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perf(#12): push suggest() filtering + LIMIT to SQL

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Replace the in-memory approach (list_files → filter in Rust) with
SQL-level ILIKE + relevance ORDER BY + LIMIT.

- Add suggest_files_by_name() to FileReadPort (default impl for stubs)
- Add suggest_folders_by_name() to FolderRepository (default impl)
- Implement efficient SQL in FileBlobReadRepository & FolderDbRepository
  with LOWER(name) LIKE pattern, 3-tier relevance sorting, and LIMIT
- Rewrite SearchService::suggest() to call new methods in parallel

Before: 50K files → ~10 MB transferred, 52K string comparisons
After:  50K files → ~20 rows transferred, index-assisted scan
This commit is contained in:
Dionisio
2026-02-23 23:36:38 +01:00
parent ab0c4476b3
commit 44113eabdc
5 changed files with 240 additions and 39 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/application/services/search_service.rs
+39 -39
View File
@@ -187,7 +187,8 @@ impl SearchService {
}
/// Quick suggestions search — returns up to `limit` name suggestions
/// matching the query prefix. Uses cache-friendly shallow search.
/// matching the query. Pushes filtering, relevance sort and LIMIT to SQL
/// so only a handful of rows cross the DB→app boundary.
pub async fn suggest(
&self,
query: &str,
@@ -195,50 +196,49 @@ impl SearchService {
limit: usize,
) -> Result<SearchSuggestionsDto> {
let start = Instant::now();
let query_lower = query.to_lowercase();
let mut suggestions: Vec<SearchSuggestionItem> = Vec::new();
// Ask SQL for at most `limit` best-matching files and folders
let (files, folders) = tokio::join!(
self.file_repository
.suggest_files_by_name(folder_id, query, limit),
self.folder_repository
.suggest_folders_by_name(folder_id, query, limit),
);
let files = files?;
let folders = folders?;
// List files in the folder
let files = self.file_repository.list_files(folder_id).await?;
for file in files {
let file_dto = FileDto::from(file);
if file_dto.name.to_lowercase().contains(&query_lower) {
let score = compute_relevance(&file_dto.name, query);
suggestions.push(SearchSuggestionItem {
name: file_dto.name.clone(),
item_type: "file".to_string(),
id: file_dto.id.clone(),
path: file_dto.path.clone(),
icon_class: get_icon_class(&file_dto.name, &file_dto.mime_type),
icon_special_class: get_icon_special_class(&file_dto.name, &file_dto.mime_type),
relevance_score: score,
});
}
if suggestions.len() >= limit * 2 {
break; // Collect enough candidates
}
let mut suggestions: Vec<SearchSuggestionItem> =
Vec::with_capacity(files.len() + folders.len());
for file in &files {
let file_dto = FileDto::from(file.clone());
let score = compute_relevance(&file_dto.name, query);
suggestions.push(SearchSuggestionItem {
name: file_dto.name.clone(),
item_type: "file".to_string(),
id: file_dto.id.clone(),
path: file_dto.path.clone(),
icon_class: get_icon_class(&file_dto.name, &file_dto.mime_type),
icon_special_class: get_icon_special_class(&file_dto.name, &file_dto.mime_type),
relevance_score: score,
});
}
// List folders
let folders = self.folder_repository.list_folders(folder_id).await?;
for folder in folders {
let folder_dto = FolderDto::from(folder);
if folder_dto.name.to_lowercase().contains(&query_lower) {
let score = compute_relevance(&folder_dto.name, query);
suggestions.push(SearchSuggestionItem {
name: folder_dto.name.clone(),
item_type: "folder".to_string(),
id: folder_dto.id.clone(),
path: folder_dto.path.clone(),
icon_class: "fas fa-folder".to_string(),
icon_special_class: "folder-icon".to_string(),
relevance_score: score,
});
}
for folder in &folders {
let folder_dto = FolderDto::from(folder.clone());
let score = compute_relevance(&folder_dto.name, query);
suggestions.push(SearchSuggestionItem {
name: folder_dto.name.clone(),
item_type: "folder".to_string(),
id: folder_dto.id.clone(),
path: folder_dto.path.clone(),
icon_class: "fas fa-folder".to_string(),
icon_special_class: "folder-icon".to_string(),
relevance_score: score,
});
}
// Sort by relevance and truncate
// Merge files + folders by relevance and truncate to the final limit
suggestions.sort_by(|a, b| b.relevance_score.cmp(&a.relevance_score));
suggestions.truncate(limit);