mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-06-16 01:29:51 +02:00
use rust struct destructuring for SearchAggregator
This commit is contained in:
Vivek Kumar
parent
ef31ab52a4
commit
4c641b79a2
|
|
@ -615,19 +615,43 @@ pub struct SearchAggregator {
|
|||
|
||||
impl SearchAggregator {
|
||||
pub fn from_query(query: &SearchQuery, request: &HttpRequest) -> Self {
|
||||
let SearchQuery {
|
||||
q,
|
||||
vector,
|
||||
offset,
|
||||
limit,
|
||||
page,
|
||||
hits_per_page,
|
||||
attributes_to_retrieve: _,
|
||||
attributes_to_crop: _,
|
||||
crop_length,
|
||||
attributes_to_highlight: _,
|
||||
show_matches_position,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
filter,
|
||||
sort,
|
||||
facets: _,
|
||||
highlight_pre_tag,
|
||||
highlight_post_tag,
|
||||
crop_marker,
|
||||
matching_strategy,
|
||||
attributes_to_search_on,
|
||||
} = query;
|
||||
|
||||
let mut ret = Self::default();
|
||||
ret.timestamp = Some(OffsetDateTime::now_utc());
|
||||
|
||||
ret.total_received = 1;
|
||||
ret.user_agents = extract_user_agents(request).into_iter().collect();
|
||||
|
||||
if let Some(ref sort) = query.sort {
|
||||
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();
|
||||
}
|
||||
|
||||
if let Some(ref filter) = query.filter {
|
||||
if let Some(ref filter) = filter {
|
||||
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
|
||||
ret.filter_total_number_of_criteria = 1;
|
||||
|
||||
|
|
@ -652,80 +676,124 @@ impl SearchAggregator {
|
|||
}
|
||||
|
||||
// attributes_to_search_on
|
||||
if let Some(_) = query.attributes_to_search_on {
|
||||
if let Some(_) = attributes_to_search_on {
|
||||
ret.attributes_to_search_on_total_number_of_uses = 1;
|
||||
}
|
||||
|
||||
if let Some(ref q) = query.q {
|
||||
if let Some(ref q) = q {
|
||||
ret.max_terms_number = q.split_whitespace().count();
|
||||
}
|
||||
|
||||
if let Some(ref vector) = query.vector {
|
||||
if let Some(ref vector) = vector {
|
||||
ret.max_vector_size = vector.len();
|
||||
}
|
||||
|
||||
if query.is_finite_pagination() {
|
||||
let limit = query.hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
|
||||
let limit = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
|
||||
ret.max_limit = limit;
|
||||
ret.max_offset = query.page.unwrap_or(1).saturating_sub(1) * limit;
|
||||
ret.max_offset = page.unwrap_or(1).saturating_sub(1) * limit;
|
||||
ret.finite_pagination = 1;
|
||||
} else {
|
||||
ret.max_limit = query.limit;
|
||||
ret.max_offset = query.offset;
|
||||
ret.max_limit = *limit;
|
||||
ret.max_offset = *offset;
|
||||
ret.finite_pagination = 0;
|
||||
}
|
||||
|
||||
ret.matching_strategy.insert(format!("{:?}", query.matching_strategy), 1);
|
||||
ret.matching_strategy.insert(format!("{:?}", matching_strategy), 1);
|
||||
|
||||
ret.highlight_pre_tag = query.highlight_pre_tag != DEFAULT_HIGHLIGHT_PRE_TAG();
|
||||
ret.highlight_post_tag = query.highlight_post_tag != DEFAULT_HIGHLIGHT_POST_TAG();
|
||||
ret.crop_marker = query.crop_marker != DEFAULT_CROP_MARKER();
|
||||
ret.crop_length = query.crop_length != DEFAULT_CROP_LENGTH();
|
||||
ret.show_matches_position = query.show_matches_position;
|
||||
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 = query.show_ranking_score;
|
||||
ret.show_ranking_score_details = query.show_ranking_score_details;
|
||||
ret.show_ranking_score = *show_ranking_score;
|
||||
ret.show_ranking_score_details = *show_ranking_score_details;
|
||||
|
||||
ret
|
||||
}
|
||||
|
||||
pub fn succeed(&mut self, result: &SearchResult) {
|
||||
let SearchResult {
|
||||
hits: _,
|
||||
query: _,
|
||||
vector: _,
|
||||
processing_time_ms,
|
||||
hits_info: _,
|
||||
facet_distribution: _,
|
||||
facet_stats: _,
|
||||
} = result;
|
||||
|
||||
self.total_succeeded = self.total_succeeded.saturating_add(1);
|
||||
self.time_spent.push(result.processing_time_ms as usize);
|
||||
self.time_spent.push(*processing_time_ms as usize);
|
||||
}
|
||||
|
||||
/// Aggregate one [SearchAggregator] into another.
|
||||
pub fn aggregate(&mut self, mut other: Self) {
|
||||
let Self {
|
||||
timestamp,
|
||||
user_agents,
|
||||
total_received,
|
||||
total_succeeded,
|
||||
ref mut time_spent,
|
||||
sort_with_geo_point,
|
||||
sort_sum_of_criteria_terms,
|
||||
sort_total_number_of_criteria,
|
||||
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,
|
||||
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,
|
||||
} = other;
|
||||
|
||||
if self.timestamp.is_none() {
|
||||
self.timestamp = other.timestamp;
|
||||
self.timestamp = timestamp;
|
||||
}
|
||||
|
||||
// context
|
||||
for user_agent in other.user_agents.into_iter() {
|
||||
for user_agent in user_agents.into_iter() {
|
||||
self.user_agents.insert(user_agent);
|
||||
}
|
||||
|
||||
// request
|
||||
self.total_received = self.total_received.saturating_add(other.total_received);
|
||||
self.total_succeeded = self.total_succeeded.saturating_add(other.total_succeeded);
|
||||
self.time_spent.append(&mut other.time_spent);
|
||||
self.total_received = self.total_received.saturating_add(total_received);
|
||||
self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
|
||||
self.time_spent.append(time_spent);
|
||||
|
||||
// sort
|
||||
self.sort_with_geo_point |= other.sort_with_geo_point;
|
||||
self.sort_with_geo_point |= sort_with_geo_point;
|
||||
self.sort_sum_of_criteria_terms =
|
||||
self.sort_sum_of_criteria_terms.saturating_add(other.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(other.sort_total_number_of_criteria);
|
||||
self.sort_total_number_of_criteria.saturating_add(sort_total_number_of_criteria);
|
||||
|
||||
// filter
|
||||
self.filter_with_geo_radius |= other.filter_with_geo_radius;
|
||||
self.filter_with_geo_bounding_box |= other.filter_with_geo_bounding_box;
|
||||
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(other.filter_sum_of_criteria_terms);
|
||||
self.filter_total_number_of_criteria = self
|
||||
.filter_total_number_of_criteria
|
||||
.saturating_add(other.filter_total_number_of_criteria);
|
||||
for (key, value) in other.used_syntax.into_iter() {
|
||||
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);
|
||||
}
|
||||
|
|
@ -733,115 +801,149 @@ impl SearchAggregator {
|
|||
// attributes_to_search_on
|
||||
self.attributes_to_search_on_total_number_of_uses = self
|
||||
.attributes_to_search_on_total_number_of_uses
|
||||
.saturating_add(other.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(other.max_terms_number);
|
||||
self.max_terms_number = self.max_terms_number.max(max_terms_number);
|
||||
|
||||
// vector
|
||||
self.max_vector_size = self.max_vector_size.max(other.max_vector_size);
|
||||
self.max_vector_size = self.max_vector_size.max(max_vector_size);
|
||||
|
||||
// pagination
|
||||
self.max_limit = self.max_limit.max(other.max_limit);
|
||||
self.max_offset = self.max_offset.max(other.max_offset);
|
||||
self.finite_pagination += other.finite_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(other.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(other.max_attributes_to_highlight);
|
||||
self.highlight_pre_tag |= other.highlight_pre_tag;
|
||||
self.highlight_post_tag |= other.highlight_post_tag;
|
||||
self.max_attributes_to_crop = self.max_attributes_to_crop.max(other.max_attributes_to_crop);
|
||||
self.crop_marker |= other.crop_marker;
|
||||
self.show_matches_position |= other.show_matches_position;
|
||||
self.crop_length |= other.crop_length;
|
||||
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(other.facets_sum_of_terms);
|
||||
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(other.facets_total_number_of_facets);
|
||||
self.facets_total_number_of_facets.saturating_add(facets_total_number_of_facets);
|
||||
|
||||
// matching strategy
|
||||
for (key, value) in other.matching_strategy.into_iter() {
|
||||
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 |= other.show_ranking_score;
|
||||
self.show_ranking_score_details |= other.show_ranking_score_details;
|
||||
self.show_ranking_score |= show_ranking_score;
|
||||
self.show_ranking_score_details |= show_ranking_score_details;
|
||||
}
|
||||
|
||||
pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
|
||||
let Self {
|
||||
timestamp,
|
||||
user_agents,
|
||||
total_received,
|
||||
total_succeeded,
|
||||
time_spent,
|
||||
sort_with_geo_point,
|
||||
sort_sum_of_criteria_terms,
|
||||
sort_total_number_of_criteria,
|
||||
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,
|
||||
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,
|
||||
} = self;
|
||||
|
||||
if self.total_received == 0 {
|
||||
None
|
||||
} else {
|
||||
// we get all the values in a sorted manner
|
||||
let time_spent = self.time_spent.into_sorted_vec();
|
||||
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);
|
||||
|
||||
let properties = json!({
|
||||
"user-agent": self.user_agents,
|
||||
"user-agent": user_agents,
|
||||
"requests": {
|
||||
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
|
||||
"total_succeeded": self.total_succeeded,
|
||||
"total_failed": self.total_received.saturating_sub(self.total_succeeded), // just to be sure we never panics
|
||||
"total_received": self.total_received,
|
||||
"total_succeeded": total_succeeded,
|
||||
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
|
||||
"total_received": total_received,
|
||||
},
|
||||
"sort": {
|
||||
"with_geoPoint": self.sort_with_geo_point,
|
||||
"avg_criteria_number": format!("{:.2}", self.sort_sum_of_criteria_terms as f64 / self.sort_total_number_of_criteria as f64),
|
||||
"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),
|
||||
},
|
||||
"filter": {
|
||||
"with_geoRadius": self.filter_with_geo_radius,
|
||||
"with_geoBoundingBox": self.filter_with_geo_bounding_box,
|
||||
"avg_criteria_number": format!("{:.2}", self.filter_sum_of_criteria_terms as f64 / self.filter_total_number_of_criteria as f64),
|
||||
"most_used_syntax": self.used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
|
||||
"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": self.attributes_to_search_on_total_number_of_uses,
|
||||
"total_number_of_uses": attributes_to_search_on_total_number_of_uses,
|
||||
},
|
||||
"q": {
|
||||
"max_terms_number": self.max_terms_number,
|
||||
"max_terms_number": max_terms_number,
|
||||
},
|
||||
"vector": {
|
||||
"max_vector_size": self.max_vector_size,
|
||||
"max_vector_size": max_vector_size,
|
||||
},
|
||||
"pagination": {
|
||||
"max_limit": self.max_limit,
|
||||
"max_offset": self.max_offset,
|
||||
"most_used_navigation": if self.finite_pagination > (self.total_received / 2) { "exhaustive" } else { "estimated" },
|
||||
"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": self.max_attributes_to_retrieve,
|
||||
"max_attributes_to_highlight": self.max_attributes_to_highlight,
|
||||
"highlight_pre_tag": self.highlight_pre_tag,
|
||||
"highlight_post_tag": self.highlight_post_tag,
|
||||
"max_attributes_to_crop": self.max_attributes_to_crop,
|
||||
"crop_marker": self.crop_marker,
|
||||
"show_matches_position": self.show_matches_position,
|
||||
"crop_length": self.crop_length,
|
||||
"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}", self.facets_sum_of_terms as f64 / self.facets_total_number_of_facets as f64),
|
||||
"avg_facets_number": format!("{:.2}", facets_sum_of_terms as f64 / facets_total_number_of_facets as f64),
|
||||
},
|
||||
"matching_strategy": {
|
||||
"most_used_strategy": self.matching_strategy.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
|
||||
"most_used_strategy": matching_strategy.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
|
||||
},
|
||||
"scoring": {
|
||||
"show_ranking_score": self.show_ranking_score,
|
||||
"show_ranking_score_details": self.show_ranking_score_details,
|
||||
"show_ranking_score": show_ranking_score,
|
||||
"show_ranking_score_details": show_ranking_score_details,
|
||||
},
|
||||
});
|
||||
|
||||
Some(Track {
|
||||
timestamp: self.timestamp,
|
||||
timestamp: timestamp,
|
||||
user: user.clone(),
|
||||
event: event_name.to_string(),
|
||||
properties,
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user