mirror of
https://github.com/quickwit-oss/tantivy.git
synced 2026-06-01 08:00:41 +00:00
add term aggregation clarification
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@@ -54,7 +54,7 @@ pub use self::serialize::{
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/// Available codecs to use to encode the u64 (via [`MonotonicallyMappableToU64`]) converted data.
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pub enum FastFieldCodecType {
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/// Bitpack all values in the value range. The number of bits is defined by the amplitude
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/// column.max_value()-column.min_value()
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/// `column.max_value() - column.min_value()`
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Bitpacked = 1,
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/// Linear interpolation puts a line between the first and last value and then bitpacks the
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/// values by the offset from the line. The number of bits is defined by the max deviation from
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@@ -40,7 +40,7 @@ use crate::{
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/// The normalized header gives some parameters after applying the following
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/// normalization of the vector:
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/// val -> (val - min_value) / gcd
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/// `val -> (val - min_value) / gcd`
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///
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/// By design, after normalization, `min_value = 0` and `gcd = 1`.
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#[derive(Debug, Copy, Clone)]
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@@ -17,7 +17,11 @@ use crate::fastfield::MultiValuedFastFieldReader;
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use crate::schema::Type;
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use crate::{DocId, TantivyError};
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/// Creates a bucket for every unique term
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/// Creates a bucket for every unique term and counts the number of occurences.
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/// Note that doc_count in the response buckets equals term count here.
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///
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/// If the text is untokenized and single value, that means one term per document and therefore it
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/// is in fact doc count.
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///
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/// ### Terminology
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/// Shard parameters are supposed to be equivalent to elasticsearch shard parameter.
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@@ -64,6 +68,25 @@ use crate::{DocId, TantivyError};
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/// }
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/// }
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/// ```
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///
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/// /// # Response JSON Format
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/// ```json
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/// {
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/// ...
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/// "aggregations": {
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/// "genres": {
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/// "doc_count_error_upper_bound": 0,
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/// "sum_other_doc_count": 0,
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/// "buckets": [
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/// { "key": "drumnbass", "doc_count": 6 },
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/// { "key": "raggae", "doc_count": 4 },
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/// { "key": "jazz", "doc_count": 2 }
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/// ]
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/// }
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/// }
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/// }
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/// ```
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#[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)]
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pub struct TermsAggregation {
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/// The field to aggregate on.
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@@ -1206,11 +1229,43 @@ mod tests {
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.collect();
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let res = exec_request_with_query(agg_req, &index, None);
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assert!(res.is_err());
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Ok(())
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}
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#[test]
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fn terms_aggregation_multi_token_per_doc() -> crate::Result<()> {
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let terms = vec!["Hello Hello", "Hallo Hallo"];
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let index = get_test_index_from_terms(true, &[terms])?;
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let agg_req: Aggregations = vec![(
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"my_texts".to_string(),
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Aggregation::Bucket(BucketAggregation {
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bucket_agg: BucketAggregationType::Terms(TermsAggregation {
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field: "text_id".to_string(),
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min_doc_count: Some(0),
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..Default::default()
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}),
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sub_aggregation: Default::default(),
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}),
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)]
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.into_iter()
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.collect();
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let res = exec_request_with_query(agg_req, &index, None).unwrap();
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assert_eq!(res["my_texts"]["buckets"][0]["key"], "hello");
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assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 2);
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assert_eq!(res["my_texts"]["buckets"][1]["key"], "hallo");
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assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 2);
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Ok(())
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}
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#[test]
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fn test_json_format() -> crate::Result<()> {
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let agg_req: Aggregations = vec and [Buckets](bucket).
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//!
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//! # Usage
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//!
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//! ## Prerequisite
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//! Currently aggregations work only on [fast fields](`crate::fastfield`). Single value fast fields
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//! of type `u64`, `f64`, `i64` and fast fields on text fields.
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//!
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//! ## Usage
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//! To use aggregations, build an aggregation request by constructing
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//! [`Aggregations`](agg_req::Aggregations).
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//! Create an [`AggregationCollector`] from this request. `AggregationCollector` implements the
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//! [`Collector`](crate::collector::Collector) trait and can be passed as collector into
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//! [`Searcher::search()`](crate::Searcher::search).
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//!
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//! #### Limitations
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//!
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//! Currently aggregations work only on single value fast fields of type `u64`, `f64`, `i64` and
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//! fast fields on text fields.
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//!
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//! # JSON Format
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//! ## JSON Format
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//! Aggregations request and result structures de/serialize into elasticsearch compatible JSON.
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//!
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//! ```verbatim
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@@ -35,7 +33,7 @@
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//! let json_response_string: String = &serde_json::to_string(&agg_res)?;
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//! ```
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//!
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//! # Supported Aggregations
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//! ## Supported Aggregations
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//! - [Bucket](bucket)
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//! - [Histogram](bucket::HistogramAggregation)
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//! - [Range](bucket::RangeAggregation)
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@@ -7,16 +7,15 @@
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//! It is designed for the fast random access of some document
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//! fields given a document id.
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//!
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//! `FastField` are useful when a field is required for all or most of
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//! the `DocSet` : for instance for scoring, grouping, filtering, or faceting.
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//! Fast fields are useful when a field is required for all or most of
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//! the `DocSet`: for instance for scoring, grouping, aggregation, filtering, or faceting.
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//!
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//!
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//! Fields have to be declared as `FAST` in the schema.
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//! Currently supported fields are: u64, i64, f64 and bytes.
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//! Fields have to be declared as `FAST` in the schema.
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//! Currently supported fields are: u64, i64, f64, bytes and text.
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//!
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//! u64, i64 and f64 fields are stored in a bit-packed fashion so that
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//! their memory usage is directly linear with the amplitude of the
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//! values stored.
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//! Fast fields are stored in with [different codecs](fastfield_codecs). The best codec is detected
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//! automatically, when serializing.
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//!
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//! Read access performance is comparable to that of an array lookup.
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@@ -37,6 +37,8 @@ pub struct FastFlag;
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///
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/// Fast fields can be random-accessed rapidly. Fields useful for scoring, filtering
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/// or collection should be mark as fast fields.
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///
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/// See [fast fields](`crate::fastfield`).
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pub const FAST: SchemaFlagList<FastFlag, ()> = SchemaFlagList {
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head: FastFlag,
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tail: (),
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