add term aggregation clarification

This commit is contained in:
Pascal Seitz
2022-10-14 16:12:19 +08:00
parent 4b4c231bba
commit 952b048341
6 changed files with 72 additions and 18 deletions

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@@ -54,7 +54,7 @@ pub use self::serialize::{
/// Available codecs to use to encode the u64 (via [`MonotonicallyMappableToU64`]) converted data.
pub enum FastFieldCodecType {
/// Bitpack all values in the value range. The number of bits is defined by the amplitude
/// column.max_value()-column.min_value()
/// `column.max_value() - column.min_value()`
Bitpacked = 1,
/// Linear interpolation puts a line between the first and last value and then bitpacks the
/// 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::{
/// The normalized header gives some parameters after applying the following
/// normalization of the vector:
/// val -> (val - min_value) / gcd
/// `val -> (val - min_value) / gcd`
///
/// By design, after normalization, `min_value = 0` and `gcd = 1`.
#[derive(Debug, Copy, Clone)]

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@@ -17,7 +17,11 @@ use crate::fastfield::MultiValuedFastFieldReader;
use crate::schema::Type;
use crate::{DocId, TantivyError};
/// Creates a bucket for every unique term
/// Creates a bucket for every unique term and counts the number of occurences.
/// Note that doc_count in the response buckets equals term count here.
///
/// If the text is untokenized and single value, that means one term per document and therefore it
/// is in fact doc count.
///
/// ### Terminology
/// Shard parameters are supposed to be equivalent to elasticsearch shard parameter.
@@ -64,6 +68,25 @@ use crate::{DocId, TantivyError};
/// }
/// }
/// ```
///
/// /// # Response JSON Format
/// ```json
/// {
/// ...
/// "aggregations": {
/// "genres": {
/// "doc_count_error_upper_bound": 0,
/// "sum_other_doc_count": 0,
/// "buckets": [
/// { "key": "drumnbass", "doc_count": 6 },
/// { "key": "raggae", "doc_count": 4 },
/// { "key": "jazz", "doc_count": 2 }
/// ]
/// }
/// }
/// }
/// ```
#[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)]
pub struct TermsAggregation {
/// The field to aggregate on.
@@ -1206,11 +1229,43 @@ mod tests {
.collect();
let res = exec_request_with_query(agg_req, &index, None);
assert!(res.is_err());
Ok(())
}
#[test]
fn terms_aggregation_multi_token_per_doc() -> crate::Result<()> {
let terms = vec!["Hello Hello", "Hallo Hallo"];
let index = get_test_index_from_terms(true, &[terms])?;
let agg_req: Aggregations = vec![(
"my_texts".to_string(),
Aggregation::Bucket(BucketAggregation {
bucket_agg: BucketAggregationType::Terms(TermsAggregation {
field: "text_id".to_string(),
min_doc_count: Some(0),
..Default::default()
}),
sub_aggregation: Default::default(),
}),
)]
.into_iter()
.collect();
let res = exec_request_with_query(agg_req, &index, None).unwrap();
assert_eq!(res["my_texts"]["buckets"][0]["key"], "hello");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "hallo");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 2);
Ok(())
}
#[test]
fn test_json_format() -> crate::Result<()> {
let agg_req: Aggregations = vec![(

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@@ -10,21 +10,19 @@
//!
//! There are two categories: [Metrics](metric) and [Buckets](bucket).
//!
//! # Usage
//!
//! ## Prerequisite
//! Currently aggregations work only on [fast fields](`crate::fastfield`). Single value fast fields
//! of type `u64`, `f64`, `i64` and fast fields on text fields.
//!
//! ## Usage
//! To use aggregations, build an aggregation request by constructing
//! [`Aggregations`](agg_req::Aggregations).
//! Create an [`AggregationCollector`] from this request. `AggregationCollector` implements the
//! [`Collector`](crate::collector::Collector) trait and can be passed as collector into
//! [`Searcher::search()`](crate::Searcher::search).
//!
//! #### Limitations
//!
//! Currently aggregations work only on single value fast fields of type `u64`, `f64`, `i64` and
//! fast fields on text fields.
//!
//! # JSON Format
//! ## JSON Format
//! Aggregations request and result structures de/serialize into elasticsearch compatible JSON.
//!
//! ```verbatim
@@ -35,7 +33,7 @@
//! let json_response_string: String = &serde_json::to_string(&agg_res)?;
//! ```
//!
//! # Supported Aggregations
//! ## Supported Aggregations
//! - [Bucket](bucket)
//! - [Histogram](bucket::HistogramAggregation)
//! - [Range](bucket::RangeAggregation)

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@@ -7,16 +7,15 @@
//! It is designed for the fast random access of some document
//! fields given a document id.
//!
//! `FastField` are useful when a field is required for all or most of
//! the `DocSet` : for instance for scoring, grouping, filtering, or faceting.
//! Fast fields are useful when a field is required for all or most of
//! the `DocSet`: for instance for scoring, grouping, aggregation, filtering, or faceting.
//!
//!
//! Fields have to be declared as `FAST` in the schema.
//! Currently supported fields are: u64, i64, f64 and bytes.
//! Fields have to be declared as `FAST` in the schema.
//! Currently supported fields are: u64, i64, f64, bytes and text.
//!
//! u64, i64 and f64 fields are stored in a bit-packed fashion so that
//! their memory usage is directly linear with the amplitude of the
//! values stored.
//! Fast fields are stored in with [different codecs](fastfield_codecs). The best codec is detected
//! automatically, when serializing.
//!
//! Read access performance is comparable to that of an array lookup.

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@@ -37,6 +37,8 @@ pub struct FastFlag;
///
/// Fast fields can be random-accessed rapidly. Fields useful for scoring, filtering
/// or collection should be mark as fast fields.
///
/// See [fast fields](`crate::fastfield`).
pub const FAST: SchemaFlagList<FastFlag, ()> = SchemaFlagList {
head: FastFlag,
tail: (),