Files
cista-storage/frontend/src/workers/searchWorker.ts
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226 lines
6.9 KiB
TypeScript

// Search worker - runs search in background thread
// Receives document updates and search queries, returns incremental results
interface DocData {
loc: string
name: string
key: string
size: number
mtime: number
dir: boolean
}
interface WorkerDoc extends DocData {
haystack: string
}
interface SearchMessage {
type: 'search'
query: string
loc: string
id: number
}
interface UpdateMessage {
type: 'update'
documents: DocData[]
}
type IncomingMessage = SearchMessage | UpdateMessage
interface ResultMessage {
type: 'results'
docs: DocData[]
id: number
done: boolean
}
// Worker state
let recentDocuments: WorkerDoc[] = [] // Sorted by mtime descending
let currentSearchId = 0
// Search result cache - cleared when documents change
interface CacheEntry {
query: string // Normalized query string
results: WorkerDoc[] // Matched results (up to limit)
complete: boolean // True if search scanned all documents
}
const searchCache: CacheEntry[] = []
const MAX_CACHE_SIZE = 10
const RESULT_LIMIT = 100
// Normalize string for search (remove diacritics, lowercase)
// Haystack adds ^ and $ markers to allow matching start/end of name
function normalizeHaystack(str: string): string {
return '^' + str.normalize('NFKD').replace(/[\u0300-\u036f]/g, '').toLowerCase() + '$'
}
function normalizeQuery(str: string): string {
return str.normalize('NFKD').replace(/[\u0300-\u036f]/g, '').toLowerCase()
}
// Test if document matches search query
function matches(haystack: string, query: string, words: string[]): boolean {
return haystack.includes(query) || words.every(word => haystack.includes(word))
}
// Collator for sorting
const collator = new Intl.Collator('en', { sensitivity: 'base', numeric: true })
// Yield control to allow new messages to be processed
const yieldControl = (): Promise<void> => new Promise(resolve => setTimeout(resolve, 0))
// Find best cache entry to filter from
// Returns entry if new query's results are guaranteed to be a subset of cached results
// Only valid if the cached search was complete (scanned all documents)
function findCacheSubset(query: string): CacheEntry | null {
// Look for a cached query that the new query starts with
// e.g., cached "foo" can be used for "foobar" or "foo bar"
// The longer the prefix, the better (fewer items to filter)
// IMPORTANT: Only use complete cache entries - incomplete ones may have
// missed results that would match the more specific query
let best: CacheEntry | null = null
for (const entry of searchCache) {
if (entry.complete && query.startsWith(entry.query)) {
if (!best || entry.query.length > best.query.length) {
best = entry
}
}
}
return best
}
// Add result to cache
function addToCache(query: string, results: WorkerDoc[], complete: boolean) {
// Remove existing entry for same query if any
const idx = searchCache.findIndex(e => e.query === query)
if (idx !== -1) searchCache.splice(idx, 1)
// Add to front (most recent)
searchCache.unshift({ query, results, complete })
// Trim cache
if (searchCache.length > MAX_CACHE_SIZE) searchCache.pop()
}
// Clear cache (called when documents change)
function clearCache() {
searchCache.length = 0
}
// Perform search with incremental results
async function performSearch(rawQuery: string, loc: string, searchId: number) {
const query = normalizeQuery(rawQuery)
const words = query.split(/\s+/)
const results: WorkerDoc[] = []
let lastResultCount = 0
// Check cache for exact match
const exactMatch = searchCache.find(e => e.query === query)
if (exactMatch) {
if (currentSearchId === searchId) {
postResults(exactMatch.results, rawQuery, loc, searchId, true)
}
return
}
// Check if we can filter from a cached superset
const cacheEntry = findCacheSubset(query)
if (cacheEntry) {
// Fast path: filter from cached results (only used for complete cache entries)
for (const doc of cacheEntry.results) {
if (matches(doc.haystack, query, words)) {
results.push(doc)
}
}
// Cache entry was complete, so filtered results are also complete
addToCache(query, results, true)
if (currentSearchId === searchId) {
postResults(results, rawQuery, loc, searchId, true)
}
return
}
// Slow path: scan all documents
const batchSize = 500
for (let i = 0; i < recentDocuments.length && results.length < RESULT_LIMIT; i += batchSize) {
if (currentSearchId !== searchId) return // Superseded
// Process batch
const end = Math.min(i + batchSize, recentDocuments.length)
for (let j = i; j < end && results.length < RESULT_LIMIT; j++) {
const doc = recentDocuments[j]!
if (matches(doc.haystack, query, words)) {
results.push(doc)
}
}
// Post incremental results if we found new matches
if (results.length > lastResultCount && currentSearchId === searchId) {
lastResultCount = results.length
postResults(results, rawQuery, loc, searchId, false)
}
// Yield control between batches
if (i + batchSize < recentDocuments.length && results.length < RESULT_LIMIT) {
await yieldControl()
}
}
// Cache and post final results
addToCache(query, results, results.length < RESULT_LIMIT)
if (currentSearchId === searchId) {
postResults(results, rawQuery, loc, searchId, true)
}
}
// Post results to main thread
function postResults(docs: WorkerDoc[], query: string, loc: string, id: number, done: boolean) {
const sorted = sortResults(docs, query, loc)
postMessage({
type: 'results',
docs: sorted.map(({ haystack, ...rest }) => rest),
id,
done
} as ResultMessage)
}
// Sort results by relevance
function sortResults(docs: WorkerDoc[], query: string, loc: string): WorkerDoc[] {
const locsub = loc + '/'
return [...docs].sort((a, b) => (
// Current folder first
Number(b.loc === loc) - Number(a.loc === loc) ||
// Then subfolders
Number(b.loc.startsWith(locsub)) - Number(a.loc.startsWith(locsub)) ||
// Then by location
collator.compare(a.loc, b.loc) ||
// Folders before files
Number(b.dir) - Number(a.dir) ||
// Exact name match first
Number(b.name.includes(query)) - Number(a.name.includes(query)) ||
// Finally by name
collator.compare(a.name, b.name)
))
}
// Handle incoming messages
self.onmessage = async (e: MessageEvent<IncomingMessage>) => {
const msg = e.data
if (msg.type === 'update') {
// Update document list with haystacks, sorted by mtime descending
recentDocuments = msg.documents
.map(doc => ({ ...doc, haystack: normalizeHaystack(doc.name) }))
.sort((a, b) => b.mtime - a.mtime)
clearCache()
} else if (msg.type === 'search') {
currentSearchId = msg.id
if (msg.query) {
await performSearch(msg.query, msg.loc, msg.id)
} else {
// Empty query - no results needed
postMessage({ type: 'results', docs: [], id: msg.id, done: true } as ResultMessage)
}
}
}