ms .. 102.3672ms] terms_all_unique_with_avg_sub_agg Memory: 54.7 MB Avg: 18.4644ms (-0.11%) Median: 18.4644ms (-0.11%) [18.4644ms .. 18.4644ms] terms_many_with_avg_sub_agg Memory: 13.5 MB Avg: 16.7345ms (-4.09%) Median: 16.7345ms (-4.09%) [16.7345ms .. 16.7345ms] terms_status_with_avg_sub_agg Memory: 92.1 KB Avg: 5.1590ms (+0.33%) Median: 5.1590ms (+0.33%) [5.1590ms .. 5.1590ms] terms_status_with_terms_zipf_1000_sub_agg Memory: 213.2 KB Avg: 3.9562ms (+1.49%) Median: 3.9562ms (+1.49%) [3.9562ms .. 3.9562ms] terms_zipf_1000_with_terms_status_sub_agg Memory: 724.4 KB Avg: 11.7206ms (-4.68%) Median: 11.7206ms (-4.68%) [11.7206ms .. 11.7206ms] terms_status_with_histogram Memory: 139.0 KB Avg: 2.3985ms (-1.07%) Median: 2.3985ms (-1.07%) [2.3985ms .. 2.3985ms] terms_status_with_date_histogram Memory: 145.9 KB Avg: 2.2963ms (-1.86%) Median: 2.2963ms (-1.86%) [2.2963ms .. 2.2963ms] terms_status_with_date_histogram_hard_bounds Memory: 145.4 KB Avg: 2.4312ms (-1.37%) Median: 2.4312ms (-1.37%) [2.4312ms .. 2.4312ms] terms_status_with_date_histogram_and_sibling_terms Memory: 143.3 KB Avg: 3.8401ms (+0.44%) Median: 3.8401ms (+0.44%) [3.8401ms .. 3.8401ms] terms_zipf_1000 Memory: 75.8 KB Avg: 2.1611ms (-2.70%) Median: 2.1611ms (-2.70%) [2.1611ms .. 2.1611ms] terms_zipf_1000_with_histogram Memory: 1.2 MB Avg: 20.1369ms (-1.16%) Median: 20.1369ms (-1.16%) [20.1369ms .. 20.1369ms] terms_zipf_1000_with_avg_sub_agg Memory: 472.7 KB Avg: 8.5851ms (-4.93%) Median: 8.5851ms (-4.93%) [8.5851ms .. 8.5851ms] terms_many_json_mixed_type_with_avg_sub_agg Memory: 17.9 MB Avg: 26.3988ms (-6.61%) Median: 26.3988ms (-6.61%) [26.3988ms .. 26.3988ms] ```
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_data
agg_data 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. agg_data 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.