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https://github.com/meilisearch/meilisearch.git
synced 2024-11-26 03:55:07 +08:00
Analytics changes
This commit is contained in:
parent
d35278320e
commit
54b15059a0
@ -25,6 +25,18 @@ impl SearchAggregator {
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pub fn succeed(&mut self, _: &dyn Any) {}
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}
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#[derive(Default)]
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pub struct SimilarAggregator;
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#[allow(dead_code)]
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impl SimilarAggregator {
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pub fn from_query(_: &dyn Any, _: &dyn Any) -> Self {
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Self
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}
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pub fn succeed(&mut self, _: &dyn Any) {}
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}
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#[derive(Default)]
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pub struct MultiSearchAggregator;
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@ -66,6 +78,8 @@ impl Analytics for MockAnalytics {
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fn publish(&self, _event_name: String, _send: Value, _request: Option<&HttpRequest>) {}
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fn get_search(&self, _aggregate: super::SearchAggregator) {}
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fn post_search(&self, _aggregate: super::SearchAggregator) {}
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fn get_similar(&self, _aggregate: super::SimilarAggregator) {}
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fn post_similar(&self, _aggregate: super::SimilarAggregator) {}
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fn post_multi_search(&self, _aggregate: super::MultiSearchAggregator) {}
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fn post_facet_search(&self, _aggregate: super::FacetSearchAggregator) {}
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fn add_documents(
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@ -22,6 +22,8 @@ pub type SegmentAnalytics = mock_analytics::MockAnalytics;
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#[cfg(not(feature = "analytics"))]
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pub type SearchAggregator = mock_analytics::SearchAggregator;
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#[cfg(not(feature = "analytics"))]
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pub type SimilarAggregator = mock_analytics::SimilarAggregator;
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#[cfg(not(feature = "analytics"))]
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pub type MultiSearchAggregator = mock_analytics::MultiSearchAggregator;
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#[cfg(not(feature = "analytics"))]
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pub type FacetSearchAggregator = mock_analytics::FacetSearchAggregator;
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@ -32,6 +34,8 @@ pub type SegmentAnalytics = segment_analytics::SegmentAnalytics;
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#[cfg(feature = "analytics")]
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pub type SearchAggregator = segment_analytics::SearchAggregator;
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#[cfg(feature = "analytics")]
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pub type SimilarAggregator = segment_analytics::SimilarAggregator;
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#[cfg(feature = "analytics")]
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pub type MultiSearchAggregator = segment_analytics::MultiSearchAggregator;
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#[cfg(feature = "analytics")]
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pub type FacetSearchAggregator = segment_analytics::FacetSearchAggregator;
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@ -86,6 +90,12 @@ pub trait Analytics: Sync + Send {
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/// This method should be called to aggregate a post search
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fn post_search(&self, aggregate: SearchAggregator);
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/// This method should be called to aggregate a get similar request
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fn get_similar(&self, aggregate: SimilarAggregator);
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/// This method should be called to aggregate a post similar request
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fn post_similar(&self, aggregate: SimilarAggregator);
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/// This method should be called to aggregate a post array of searches
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fn post_multi_search(&self, aggregate: MultiSearchAggregator);
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@ -36,8 +36,9 @@ use crate::routes::indexes::facet_search::FacetSearchQuery;
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use crate::routes::{create_all_stats, Stats};
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use crate::search::{
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FacetSearchResult, MatchingStrategy, SearchQuery, SearchQueryWithIndex, SearchResult,
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DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
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DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEMANTIC_RATIO,
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SimilarQuery, SimilarResult, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER,
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DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT,
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DEFAULT_SEMANTIC_RATIO,
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};
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use crate::Opt;
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@ -73,6 +74,8 @@ pub enum AnalyticsMsg {
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BatchMessage(Track),
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AggregateGetSearch(SearchAggregator),
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AggregatePostSearch(SearchAggregator),
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AggregateGetSimilar(SimilarAggregator),
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AggregatePostSimilar(SimilarAggregator),
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AggregatePostMultiSearch(MultiSearchAggregator),
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AggregatePostFacetSearch(FacetSearchAggregator),
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AggregateAddDocuments(DocumentsAggregator),
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@ -149,6 +152,8 @@ impl SegmentAnalytics {
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update_documents_aggregator: DocumentsAggregator::default(),
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get_fetch_documents_aggregator: DocumentsFetchAggregator::default(),
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post_fetch_documents_aggregator: DocumentsFetchAggregator::default(),
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get_similar_aggregator: SimilarAggregator::default(),
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post_similar_aggregator: SimilarAggregator::default(),
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});
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tokio::spawn(segment.run(index_scheduler.clone(), auth_controller.clone()));
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@ -184,6 +189,14 @@ impl super::Analytics for SegmentAnalytics {
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let _ = self.sender.try_send(AnalyticsMsg::AggregatePostSearch(aggregate));
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}
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fn get_similar(&self, aggregate: SimilarAggregator) {
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let _ = self.sender.try_send(AnalyticsMsg::AggregateGetSimilar(aggregate));
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}
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fn post_similar(&self, aggregate: SimilarAggregator) {
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let _ = self.sender.try_send(AnalyticsMsg::AggregatePostSimilar(aggregate));
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}
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fn post_facet_search(&self, aggregate: FacetSearchAggregator) {
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let _ = self.sender.try_send(AnalyticsMsg::AggregatePostFacetSearch(aggregate));
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}
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@ -379,6 +392,8 @@ pub struct Segment {
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update_documents_aggregator: DocumentsAggregator,
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get_fetch_documents_aggregator: DocumentsFetchAggregator,
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post_fetch_documents_aggregator: DocumentsFetchAggregator,
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get_similar_aggregator: SimilarAggregator,
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post_similar_aggregator: SimilarAggregator,
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}
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impl Segment {
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@ -441,6 +456,8 @@ impl Segment {
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Some(AnalyticsMsg::AggregateUpdateDocuments(agreg)) => self.update_documents_aggregator.aggregate(agreg),
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Some(AnalyticsMsg::AggregateGetFetchDocuments(agreg)) => self.get_fetch_documents_aggregator.aggregate(agreg),
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Some(AnalyticsMsg::AggregatePostFetchDocuments(agreg)) => self.post_fetch_documents_aggregator.aggregate(agreg),
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Some(AnalyticsMsg::AggregateGetSimilar(agreg)) => self.get_similar_aggregator.aggregate(agreg),
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Some(AnalyticsMsg::AggregatePostSimilar(agreg)) => self.post_similar_aggregator.aggregate(agreg),
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None => (),
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}
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}
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@ -494,6 +511,8 @@ impl Segment {
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update_documents_aggregator,
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get_fetch_documents_aggregator,
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post_fetch_documents_aggregator,
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get_similar_aggregator,
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post_similar_aggregator,
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} = self;
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if let Some(get_search) =
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@ -541,6 +560,18 @@ impl Segment {
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{
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let _ = self.batcher.push(post_fetch_documents).await;
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}
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if let Some(get_similar_documents) =
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take(get_similar_aggregator).into_event(user, "Similar GET")
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{
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let _ = self.batcher.push(get_similar_documents).await;
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}
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if let Some(post_similar_documents) =
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take(post_similar_aggregator).into_event(user, "Similar POST")
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{
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let _ = self.batcher.push(post_similar_documents).await;
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}
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let _ = self.batcher.flush().await;
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}
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}
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@ -1558,3 +1589,235 @@ impl DocumentsFetchAggregator {
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})
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}
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}
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#[derive(Default)]
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pub struct SimilarAggregator {
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timestamp: Option<OffsetDateTime>,
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// context
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user_agents: HashSet<String>,
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// requests
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total_received: usize,
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total_succeeded: usize,
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time_spent: BinaryHeap<usize>,
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// filter
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filter_with_geo_radius: bool,
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filter_with_geo_bounding_box: bool,
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// every time a request has a filter, this field must be incremented by the number of terms it contains
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filter_sum_of_criteria_terms: usize,
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// every time a request has a filter, this field must be incremented by one
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filter_total_number_of_criteria: usize,
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used_syntax: HashMap<String, usize>,
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// Whether a non-default embedder was specified
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embedder: bool,
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// pagination
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max_limit: usize,
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max_offset: usize,
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// formatting
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max_attributes_to_retrieve: usize,
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// scoring
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show_ranking_score: bool,
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show_ranking_score_details: bool,
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}
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impl SimilarAggregator {
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#[allow(clippy::field_reassign_with_default)]
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pub fn from_query(query: &SimilarQuery, request: &HttpRequest) -> Self {
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let SimilarQuery {
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id: _,
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embedder,
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offset,
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limit,
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attributes_to_retrieve: _,
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show_ranking_score,
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show_ranking_score_details,
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filter,
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} = query;
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let mut ret = Self::default();
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ret.timestamp = Some(OffsetDateTime::now_utc());
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ret.total_received = 1;
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ret.user_agents = extract_user_agents(request).into_iter().collect();
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if let Some(ref filter) = filter {
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static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
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ret.filter_total_number_of_criteria = 1;
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let syntax = match filter {
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Value::String(_) => "string".to_string(),
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Value::Array(values) => {
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if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
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"mixed".to_string()
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} else {
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"array".to_string()
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}
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}
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_ => "none".to_string(),
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};
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// convert the string to a HashMap
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ret.used_syntax.insert(syntax, 1);
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let stringified_filters = filter.to_string();
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ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
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ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
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ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
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}
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ret.max_limit = *limit;
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ret.max_offset = *offset;
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ret.show_ranking_score = *show_ranking_score;
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ret.show_ranking_score_details = *show_ranking_score_details;
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ret.embedder = embedder.is_some();
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ret
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}
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pub fn succeed(&mut self, result: &SimilarResult) {
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let SimilarResult { id: _, hits: _, processing_time_ms, hits_info: _ } = result;
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self.total_succeeded = self.total_succeeded.saturating_add(1);
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self.time_spent.push(*processing_time_ms as usize);
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}
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/// Aggregate one [SimilarAggregator] into another.
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pub fn aggregate(&mut self, mut other: Self) {
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let Self {
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timestamp,
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user_agents,
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total_received,
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total_succeeded,
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ref mut time_spent,
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filter_with_geo_radius,
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filter_with_geo_bounding_box,
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filter_sum_of_criteria_terms,
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filter_total_number_of_criteria,
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used_syntax,
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max_limit,
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max_offset,
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max_attributes_to_retrieve,
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show_ranking_score,
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show_ranking_score_details,
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embedder,
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} = other;
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if self.timestamp.is_none() {
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self.timestamp = timestamp;
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}
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// context
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for user_agent in user_agents.into_iter() {
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self.user_agents.insert(user_agent);
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}
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// request
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self.total_received = self.total_received.saturating_add(total_received);
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self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
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self.time_spent.append(time_spent);
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// filter
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self.filter_with_geo_radius |= filter_with_geo_radius;
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self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
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self.filter_sum_of_criteria_terms =
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self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
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self.filter_total_number_of_criteria =
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self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
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for (key, value) in used_syntax.into_iter() {
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let used_syntax = self.used_syntax.entry(key).or_insert(0);
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*used_syntax = used_syntax.saturating_add(value);
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}
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self.embedder |= embedder;
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// pagination
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self.max_limit = self.max_limit.max(max_limit);
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self.max_offset = self.max_offset.max(max_offset);
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// formatting
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self.max_attributes_to_retrieve =
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self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
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// scoring
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self.show_ranking_score |= show_ranking_score;
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self.show_ranking_score_details |= show_ranking_score_details;
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}
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pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
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let Self {
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timestamp,
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user_agents,
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total_received,
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total_succeeded,
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time_spent,
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filter_with_geo_radius,
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filter_with_geo_bounding_box,
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filter_sum_of_criteria_terms,
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filter_total_number_of_criteria,
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used_syntax,
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max_limit,
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max_offset,
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max_attributes_to_retrieve,
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show_ranking_score,
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show_ranking_score_details,
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embedder,
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} = self;
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if total_received == 0 {
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None
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} else {
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// we get all the values in a sorted manner
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let time_spent = time_spent.into_sorted_vec();
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// the index of the 99th percentage of value
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let percentile_99th = time_spent.len() * 99 / 100;
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// We are only interested by the slowest value of the 99th fastest results
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let time_spent = time_spent.get(percentile_99th);
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let properties = json!({
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"user-agent": user_agents,
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"requests": {
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"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
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"total_succeeded": total_succeeded,
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"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
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"total_received": total_received,
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},
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"filter": {
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"with_geoRadius": filter_with_geo_radius,
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"with_geoBoundingBox": filter_with_geo_bounding_box,
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"avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
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"most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
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},
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"hybrid": {
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"embedder": embedder,
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},
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"pagination": {
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"max_limit": max_limit,
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"max_offset": max_offset,
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},
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"formatting": {
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"max_attributes_to_retrieve": max_attributes_to_retrieve,
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},
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"scoring": {
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"show_ranking_score": show_ranking_score,
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"show_ranking_score_details": show_ranking_score_details,
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},
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});
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Some(Track {
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timestamp,
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user: user.clone(),
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event: event_name.to_string(),
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properties,
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..Default::default()
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})
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}
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}
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}
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