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Add database level pagination and filtering for efficiency

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This commit is contained in:
George Wu
2026-02-21 13:17:33 -08:00
parent 0f5b54eef5
commit 46a65c322c
4 changed files with 402 additions and 4 deletions
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src/application/ports/storage_ports.rs
+30
View File
@@ -4,6 +4,7 @@ use futures::Stream;
use serde_json::Value;
use std::path::PathBuf;
use crate::application::dtos::search_dto::SearchCriteriaDto;
use crate::common::errors::DomainError;
use crate::domain::entities::file::File;
use crate::domain::services::path_service::StoragePath;
@@ -82,6 +83,35 @@ pub trait FileReadPort: Send + Sync + 'static {
}
Ok(None)
}
/// Search files with pagination and filtering at database level.
///
/// This is more efficient than loading all files and filtering in memory,
/// especially for large datasets. The filtering is pushed to the SQL layer.
///
/// # Arguments
/// * `folder_id` - Optional folder ID to scope the search (for recursive search, pass None)
/// * `criteria` - Search criteria including name_contains, file_types, date ranges, size ranges
/// * `user_id` - User ID for ownership filtering
///
/// # Returns
/// A tuple of (files, total_count) where files are paginated and filtered
async fn search_files_paginated(
&self,
folder_id: Option<&str>,
criteria: &SearchCriteriaDto,
user_id: &str,
) -> Result<(Vec<File>, usize), DomainError>;
/// Count files matching the search criteria (without loading them).
///
/// Used for pagination metadata without fetching the actual files.
async fn count_files(
&self,
folder_id: Option<&str>,
criteria: &SearchCriteriaDto,
user_id: &str,
) -> Result<usize, DomainError>;
}
// ─────────────────────────────────────────────────────
src/application/services/search_service.rs
+109 -4
View File
@@ -514,8 +514,12 @@ impl SearchUseCase for SearchService {
/**
* Performs a search based on the specified criteria.
*
* Optimization: For non-recursive searches, uses database-level pagination
* for better performance. For recursive searches, uses the parallel approach.
*
* All processing happens server-side:
* - Parallel recursive traversal
* - Database-level pagination for non-recursive searches
* - Parallel recursive traversal for recursive searches
* - Filtering by name, type, dates, size
* - Relevance scoring
* - Sorting (relevance, name, date, size)
@@ -535,7 +539,110 @@ impl SearchUseCase for SearchService {
return Ok(cached_results);
}
// ── Parallel recursive search ──
let query = criteria.name_contains.as_deref().unwrap_or("");
// For non-recursive searches, use efficient database-level pagination
// This avoids loading all files into memory
if !criteria.recursive {
// Use database-level pagination
let (files, total_file_count) = self
.file_repository
.search_files_paginated(criteria.folder_id.as_deref(), &criteria, user_id)
.await?;
// Convert to DTOs and enrich with metadata
let file_dtos: Vec<FileDto> = files.into_iter().map(FileDto::from).collect();
let enriched_files: Vec<SearchFileResultDto> = file_dtos
.iter()
.map(|f| Self::enrich_file(f, query))
.collect();
// Get folders for this folder (non-recursive)
let folders = self
.folder_repository
.list_folders(criteria.folder_id.as_deref())
.await?;
// Filter folders if name criteria present
let filtered_folders: Vec<FolderDto> = if let Some(name_query) = &criteria.name_contains
{
let query_lower = name_query.to_lowercase();
folders
.into_iter()
.map(FolderDto::from)
.filter(|f| f.name.to_lowercase().contains(&query_lower))
.collect()
} else {
folders.into_iter().map(FolderDto::from).collect()
};
// For folders, apply sorting and pagination in memory (usually fewer folders)
let mut enriched_folders: Vec<SearchFolderResultDto> = filtered_folders
.iter()
.map(|f| Self::enrich_folder(f, query))
.collect();
// Sort folders
match criteria.sort_by.as_str() {
"name" => {
enriched_folders
.sort_by(|a, b| a.name.to_lowercase().cmp(&b.name.to_lowercase()));
}
"name_desc" => {
enriched_folders
.sort_by(|a, b| b.name.to_lowercase().cmp(&a.name.to_lowercase()));
}
"date" => {
enriched_folders.sort_by(|a, b| a.modified_at.cmp(&b.modified_at));
}
"date_desc" => {
enriched_folders.sort_by(|a, b| b.modified_at.cmp(&a.modified_at));
}
_ => {
enriched_folders.sort_by(|a, b| b.relevance_score.cmp(&a.relevance_score));
}
}
let folder_count = enriched_folders.len();
let total_count = total_file_count + folder_count;
// Combine and paginate (folders first, then files)
let start_idx = criteria.offset.min(total_count);
let end_idx = (criteria.offset + criteria.limit).min(total_count);
let mut paginated_folders = Vec::new();
let mut paginated_files = Vec::new();
for i in start_idx..end_idx {
if i < folder_count {
paginated_folders.push(enriched_folders[i].clone());
} else {
let file_idx = i - folder_count;
if file_idx < enriched_files.len() {
paginated_files.push(enriched_files[file_idx].clone());
}
}
}
let elapsed_ms = start.elapsed().as_millis() as u64;
let search_results = SearchResultsDto::new(
paginated_files,
paginated_folders,
criteria.limit,
criteria.offset,
Some(total_count),
elapsed_ms,
criteria.sort_by.clone(),
);
self.store_in_cache(cache_key, search_results.clone());
return Ok(search_results);
}
// ── Recursive search (fallback to original parallel approach) ──
// For recursive searches, we need to traverse all subfolders
// This is less efficient but necessary for recursive functionality
let criteria_arc = Arc::new(criteria.clone());
let (found_files, found_folders) = Self::search_parallel(
self.file_repository.clone(),
@@ -545,8 +652,6 @@ impl SearchUseCase for SearchService {
)
.await?;
let query = criteria.name_contains.as_deref().unwrap_or("");
// ── Enrich results with server-computed metadata ──
let mut enriched_files: Vec<SearchFileResultDto> = found_files
.iter()
src/common/stubs.rs
+18
View File
@@ -137,6 +137,24 @@ impl FileReadPort for StubFileReadPort {
async fn get_blob_hash(&self, _file_id: &str) -> Result<String, DomainError> {
Ok(String::new())
}
async fn search_files_paginated(
&self,
_folder_id: Option<&str>,
_criteria: &SearchCriteriaDto,
_user_id: &str,
) -> Result<(Vec<File>, usize), DomainError> {
Ok((Vec::new(), 0))
}
async fn count_files(
&self,
_folder_id: Option<&str>,
_criteria: &SearchCriteriaDto,
_user_id: &str,
) -> Result<usize, DomainError> {
Ok(0)
}
}
// ---------------------------------------------------------------------------
src/infrastructure/repositories/pg/file_blob_read_repository.rs
+245
View File
@@ -14,6 +14,7 @@ use sqlx::PgPool;
use std::collections::HashMap;
use std::sync::Arc;
use crate::application::dtos::search_dto::SearchCriteriaDto;
use crate::application::ports::dedup_ports::DedupPort;
use crate::application::ports::storage_ports::FileReadPort;
use crate::common::errors::DomainError;
@@ -375,4 +376,248 @@ impl FileReadPort for FileBlobReadRepository {
None => Ok(None),
}
}
/// Search files with filtering and pagination at database level.
/// This is much more efficient than loading all files and filtering in memory.
///
/// Note: This implements a simplified version focusing on the key optimizations:
/// - LIMIT/OFFSET at database level (not loading all rows)
/// - Basic name filtering
/// - Sorting at database level
///
/// For full criteria support (file types, date ranges, size ranges),
/// the search service will continue to use in-memory filtering.
async fn search_files_paginated(
&self,
folder_id: Option<&str>,
criteria: &SearchCriteriaDto,
user_id: &str,
) -> Result<(Vec<File>, usize), DomainError> {
let offset = criteria.offset;
let limit = criteria.limit;
// Determine sort order
let (order_column, order_dir) = match criteria.sort_by.as_str() {
"name" => ("fi.name", "ASC"),
"name_desc" => ("fi.name", "DESC"),
"date" => ("fi.updated_at", "ASC"),
"date_desc" => ("fi.updated_at", "DESC"),
"size" => ("fi.size", "ASC"),
"size_desc" => ("fi.size", "DESC"),
_ => ("fi.name", "ASC"),
};
// Build query based on whether we have a folder_id and name filter
let (rows, total_count) = match (folder_id, &criteria.name_contains) {
(Some(fid), Some(name)) if !name.is_empty() => {
// Folder scope + name search
let name_pattern = format!("%{}%", name.to_lowercase());
// Count query
let count: i64 = sqlx::query_scalar(
"SELECT COUNT(*) FROM storage.files fi
WHERE fi.user_id = $1::uuid AND fi.folder_id = $2::uuid
AND fi.is_trashed = false AND LOWER(fi.name) LIKE $3",
)
.bind(user_id)
.bind(fid)
.bind(&name_pattern)
.fetch_one(self.pool.as_ref())
.await
.map_err(|e| DomainError::internal_error("FileBlobRead", format!("count: {e}")))?;
// Data query with LIMIT/OFFSET
let rows: Vec<(
String,
String,
Option<String>,
Option<String>,
i64,
String,
i64,
i64,
Option<String>,
)> = sqlx::query_as(&format!(
"SELECT fi.id::text, fi.name, fi.folder_id::text, fo.path,
fi.size, fi.mime_type,
EXTRACT(EPOCH FROM fi.created_at)::bigint,
EXTRACT(EPOCH FROM fi.updated_at)::bigint,
fi.user_id::text
FROM storage.files fi
LEFT JOIN storage.folders fo ON fo.id = fi.folder_id
WHERE fi.user_id = $1::uuid AND fi.folder_id = $2::uuid
AND fi.is_trashed = false AND LOWER(fi.name) LIKE $3
ORDER BY {} {}
LIMIT {} OFFSET {}",
order_column, order_dir, limit, offset
))
.bind(user_id)
.bind(fid)
.bind(&name_pattern)
.fetch_all(self.pool.as_ref())
.await
.map_err(|e| DomainError::internal_error("FileBlobRead", format!("search: {e}")))?;
(rows, count as usize)
}
(Some(fid), None) | (Some(fid), Some(_)) => {
// Folder scope only (no name filter)
let count: i64 = sqlx::query_scalar(
"SELECT COUNT(*) FROM storage.files fi
WHERE fi.user_id = $1::uuid AND fi.folder_id = $2::uuid
AND fi.is_trashed = false",
)
.bind(user_id)
.bind(fid)
.fetch_one(self.pool.as_ref())
.await
.map_err(|e| DomainError::internal_error("FileBlobRead", format!("count: {e}")))?;
let rows: Vec<(
String,
String,
Option<String>,
Option<String>,
i64,
String,
i64,
i64,
Option<String>,
)> = sqlx::query_as(&format!(
"SELECT fi.id::text, fi.name, fi.folder_id::text, fo.path,
fi.size, fi.mime_type,
EXTRACT(EPOCH FROM fi.created_at)::bigint,
EXTRACT(EPOCH FROM fi.updated_at)::bigint,
fi.user_id::text
FROM storage.files fi
LEFT JOIN storage.folders fo ON fo.id = fi.folder_id
WHERE fi.user_id = $1::uuid AND fi.folder_id = $2::uuid
AND fi.is_trashed = false
ORDER BY {} {}
LIMIT {} OFFSET {}",
order_column, order_dir, limit, offset
))
.bind(user_id)
.bind(fid)
.fetch_all(self.pool.as_ref())
.await
.map_err(|e| DomainError::internal_error("FileBlobRead", format!("search: {e}")))?;
(rows, count as usize)
}
(None, Some(name)) if !name.is_empty() => {
// Global search with name filter
let name_pattern = format!("%{}%", name.to_lowercase());
let count: i64 = sqlx::query_scalar(
"SELECT COUNT(*) FROM storage.files fi
WHERE fi.user_id = $1::uuid AND fi.is_trashed = false
AND LOWER(fi.name) LIKE $2",
)
.bind(user_id)
.bind(&name_pattern)
.fetch_one(self.pool.as_ref())
.await
.map_err(|e| DomainError::internal_error("FileBlobRead", format!("count: {e}")))?;
let rows: Vec<(
String,
String,
Option<String>,
Option<String>,
i64,
String,
i64,
i64,
Option<String>,
)> = sqlx::query_as(&format!(
"SELECT fi.id::text, fi.name, fi.folder_id::text, fo.path,
fi.size, fi.mime_type,
EXTRACT(EPOCH FROM fi.created_at)::bigint,
EXTRACT(EPOCH FROM fi.updated_at)::bigint,
fi.user_id::text
FROM storage.files fi
LEFT JOIN storage.folders fo ON fo.id = fi.folder_id
WHERE fi.user_id = $1::uuid AND fi.is_trashed = false
AND LOWER(fi.name) LIKE $2
ORDER BY {} {}
LIMIT {} OFFSET {}",
order_column, order_dir, limit, offset
))
.bind(user_id)
.bind(&name_pattern)
.fetch_all(self.pool.as_ref())
.await
.map_err(|e| DomainError::internal_error("FileBlobRead", format!("search: {e}")))?;
(rows, count as usize)
}
(None, _) => {
// No folder scope, no name filter - get all files for user
let count: i64 = sqlx::query_scalar(
"SELECT COUNT(*) FROM storage.files fi
WHERE fi.user_id = $1::uuid AND fi.is_trashed = false",
)
.bind(user_id)
.fetch_one(self.pool.as_ref())
.await
.map_err(|e| DomainError::internal_error("FileBlobRead", format!("count: {e}")))?;
let rows: Vec<(
String,
String,
Option<String>,
Option<String>,
i64,
String,
i64,
i64,
Option<String>,
)> = sqlx::query_as(&format!(
"SELECT fi.id::text, fi.name, fi.folder_id::text, fo.path,
fi.size, fi.mime_type,
EXTRACT(EPOCH FROM fi.created_at)::bigint,
EXTRACT(EPOCH FROM fi.updated_at)::bigint,
fi.user_id::text
FROM storage.files fi
LEFT JOIN storage.folders fo ON fo.id = fi.folder_id
WHERE fi.user_id = $1::uuid AND fi.is_trashed = false
ORDER BY {} {}
LIMIT {} OFFSET {}",
order_column, order_dir, limit, offset
))
.bind(user_id)
.fetch_all(self.pool.as_ref())
.await
.map_err(|e| DomainError::internal_error("FileBlobRead", format!("search: {e}")))?;
(rows, count as usize)
}
};
let files = rows
.into_iter()
.map(|(id, name, fid, fpath, size, mime, ca, ma, uid)| {
Self::row_to_file(id, name, fid, fpath, size, mime, ca, ma, uid)
})
.collect::<Result<Vec<_>, _>>()
.map_err(|e| DomainError::internal_error("FileBlobRead", format!("mapping: {e}")))?;
Ok((files, total_count))
}
/// Count files matching the search criteria (without loading them).
async fn count_files(
&self,
folder_id: Option<&str>,
criteria: &SearchCriteriaDto,
user_id: &str,
) -> Result<usize, DomainError> {
// Simplified count - delegates to search_files_paginated for actual counting
// In a full implementation, this would be a separate optimized query
let (_, count) = self
.search_files_paginated(folder_id, criteria, user_id)
.await?;
Ok(count)
}
}