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move all the searches structures to new modules

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This commit is contained in:
Tamo 2024-10-20 17:54:43 +02:00
parent af589c85ec
commit 5675585fe8
10 changed files with 903 additions and 874 deletions
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4
meilisearch/src/analytics/mod.rs
View File

@ -15,13 +15,9 @@ use platform_dirs::AppDirs;
// if the feature analytics is enabled we use the real analytics
pub type SegmentAnalytics = segment_analytics::SegmentAnalytics;
pub use segment_analytics::SearchAggregator;
pub use segment_analytics::SimilarAggregator;
use crate::Opt;
pub use self::segment_analytics::MultiSearchAggregator;
/// A macro used to quickly define events that don't aggregate or send anything besides an empty event with its name.
#[macro_export]
macro_rules! empty_analytics {

868
meilisearch/src/analytics/segment_analytics.rs
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@ -1,5 +1,5 @@
use std::any::TypeId;
use std::collections::{BTreeSet, BinaryHeap, HashMap, HashSet};
use std::collections::{HashMap, HashSet};
use std::fs;
use std::path::{Path, PathBuf};
use std::sync::Arc;
@ -11,10 +11,8 @@ use byte_unit::Byte;
use index_scheduler::IndexScheduler;
use meilisearch_auth::{AuthController, AuthFilter};
use meilisearch_types::features::RuntimeTogglableFeatures;
use meilisearch_types::locales::Locale;
use meilisearch_types::InstanceUid;
use once_cell::sync::Lazy;
use regex::Regex;
use segment::message::{Identify, Track, User};
use segment::{AutoBatcher, Batcher, HttpClient};
use serde::Serialize;
@ -25,17 +23,12 @@ use tokio::select;
use tokio::sync::mpsc::{self, Receiver, Sender};
use uuid::Uuid;
use super::{config_user_id_path, Aggregate, AggregateMethod, MEILISEARCH_CONFIG_PATH};
use super::{config_user_id_path, Aggregate, MEILISEARCH_CONFIG_PATH};
use crate::option::{
default_http_addr, IndexerOpts, LogMode, MaxMemory, MaxThreads, ScheduleSnapshot,
};
use crate::routes::{create_all_stats, Stats};
use crate::search::{
FederatedSearch, SearchQuery, SearchQueryWithIndex, SearchResult, SimilarQuery, SimilarResult,
DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEMANTIC_RATIO,
};
use crate::{aggregate_methods, Opt};
use crate::Opt;
const ANALYTICS_HEADER: &str = "X-Meilisearch-Client";
@ -489,858 +482,3 @@ impl Segment {
let _ = self.batcher.flush().await;
}
}
#[derive(Default)]
pub struct SearchAggregator<Method: AggregateMethod> {
// requests
total_received: usize,
total_succeeded: usize,
total_degraded: usize,
total_used_negative_operator: usize,
time_spent: BinaryHeap<usize>,
// sort
sort_with_geo_point: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
sort_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
sort_total_number_of_criteria: usize,
// distinct
distinct: bool,
// filter
filter_with_geo_radius: bool,
filter_with_geo_bounding_box: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
filter_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
filter_total_number_of_criteria: usize,
used_syntax: HashMap<String, usize>,
// attributes_to_search_on
// every time a search is done using attributes_to_search_on
attributes_to_search_on_total_number_of_uses: usize,
// q
// The maximum number of terms in a q request
max_terms_number: usize,
// vector
// The maximum number of floats in a vector request
max_vector_size: usize,
// Whether the semantic ratio passed to a hybrid search equals the default ratio.
semantic_ratio: bool,
hybrid: bool,
retrieve_vectors: bool,
// every time a search is done, we increment the counter linked to the used settings
matching_strategy: HashMap<String, usize>,
// List of the unique Locales passed as parameter
locales: BTreeSet<Locale>,
// pagination
max_limit: usize,
max_offset: usize,
finite_pagination: usize,
// formatting
max_attributes_to_retrieve: usize,
max_attributes_to_highlight: usize,
highlight_pre_tag: bool,
highlight_post_tag: bool,
max_attributes_to_crop: usize,
crop_marker: bool,
show_matches_position: bool,
crop_length: bool,
// facets
facets_sum_of_terms: usize,
facets_total_number_of_facets: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
ranking_score_threshold: bool,
marker: std::marker::PhantomData<Method>,
}
impl<Method: AggregateMethod> SearchAggregator<Method> {
#[allow(clippy::field_reassign_with_default)]
pub fn from_query(query: &SearchQuery) -> Self {
let SearchQuery {
q,
vector,
offset,
limit,
page,
hits_per_page,
attributes_to_retrieve: _,
retrieve_vectors,
attributes_to_crop: _,
crop_length,
attributes_to_highlight: _,
show_matches_position,
show_ranking_score,
show_ranking_score_details,
filter,
sort,
distinct,
facets: _,
highlight_pre_tag,
highlight_post_tag,
crop_marker,
matching_strategy,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
locales,
} = query;
let mut ret = Self::default();
ret.total_received = 1;
if let Some(ref sort) = sort {
ret.sort_total_number_of_criteria = 1;
ret.sort_with_geo_point = sort.iter().any(|s| s.contains("_geoPoint("));
ret.sort_sum_of_criteria_terms = sort.len();
}
ret.distinct = distinct.is_some();
if let Some(ref filter) = filter {
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
ret.filter_total_number_of_criteria = 1;
let syntax = match filter {
Value::String(_) => "string".to_string(),
Value::Array(values) => {
if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
"mixed".to_string()
} else {
"array".to_string()
}
}
_ => "none".to_string(),
};
// convert the string to a HashMap
ret.used_syntax.insert(syntax, 1);
let stringified_filters = filter.to_string();
ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
}
// attributes_to_search_on
if attributes_to_search_on.is_some() {
ret.attributes_to_search_on_total_number_of_uses = 1;
}
if let Some(ref q) = q {
ret.max_terms_number = q.split_whitespace().count();
}
if let Some(ref vector) = vector {
ret.max_vector_size = vector.len();
}
ret.retrieve_vectors |= retrieve_vectors;
if query.is_finite_pagination() {
let limit = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
ret.max_limit = limit;
ret.max_offset = page.unwrap_or(1).saturating_sub(1) * limit;
ret.finite_pagination = 1;
} else {
ret.max_limit = *limit;
ret.max_offset = *offset;
ret.finite_pagination = 0;
}
ret.matching_strategy.insert(format!("{:?}", matching_strategy), 1);
if let Some(locales) = locales {
ret.locales = locales.iter().copied().collect();
}
ret.highlight_pre_tag = *highlight_pre_tag != DEFAULT_HIGHLIGHT_PRE_TAG();
ret.highlight_post_tag = *highlight_post_tag != DEFAULT_HIGHLIGHT_POST_TAG();
ret.crop_marker = *crop_marker != DEFAULT_CROP_MARKER();
ret.crop_length = *crop_length != DEFAULT_CROP_LENGTH();
ret.show_matches_position = *show_matches_position;
ret.show_ranking_score = *show_ranking_score;
ret.show_ranking_score_details = *show_ranking_score_details;
ret.ranking_score_threshold = ranking_score_threshold.is_some();
if let Some(hybrid) = hybrid {
ret.semantic_ratio = hybrid.semantic_ratio != DEFAULT_SEMANTIC_RATIO();
ret.hybrid = true;
}
ret
}
pub fn succeed(&mut self, result: &SearchResult) {
let SearchResult {
hits: _,
query: _,
processing_time_ms,
hits_info: _,
semantic_hit_count: _,
facet_distribution: _,
facet_stats: _,
degraded,
used_negative_operator,
} = result;
self.total_succeeded = self.total_succeeded.saturating_add(1);
if *degraded {
self.total_degraded = self.total_degraded.saturating_add(1);
}
if *used_negative_operator {
self.total_used_negative_operator = self.total_used_negative_operator.saturating_add(1);
}
self.time_spent.push(*processing_time_ms as usize);
}
}
aggregate_methods!(
SearchGET => "Documents Searched GET",
SearchPOST => "Documents Searched POST",
);
impl<Method: AggregateMethod> Aggregate for SearchAggregator<Method> {
fn event_name(&self) -> &'static str {
Method::event_name()
}
fn aggregate(mut self: Box<Self>, new: Box<Self>) -> Box<Self> {
let Self {
total_received,
total_succeeded,
mut time_spent,
sort_with_geo_point,
sort_sum_of_criteria_terms,
sort_total_number_of_criteria,
distinct,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
attributes_to_search_on_total_number_of_uses,
max_terms_number,
max_vector_size,
retrieve_vectors,
matching_strategy,
max_limit,
max_offset,
finite_pagination,
max_attributes_to_retrieve,
max_attributes_to_highlight,
highlight_pre_tag,
highlight_post_tag,
max_attributes_to_crop,
crop_marker,
show_matches_position,
crop_length,
facets_sum_of_terms,
facets_total_number_of_facets,
show_ranking_score,
show_ranking_score_details,
semantic_ratio,
hybrid,
total_degraded,
total_used_negative_operator,
ranking_score_threshold,
mut locales,
marker: _,
} = *new;
// request
self.total_received = self.total_received.saturating_add(total_received);
self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
self.total_degraded = self.total_degraded.saturating_add(total_degraded);
self.total_used_negative_operator =
self.total_used_negative_operator.saturating_add(total_used_negative_operator);
self.time_spent.append(&mut time_spent);
// sort
self.sort_with_geo_point |= sort_with_geo_point;
self.sort_sum_of_criteria_terms =
self.sort_sum_of_criteria_terms.saturating_add(sort_sum_of_criteria_terms);
self.sort_total_number_of_criteria =
self.sort_total_number_of_criteria.saturating_add(sort_total_number_of_criteria);
// distinct
self.distinct |= distinct;
// filter
self.filter_with_geo_radius |= filter_with_geo_radius;
self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
self.filter_sum_of_criteria_terms =
self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
self.filter_total_number_of_criteria =
self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
for (key, value) in used_syntax.into_iter() {
let used_syntax = self.used_syntax.entry(key).or_insert(0);
*used_syntax = used_syntax.saturating_add(value);
}
// attributes_to_search_on
self.attributes_to_search_on_total_number_of_uses = self
.attributes_to_search_on_total_number_of_uses
.saturating_add(attributes_to_search_on_total_number_of_uses);
// q
self.max_terms_number = self.max_terms_number.max(max_terms_number);
// vector
self.max_vector_size = self.max_vector_size.max(max_vector_size);
self.retrieve_vectors |= retrieve_vectors;
self.semantic_ratio |= semantic_ratio;
self.hybrid |= hybrid;
// pagination
self.max_limit = self.max_limit.max(max_limit);
self.max_offset = self.max_offset.max(max_offset);
self.finite_pagination += finite_pagination;
// formatting
self.max_attributes_to_retrieve =
self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
self.max_attributes_to_highlight =
self.max_attributes_to_highlight.max(max_attributes_to_highlight);
self.highlight_pre_tag |= highlight_pre_tag;
self.highlight_post_tag |= highlight_post_tag;
self.max_attributes_to_crop = self.max_attributes_to_crop.max(max_attributes_to_crop);
self.crop_marker |= crop_marker;
self.show_matches_position |= show_matches_position;
self.crop_length |= crop_length;
// facets
self.facets_sum_of_terms = self.facets_sum_of_terms.saturating_add(facets_sum_of_terms);
self.facets_total_number_of_facets =
self.facets_total_number_of_facets.saturating_add(facets_total_number_of_facets);
// matching strategy
for (key, value) in matching_strategy.into_iter() {
let matching_strategy = self.matching_strategy.entry(key).or_insert(0);
*matching_strategy = matching_strategy.saturating_add(value);
}
// scoring
self.show_ranking_score |= show_ranking_score;
self.show_ranking_score_details |= show_ranking_score_details;
self.ranking_score_threshold |= ranking_score_threshold;
// locales
self.locales.append(&mut locales);
self
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
time_spent,
sort_with_geo_point,
sort_sum_of_criteria_terms,
sort_total_number_of_criteria,
distinct,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
attributes_to_search_on_total_number_of_uses,
max_terms_number,
max_vector_size,
retrieve_vectors,
matching_strategy,
max_limit,
max_offset,
finite_pagination,
max_attributes_to_retrieve,
max_attributes_to_highlight,
highlight_pre_tag,
highlight_post_tag,
max_attributes_to_crop,
crop_marker,
show_matches_position,
crop_length,
facets_sum_of_terms,
facets_total_number_of_facets,
show_ranking_score,
show_ranking_score_details,
semantic_ratio,
hybrid,
total_degraded,
total_used_negative_operator,
ranking_score_threshold,
locales,
marker: _,
} = *self;
// we get all the values in a sorted manner
let time_spent = time_spent.into_sorted_vec();
// the index of the 99th percentage of value
let percentile_99th = time_spent.len() * 99 / 100;
// We are only interested by the slowest value of the 99th fastest results
let time_spent = time_spent.get(percentile_99th);
json!({
"requests": {
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
"total_degraded": total_degraded,
"total_used_negative_operator": total_used_negative_operator,
},
"sort": {
"with_geoPoint": sort_with_geo_point,
"avg_criteria_number": format!("{:.2}", sort_sum_of_criteria_terms as f64 / sort_total_number_of_criteria as f64),
},
"distinct": distinct,
"filter": {
"with_geoRadius": filter_with_geo_radius,
"with_geoBoundingBox": filter_with_geo_bounding_box,
"avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
"most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"attributes_to_search_on": {
"total_number_of_uses": attributes_to_search_on_total_number_of_uses,
},
"q": {
"max_terms_number": max_terms_number,
},
"vector": {
"max_vector_size": max_vector_size,
"retrieve_vectors": retrieve_vectors,
},
"hybrid": {
"enabled": hybrid,
"semantic_ratio": semantic_ratio,
},
"pagination": {
"max_limit": max_limit,
"max_offset": max_offset,
"most_used_navigation": if finite_pagination > (total_received / 2) { "exhaustive" } else { "estimated" },
},
"formatting": {
"max_attributes_to_retrieve": max_attributes_to_retrieve,
"max_attributes_to_highlight": max_attributes_to_highlight,
"highlight_pre_tag": highlight_pre_tag,
"highlight_post_tag": highlight_post_tag,
"max_attributes_to_crop": max_attributes_to_crop,
"crop_marker": crop_marker,
"show_matches_position": show_matches_position,
"crop_length": crop_length,
},
"facets": {
"avg_facets_number": format!("{:.2}", facets_sum_of_terms as f64 / facets_total_number_of_facets as f64),
},
"matching_strategy": {
"most_used_strategy": matching_strategy.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"locales": locales,
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
"ranking_score_threshold": ranking_score_threshold,
},
})
}
}
#[derive(Default)]
pub struct MultiSearchAggregator {
// requests
total_received: usize,
total_succeeded: usize,
// sum of the number of distinct indexes in each single request, use with total_received to compute an avg
total_distinct_index_count: usize,
// number of queries with a single index, use with total_received to compute a proportion
total_single_index: usize,
// sum of the number of search queries in the requests, use with total_received to compute an average
total_search_count: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
// federation
use_federation: bool,
}
impl MultiSearchAggregator {
pub fn from_federated_search(federated_search: &FederatedSearch) -> Self {
let use_federation = federated_search.federation.is_some();
let distinct_indexes: HashSet<_> = federated_search
.queries
.iter()
.map(|query| {
let query = &query;
// make sure we get a compilation error if a field gets added to / removed from SearchQueryWithIndex
let SearchQueryWithIndex {
index_uid,
federation_options: _,
q: _,
vector: _,
offset: _,
limit: _,
page: _,
hits_per_page: _,
attributes_to_retrieve: _,
retrieve_vectors: _,
attributes_to_crop: _,
crop_length: _,
attributes_to_highlight: _,
show_ranking_score: _,
show_ranking_score_details: _,
show_matches_position: _,
filter: _,
sort: _,
distinct: _,
facets: _,
highlight_pre_tag: _,
highlight_post_tag: _,
crop_marker: _,
matching_strategy: _,
attributes_to_search_on: _,
hybrid: _,
ranking_score_threshold: _,
locales: _,
} = query;
index_uid.as_str()
})
.collect();
let show_ranking_score =
federated_search.queries.iter().any(|query| query.show_ranking_score);
let show_ranking_score_details =
federated_search.queries.iter().any(|query| query.show_ranking_score_details);
Self {
total_received: 1,
total_succeeded: 0,
total_distinct_index_count: distinct_indexes.len(),
total_single_index: if distinct_indexes.len() == 1 { 1 } else { 0 },
total_search_count: federated_search.queries.len(),
show_ranking_score,
show_ranking_score_details,
use_federation,
}
}
pub fn succeed(&mut self) {
self.total_succeeded = self.total_succeeded.saturating_add(1);
}
}
impl Aggregate for MultiSearchAggregator {
fn event_name(&self) -> &'static str {
"Documents Searched by Multi-Search POST"
}
/// Aggregate one [MultiSearchAggregator] into another.
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
// write the aggregate in a way that will cause a compilation error if a field is added.
// get ownership of self, replacing it by a default value.
let this = *self;
let total_received = this.total_received.saturating_add(new.total_received);
let total_succeeded = this.total_succeeded.saturating_add(new.total_succeeded);
let total_distinct_index_count =
this.total_distinct_index_count.saturating_add(new.total_distinct_index_count);
let total_single_index = this.total_single_index.saturating_add(new.total_single_index);
let total_search_count = this.total_search_count.saturating_add(new.total_search_count);
let show_ranking_score = this.show_ranking_score || new.show_ranking_score;
let show_ranking_score_details =
this.show_ranking_score_details || new.show_ranking_score_details;
let use_federation = this.use_federation || new.use_federation;
Box::new(Self {
total_received,
total_succeeded,
total_distinct_index_count,
total_single_index,
total_search_count,
show_ranking_score,
show_ranking_score_details,
use_federation,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
total_distinct_index_count,
total_single_index,
total_search_count,
show_ranking_score,
show_ranking_score_details,
use_federation,
} = *self;
json!({
"requests": {
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
},
"indexes": {
"total_single_index": total_single_index,
"total_distinct_index_count": total_distinct_index_count,
"avg_distinct_index_count": (total_distinct_index_count as f64) / (total_received as f64), // not 0 else returned early
},
"searches": {
"total_search_count": total_search_count,
"avg_search_count": (total_search_count as f64) / (total_received as f64),
},
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
},
"federation": {
"use_federation": use_federation,
}
})
}
}
aggregate_methods!(
SimilarPOST => "Similar POST",
SimilarGET => "Similar GET",
);
#[derive(Default)]
pub struct SimilarAggregator<Method: AggregateMethod> {
// requests
total_received: usize,
total_succeeded: usize,
time_spent: BinaryHeap<usize>,
// filter
filter_with_geo_radius: bool,
filter_with_geo_bounding_box: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
filter_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
filter_total_number_of_criteria: usize,
used_syntax: HashMap<String, usize>,
// Whether a non-default embedder was specified
retrieve_vectors: bool,
// pagination
max_limit: usize,
max_offset: usize,
// formatting
max_attributes_to_retrieve: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
ranking_score_threshold: bool,
marker: std::marker::PhantomData<Method>,
}
impl<Method: AggregateMethod> SimilarAggregator<Method> {
#[allow(clippy::field_reassign_with_default)]
pub fn from_query(query: &SimilarQuery) -> Self {
let SimilarQuery {
id: _,
embedder: _,
offset,
limit,
attributes_to_retrieve: _,
retrieve_vectors,
show_ranking_score,
show_ranking_score_details,
filter,
ranking_score_threshold,
} = query;
let mut ret = Self::default();
ret.total_received = 1;
if let Some(ref filter) = filter {
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
ret.filter_total_number_of_criteria = 1;
let syntax = match filter {
Value::String(_) => "string".to_string(),
Value::Array(values) => {
if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
"mixed".to_string()
} else {
"array".to_string()
}
}
_ => "none".to_string(),
};
// convert the string to a HashMap
ret.used_syntax.insert(syntax, 1);
let stringified_filters = filter.to_string();
ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
}
ret.max_limit = *limit;
ret.max_offset = *offset;
ret.show_ranking_score = *show_ranking_score;
ret.show_ranking_score_details = *show_ranking_score_details;
ret.ranking_score_threshold = ranking_score_threshold.is_some();
ret.retrieve_vectors = *retrieve_vectors;
ret
}
pub fn succeed(&mut self, result: &SimilarResult) {
let SimilarResult { id: _, hits: _, processing_time_ms, hits_info: _ } = result;
self.total_succeeded = self.total_succeeded.saturating_add(1);
self.time_spent.push(*processing_time_ms as usize);
}
}
impl<Method: AggregateMethod> Aggregate for SimilarAggregator<Method> {
fn event_name(&self) -> &'static str {
Method::event_name()
}
/// Aggregate one [SimilarAggregator] into another.
fn aggregate(mut self: Box<Self>, new: Box<Self>) -> Box<Self> {
let Self {
total_received,
total_succeeded,
mut time_spent,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
max_limit,
max_offset,
max_attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
ranking_score_threshold,
retrieve_vectors,
marker: _,
} = *new;
// request
self.total_received = self.total_received.saturating_add(total_received);
self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
self.time_spent.append(&mut time_spent);
// filter
self.filter_with_geo_radius |= filter_with_geo_radius;
self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
self.filter_sum_of_criteria_terms =
self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
self.filter_total_number_of_criteria =
self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
for (key, value) in used_syntax.into_iter() {
let used_syntax = self.used_syntax.entry(key).or_insert(0);
*used_syntax = used_syntax.saturating_add(value);
}
self.retrieve_vectors |= retrieve_vectors;
// pagination
self.max_limit = self.max_limit.max(max_limit);
self.max_offset = self.max_offset.max(max_offset);
// formatting
self.max_attributes_to_retrieve =
self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
// scoring
self.show_ranking_score |= show_ranking_score;
self.show_ranking_score_details |= show_ranking_score_details;
self.ranking_score_threshold |= ranking_score_threshold;
self
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
time_spent,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
max_limit,
max_offset,
max_attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
ranking_score_threshold,
retrieve_vectors,
marker: _,
} = *self;
// we get all the values in a sorted manner
let time_spent = time_spent.into_sorted_vec();
// the index of the 99th percentage of value
let percentile_99th = time_spent.len() * 99 / 100;
// We are only interested by the slowest value of the 99th fastest results
let time_spent = time_spent.get(percentile_99th);
json!({
"requests": {
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
},
"filter": {
"with_geoRadius": filter_with_geo_radius,
"with_geoBoundingBox": filter_with_geo_bounding_box,
"avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
"most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"vector": {
"retrieve_vectors": retrieve_vectors,
},
"pagination": {
"max_limit": max_limit,
"max_offset": max_offset,
},
"formatting": {
"max_attributes_to_retrieve": max_attributes_to_retrieve,
},
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
"ranking_score_threshold": ranking_score_threshold,
}
})
}
}

2
meilisearch/src/routes/indexes/mod.rs
View File

@ -28,9 +28,11 @@ use crate::Opt;
pub mod documents;
pub mod facet_search;
pub mod search;
mod search_analytics;
pub mod settings;
mod settings_analytics;
pub mod similar;
mod similar_analytics;
pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(

4
meilisearch/src/routes/indexes/search.rs
View File

@ -13,13 +13,13 @@ use meilisearch_types::serde_cs::vec::CS;
use serde_json::Value;
use tracing::debug;
use crate::analytics::segment_analytics::{SearchGET, SearchPOST};
use crate::analytics::{Analytics, SearchAggregator};
use crate::analytics::Analytics;
use crate::error::MeilisearchHttpError;
use crate::extractors::authentication::policies::*;
use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
use crate::metrics::MEILISEARCH_DEGRADED_SEARCH_REQUESTS;
use crate::routes::indexes::search_analytics::{SearchAggregator, SearchGET, SearchPOST};
use crate::search::{
add_search_rules, perform_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
RetrieveVectors, SearchKind, SearchQuery, SemanticRatio, DEFAULT_CROP_LENGTH,

485
meilisearch/src/routes/indexes/search_analytics.rs Normal file
View File

@ -0,0 +1,485 @@
use once_cell::sync::Lazy;
use regex::Regex;
use serde_json::{json, Value};
use std::collections::{BTreeSet, BinaryHeap, HashMap};
use meilisearch_types::locales::Locale;
use crate::{
aggregate_methods,
analytics::{Aggregate, AggregateMethod},
search::{
SearchQuery, SearchResult, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER,
DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT,
DEFAULT_SEMANTIC_RATIO,
},
};
aggregate_methods!(
SearchGET => "Documents Searched GET",
SearchPOST => "Documents Searched POST",
);
#[derive(Default)]
pub struct SearchAggregator<Method: AggregateMethod> {
// requests
total_received: usize,
total_succeeded: usize,
total_degraded: usize,
total_used_negative_operator: usize,
time_spent: BinaryHeap<usize>,
// sort
sort_with_geo_point: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
sort_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
sort_total_number_of_criteria: usize,
// distinct
distinct: bool,
// filter
filter_with_geo_radius: bool,
filter_with_geo_bounding_box: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
filter_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
filter_total_number_of_criteria: usize,
used_syntax: HashMap<String, usize>,
// attributes_to_search_on
// every time a search is done using attributes_to_search_on
attributes_to_search_on_total_number_of_uses: usize,
// q
// The maximum number of terms in a q request
max_terms_number: usize,
// vector
// The maximum number of floats in a vector request
max_vector_size: usize,
// Whether the semantic ratio passed to a hybrid search equals the default ratio.
semantic_ratio: bool,
hybrid: bool,
retrieve_vectors: bool,
// every time a search is done, we increment the counter linked to the used settings
matching_strategy: HashMap<String, usize>,
// List of the unique Locales passed as parameter
locales: BTreeSet<Locale>,
// pagination
max_limit: usize,
max_offset: usize,
finite_pagination: usize,
// formatting
max_attributes_to_retrieve: usize,
max_attributes_to_highlight: usize,
highlight_pre_tag: bool,
highlight_post_tag: bool,
max_attributes_to_crop: usize,
crop_marker: bool,
show_matches_position: bool,
crop_length: bool,
// facets
facets_sum_of_terms: usize,
facets_total_number_of_facets: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
ranking_score_threshold: bool,
marker: std::marker::PhantomData<Method>,
}
impl<Method: AggregateMethod> SearchAggregator<Method> {
#[allow(clippy::field_reassign_with_default)]
pub fn from_query(query: &SearchQuery) -> Self {
let SearchQuery {
q,
vector,
offset,
limit,
page,
hits_per_page,
attributes_to_retrieve: _,
retrieve_vectors,
attributes_to_crop: _,
crop_length,
attributes_to_highlight: _,
show_matches_position,
show_ranking_score,
show_ranking_score_details,
filter,
sort,
distinct,
facets: _,
highlight_pre_tag,
highlight_post_tag,
crop_marker,
matching_strategy,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
locales,
} = query;
let mut ret = Self::default();
ret.total_received = 1;
if let Some(ref sort) = sort {
ret.sort_total_number_of_criteria = 1;
ret.sort_with_geo_point = sort.iter().any(|s| s.contains("_geoPoint("));
ret.sort_sum_of_criteria_terms = sort.len();
}
ret.distinct = distinct.is_some();
if let Some(ref filter) = filter {
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
ret.filter_total_number_of_criteria = 1;
let syntax = match filter {
Value::String(_) => "string".to_string(),
Value::Array(values) => {
if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
"mixed".to_string()
} else {
"array".to_string()
}
}
_ => "none".to_string(),
};
// convert the string to a HashMap
ret.used_syntax.insert(syntax, 1);
let stringified_filters = filter.to_string();
ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
}
// attributes_to_search_on
if attributes_to_search_on.is_some() {
ret.attributes_to_search_on_total_number_of_uses = 1;
}
if let Some(ref q) = q {
ret.max_terms_number = q.split_whitespace().count();
}
if let Some(ref vector) = vector {
ret.max_vector_size = vector.len();
}
ret.retrieve_vectors |= retrieve_vectors;
if query.is_finite_pagination() {
let limit = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
ret.max_limit = limit;
ret.max_offset = page.unwrap_or(1).saturating_sub(1) * limit;
ret.finite_pagination = 1;
} else {
ret.max_limit = *limit;
ret.max_offset = *offset;
ret.finite_pagination = 0;
}
ret.matching_strategy.insert(format!("{:?}", matching_strategy), 1);
if let Some(locales) = locales {
ret.locales = locales.iter().copied().collect();
}
ret.highlight_pre_tag = *highlight_pre_tag != DEFAULT_HIGHLIGHT_PRE_TAG();
ret.highlight_post_tag = *highlight_post_tag != DEFAULT_HIGHLIGHT_POST_TAG();
ret.crop_marker = *crop_marker != DEFAULT_CROP_MARKER();
ret.crop_length = *crop_length != DEFAULT_CROP_LENGTH();
ret.show_matches_position = *show_matches_position;
ret.show_ranking_score = *show_ranking_score;
ret.show_ranking_score_details = *show_ranking_score_details;
ret.ranking_score_threshold = ranking_score_threshold.is_some();
if let Some(hybrid) = hybrid {
ret.semantic_ratio = hybrid.semantic_ratio != DEFAULT_SEMANTIC_RATIO();
ret.hybrid = true;
}
ret
}
pub fn succeed(&mut self, result: &SearchResult) {
let SearchResult {
hits: _,
query: _,
processing_time_ms,
hits_info: _,
semantic_hit_count: _,
facet_distribution: _,
facet_stats: _,
degraded,
used_negative_operator,
} = result;
self.total_succeeded = self.total_succeeded.saturating_add(1);
if *degraded {
self.total_degraded = self.total_degraded.saturating_add(1);
}
if *used_negative_operator {
self.total_used_negative_operator = self.total_used_negative_operator.saturating_add(1);
}
self.time_spent.push(*processing_time_ms as usize);
}
}
impl<Method: AggregateMethod> Aggregate for SearchAggregator<Method> {
fn event_name(&self) -> &'static str {
Method::event_name()
}
fn aggregate(mut self: Box<Self>, new: Box<Self>) -> Box<Self> {
let Self {
total_received,
total_succeeded,
mut time_spent,
sort_with_geo_point,
sort_sum_of_criteria_terms,
sort_total_number_of_criteria,
distinct,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
attributes_to_search_on_total_number_of_uses,
max_terms_number,
max_vector_size,
retrieve_vectors,
matching_strategy,
max_limit,
max_offset,
finite_pagination,
max_attributes_to_retrieve,
max_attributes_to_highlight,
highlight_pre_tag,
highlight_post_tag,
max_attributes_to_crop,
crop_marker,
show_matches_position,
crop_length,
facets_sum_of_terms,
facets_total_number_of_facets,
show_ranking_score,
show_ranking_score_details,
semantic_ratio,
hybrid,
total_degraded,
total_used_negative_operator,
ranking_score_threshold,
mut locales,
marker: _,
} = *new;
// request
self.total_received = self.total_received.saturating_add(total_received);
self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
self.total_degraded = self.total_degraded.saturating_add(total_degraded);
self.total_used_negative_operator =
self.total_used_negative_operator.saturating_add(total_used_negative_operator);
self.time_spent.append(&mut time_spent);
// sort
self.sort_with_geo_point |= sort_with_geo_point;
self.sort_sum_of_criteria_terms =
self.sort_sum_of_criteria_terms.saturating_add(sort_sum_of_criteria_terms);
self.sort_total_number_of_criteria =
self.sort_total_number_of_criteria.saturating_add(sort_total_number_of_criteria);
// distinct
self.distinct |= distinct;
// filter
self.filter_with_geo_radius |= filter_with_geo_radius;
self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
self.filter_sum_of_criteria_terms =
self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
self.filter_total_number_of_criteria =
self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
for (key, value) in used_syntax.into_iter() {
let used_syntax = self.used_syntax.entry(key).or_insert(0);
*used_syntax = used_syntax.saturating_add(value);
}
// attributes_to_search_on
self.attributes_to_search_on_total_number_of_uses = self
.attributes_to_search_on_total_number_of_uses
.saturating_add(attributes_to_search_on_total_number_of_uses);
// q
self.max_terms_number = self.max_terms_number.max(max_terms_number);
// vector
self.max_vector_size = self.max_vector_size.max(max_vector_size);
self.retrieve_vectors |= retrieve_vectors;
self.semantic_ratio |= semantic_ratio;
self.hybrid |= hybrid;
// pagination
self.max_limit = self.max_limit.max(max_limit);
self.max_offset = self.max_offset.max(max_offset);
self.finite_pagination += finite_pagination;
// formatting
self.max_attributes_to_retrieve =
self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
self.max_attributes_to_highlight =
self.max_attributes_to_highlight.max(max_attributes_to_highlight);
self.highlight_pre_tag |= highlight_pre_tag;
self.highlight_post_tag |= highlight_post_tag;
self.max_attributes_to_crop = self.max_attributes_to_crop.max(max_attributes_to_crop);
self.crop_marker |= crop_marker;
self.show_matches_position |= show_matches_position;
self.crop_length |= crop_length;
// facets
self.facets_sum_of_terms = self.facets_sum_of_terms.saturating_add(facets_sum_of_terms);
self.facets_total_number_of_facets =
self.facets_total_number_of_facets.saturating_add(facets_total_number_of_facets);
// matching strategy
for (key, value) in matching_strategy.into_iter() {
let matching_strategy = self.matching_strategy.entry(key).or_insert(0);
*matching_strategy = matching_strategy.saturating_add(value);
}
// scoring
self.show_ranking_score |= show_ranking_score;
self.show_ranking_score_details |= show_ranking_score_details;
self.ranking_score_threshold |= ranking_score_threshold;
// locales
self.locales.append(&mut locales);
self
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
time_spent,
sort_with_geo_point,
sort_sum_of_criteria_terms,
sort_total_number_of_criteria,
distinct,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
attributes_to_search_on_total_number_of_uses,
max_terms_number,
max_vector_size,
retrieve_vectors,
matching_strategy,
max_limit,
max_offset,
finite_pagination,
max_attributes_to_retrieve,
max_attributes_to_highlight,
highlight_pre_tag,
highlight_post_tag,
max_attributes_to_crop,
crop_marker,
show_matches_position,
crop_length,
facets_sum_of_terms,
facets_total_number_of_facets,
show_ranking_score,
show_ranking_score_details,
semantic_ratio,
hybrid,
total_degraded,
total_used_negative_operator,
ranking_score_threshold,
locales,
marker: _,
} = *self;
// we get all the values in a sorted manner
let time_spent = time_spent.into_sorted_vec();
// the index of the 99th percentage of value
let percentile_99th = time_spent.len() * 99 / 100;
// We are only interested by the slowest value of the 99th fastest results
let time_spent = time_spent.get(percentile_99th);
json!({
"requests": {
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
"total_degraded": total_degraded,
"total_used_negative_operator": total_used_negative_operator,
},
"sort": {
"with_geoPoint": sort_with_geo_point,
"avg_criteria_number": format!("{:.2}", sort_sum_of_criteria_terms as f64 / sort_total_number_of_criteria as f64),
},
"distinct": distinct,
"filter": {
"with_geoRadius": filter_with_geo_radius,
"with_geoBoundingBox": filter_with_geo_bounding_box,
"avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
"most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"attributes_to_search_on": {
"total_number_of_uses": attributes_to_search_on_total_number_of_uses,
},
"q": {
"max_terms_number": max_terms_number,
},
"vector": {
"max_vector_size": max_vector_size,
"retrieve_vectors": retrieve_vectors,
},
"hybrid": {
"enabled": hybrid,
"semantic_ratio": semantic_ratio,
},
"pagination": {
"max_limit": max_limit,
"max_offset": max_offset,
"most_used_navigation": if finite_pagination > (total_received / 2) { "exhaustive" } else { "estimated" },
},
"formatting": {
"max_attributes_to_retrieve": max_attributes_to_retrieve,
"max_attributes_to_highlight": max_attributes_to_highlight,
"highlight_pre_tag": highlight_pre_tag,
"highlight_post_tag": highlight_post_tag,
"max_attributes_to_crop": max_attributes_to_crop,
"crop_marker": crop_marker,
"show_matches_position": show_matches_position,
"crop_length": crop_length,
},
"facets": {
"avg_facets_number": format!("{:.2}", facets_sum_of_terms as f64 / facets_total_number_of_facets as f64),
},
"matching_strategy": {
"most_used_strategy": matching_strategy.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"locales": locales,
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
"ranking_score_threshold": ranking_score_threshold,
},
})
}
}

4
meilisearch/src/routes/indexes/similar.rs
View File

@ -13,10 +13,10 @@ use serde_json::Value;
use tracing::debug;
use super::ActionPolicy;
use crate::analytics::segment_analytics::{SimilarGET, SimilarPOST};
use crate::analytics::{Analytics, SimilarAggregator};
use crate::analytics::Analytics;
use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
use crate::routes::indexes::similar_analytics::{SimilarAggregator, SimilarGET, SimilarPOST};
use crate::search::{
add_search_rules, perform_similar, RankingScoreThresholdSimilar, RetrieveVectors, SearchKind,
SimilarQuery, SimilarResult, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,

235
meilisearch/src/routes/indexes/similar_analytics.rs Normal file
View File

@ -0,0 +1,235 @@
use std::collections::{BinaryHeap, HashMap};
use once_cell::sync::Lazy;
use regex::Regex;
use serde_json::{json, Value};
use crate::{
aggregate_methods,
analytics::{Aggregate, AggregateMethod},
search::{SimilarQuery, SimilarResult},
};
aggregate_methods!(
SimilarPOST => "Similar POST",
SimilarGET => "Similar GET",
);
#[derive(Default)]
pub struct SimilarAggregator<Method: AggregateMethod> {
// requests
total_received: usize,
total_succeeded: usize,
time_spent: BinaryHeap<usize>,
// filter
filter_with_geo_radius: bool,
filter_with_geo_bounding_box: bool,
// every time a request has a filter, this field must be incremented by the number of terms it contains
filter_sum_of_criteria_terms: usize,
// every time a request has a filter, this field must be incremented by one
filter_total_number_of_criteria: usize,
used_syntax: HashMap<String, usize>,
// Whether a non-default embedder was specified
retrieve_vectors: bool,
// pagination
max_limit: usize,
max_offset: usize,
// formatting
max_attributes_to_retrieve: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
ranking_score_threshold: bool,
marker: std::marker::PhantomData<Method>,
}
impl<Method: AggregateMethod> SimilarAggregator<Method> {
#[allow(clippy::field_reassign_with_default)]
pub fn from_query(query: &SimilarQuery) -> Self {
let SimilarQuery {
id: _,
embedder: _,
offset,
limit,
attributes_to_retrieve: _,
retrieve_vectors,
show_ranking_score,
show_ranking_score_details,
filter,
ranking_score_threshold,
} = query;
let mut ret = Self::default();
ret.total_received = 1;
if let Some(ref filter) = filter {
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
ret.filter_total_number_of_criteria = 1;
let syntax = match filter {
Value::String(_) => "string".to_string(),
Value::Array(values) => {
if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
"mixed".to_string()
} else {
"array".to_string()
}
}
_ => "none".to_string(),
};
// convert the string to a HashMap
ret.used_syntax.insert(syntax, 1);
let stringified_filters = filter.to_string();
ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
}
ret.max_limit = *limit;
ret.max_offset = *offset;
ret.show_ranking_score = *show_ranking_score;
ret.show_ranking_score_details = *show_ranking_score_details;
ret.ranking_score_threshold = ranking_score_threshold.is_some();
ret.retrieve_vectors = *retrieve_vectors;
ret
}
pub fn succeed(&mut self, result: &SimilarResult) {
let SimilarResult { id: _, hits: _, processing_time_ms, hits_info: _ } = result;
self.total_succeeded = self.total_succeeded.saturating_add(1);
self.time_spent.push(*processing_time_ms as usize);
}
}
impl<Method: AggregateMethod> Aggregate for SimilarAggregator<Method> {
fn event_name(&self) -> &'static str {
Method::event_name()
}
/// Aggregate one [SimilarAggregator] into another.
fn aggregate(mut self: Box<Self>, new: Box<Self>) -> Box<Self> {
let Self {
total_received,
total_succeeded,
mut time_spent,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
max_limit,
max_offset,
max_attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
ranking_score_threshold,
retrieve_vectors,
marker: _,
} = *new;
// request
self.total_received = self.total_received.saturating_add(total_received);
self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
self.time_spent.append(&mut time_spent);
// filter
self.filter_with_geo_radius |= filter_with_geo_radius;
self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
self.filter_sum_of_criteria_terms =
self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
self.filter_total_number_of_criteria =
self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
for (key, value) in used_syntax.into_iter() {
let used_syntax = self.used_syntax.entry(key).or_insert(0);
*used_syntax = used_syntax.saturating_add(value);
}
self.retrieve_vectors |= retrieve_vectors;
// pagination
self.max_limit = self.max_limit.max(max_limit);
self.max_offset = self.max_offset.max(max_offset);
// formatting
self.max_attributes_to_retrieve =
self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
// scoring
self.show_ranking_score |= show_ranking_score;
self.show_ranking_score_details |= show_ranking_score_details;
self.ranking_score_threshold |= ranking_score_threshold;
self
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
time_spent,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
filter_total_number_of_criteria,
used_syntax,
max_limit,
max_offset,
max_attributes_to_retrieve,
show_ranking_score,
show_ranking_score_details,
ranking_score_threshold,
retrieve_vectors,
marker: _,
} = *self;
// we get all the values in a sorted manner
let time_spent = time_spent.into_sorted_vec();
// the index of the 99th percentage of value
let percentile_99th = time_spent.len() * 99 / 100;
// We are only interested by the slowest value of the 99th fastest results
let time_spent = time_spent.get(percentile_99th);
json!({
"requests": {
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
},
"filter": {
"with_geoRadius": filter_with_geo_radius,
"with_geoBoundingBox": filter_with_geo_bounding_box,
"avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
"most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
},
"vector": {
"retrieve_vectors": retrieve_vectors,
},
"pagination": {
"max_limit": max_limit,
"max_offset": max_offset,
},
"formatting": {
"max_attributes_to_retrieve": max_attributes_to_retrieve,
},
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
"ranking_score_threshold": ranking_score_threshold,
}
})
}
}

1
meilisearch/src/routes/mod.rs
View File

@ -25,6 +25,7 @@ pub mod indexes;
mod logs;
mod metrics;
mod multi_search;
mod multi_search_analytics;
mod snapshot;
mod swap_indexes;
pub mod tasks;

4
meilisearch/src/routes/multi_search.rs
View File

@ -9,7 +9,7 @@ use meilisearch_types::keys::actions;
use serde::Serialize;
use tracing::debug;
use crate::analytics::{Analytics, MultiSearchAggregator};
use crate::analytics::Analytics;
use crate::error::MeilisearchHttpError;
use crate::extractors::authentication::policies::ActionPolicy;
use crate::extractors::authentication::{AuthenticationError, GuardedData};
@ -21,6 +21,8 @@ use crate::search::{
};
use crate::search_queue::SearchQueue;
use super::multi_search_analytics::MultiSearchAggregator;
pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(web::resource("").route(web::post().to(SeqHandler(multi_search_with_post))));
}

170
meilisearch/src/routes/multi_search_analytics.rs Normal file
View File

@ -0,0 +1,170 @@
use std::collections::HashSet;
use serde_json::json;
use crate::{
analytics::Aggregate,
search::{FederatedSearch, SearchQueryWithIndex},
};
#[derive(Default)]
pub struct MultiSearchAggregator {
// requests
total_received: usize,
total_succeeded: usize,
// sum of the number of distinct indexes in each single request, use with total_received to compute an avg
total_distinct_index_count: usize,
// number of queries with a single index, use with total_received to compute a proportion
total_single_index: usize,
// sum of the number of search queries in the requests, use with total_received to compute an average
total_search_count: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
// federation
use_federation: bool,
}
impl MultiSearchAggregator {
pub fn from_federated_search(federated_search: &FederatedSearch) -> Self {
let use_federation = federated_search.federation.is_some();
let distinct_indexes: HashSet<_> = federated_search
.queries
.iter()
.map(|query| {
let query = &query;
// make sure we get a compilation error if a field gets added to / removed from SearchQueryWithIndex
let SearchQueryWithIndex {
index_uid,
federation_options: _,
q: _,
vector: _,
offset: _,
limit: _,
page: _,
hits_per_page: _,
attributes_to_retrieve: _,
retrieve_vectors: _,
attributes_to_crop: _,
crop_length: _,
attributes_to_highlight: _,
show_ranking_score: _,
show_ranking_score_details: _,
show_matches_position: _,
filter: _,
sort: _,
distinct: _,
facets: _,
highlight_pre_tag: _,
highlight_post_tag: _,
crop_marker: _,
matching_strategy: _,
attributes_to_search_on: _,
hybrid: _,
ranking_score_threshold: _,
locales: _,
} = query;
index_uid.as_str()
})
.collect();
let show_ranking_score =
federated_search.queries.iter().any(|query| query.show_ranking_score);
let show_ranking_score_details =
federated_search.queries.iter().any(|query| query.show_ranking_score_details);
Self {
total_received: 1,
total_succeeded: 0,
total_distinct_index_count: distinct_indexes.len(),
total_single_index: if distinct_indexes.len() == 1 { 1 } else { 0 },
total_search_count: federated_search.queries.len(),
show_ranking_score,
show_ranking_score_details,
use_federation,
}
}
pub fn succeed(&mut self) {
self.total_succeeded = self.total_succeeded.saturating_add(1);
}
}
impl Aggregate for MultiSearchAggregator {
fn event_name(&self) -> &'static str {
"Documents Searched by Multi-Search POST"
}
/// Aggregate one [MultiSearchAggregator] into another.
fn aggregate(self: Box<Self>, new: Box<Self>) -> Box<Self> {
// write the aggregate in a way that will cause a compilation error if a field is added.
// get ownership of self, replacing it by a default value.
let this = *self;
let total_received = this.total_received.saturating_add(new.total_received);
let total_succeeded = this.total_succeeded.saturating_add(new.total_succeeded);
let total_distinct_index_count =
this.total_distinct_index_count.saturating_add(new.total_distinct_index_count);
let total_single_index = this.total_single_index.saturating_add(new.total_single_index);
let total_search_count = this.total_search_count.saturating_add(new.total_search_count);
let show_ranking_score = this.show_ranking_score || new.show_ranking_score;
let show_ranking_score_details =
this.show_ranking_score_details || new.show_ranking_score_details;
let use_federation = this.use_federation || new.use_federation;
Box::new(Self {
total_received,
total_succeeded,
total_distinct_index_count,
total_single_index,
total_search_count,
show_ranking_score,
show_ranking_score_details,
use_federation,
})
}
fn into_event(self: Box<Self>) -> serde_json::Value {
let Self {
total_received,
total_succeeded,
total_distinct_index_count,
total_single_index,
total_search_count,
show_ranking_score,
show_ranking_score_details,
use_federation,
} = *self;
json!({
"requests": {
"total_succeeded": total_succeeded,
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
"total_received": total_received,
},
"indexes": {
"total_single_index": total_single_index,
"total_distinct_index_count": total_distinct_index_count,
"avg_distinct_index_count": (total_distinct_index_count as f64) / (total_received as f64), // not 0 else returned early
},
"searches": {
"total_search_count": total_search_count,
"avg_search_count": (total_search_count as f64) / (total_received as f64),
},
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
},
"federation": {
"use_federation": use_federation,
}
})
}
}