search-implementation

name	search-implementation
description	Search implementation patterns. Full-text search, Elasticsearch, Algolia, Meilisearch, PostgreSQL FTS, autocomplete.

Search Implementation

Good search is the fastest navigation in complex applications.

---

1. Solution Selection

Solution	Best For	Complexity
PostgreSQL FTS	Simple, existing DB	Low
Meilisearch	Self-hosted, fast setup	Low
Algolia	Managed, excellent DX	Low (cost)
Typesense	Open source Algolia alt	Medium
Elasticsearch	Complex, large-scale	High
OpenSearch	AWS, Elasticsearch fork	High

---

2. PostgreSQL Full-Text Search

-- Setup
ALTER TABLE products
  ADD COLUMN search_vector tsvector
  GENERATED ALWAYS AS (
    setweight(to_tsvector(\'english\', coalesce(name, \'\')), \'A\') ||
    setweight(to_tsvector(\'english\', coalesce(description, \'\')), \'B\') ||
    setweight(to_tsvector(\'english\', coalesce(category, \'\')), \'C\')
  ) STORED;

CREATE INDEX idx_products_search ON products USING GIN(search_vector);

-- Query
SELECT id, name, description,
  ts_rank(search_vector, query) AS rank
FROM products,
  websearch_to_tsquery(\'english\', \'running shoes\') AS query
WHERE search_vector @@ query
ORDER BY rank DESC
LIMIT 20;

// Prisma + raw query
const results = await prisma.$queryRaw`
  SELECT id, name, ts_rank(search_vector, query) AS rank
  FROM products, websearch_to_tsquery(\'english\', ${searchQuery}) AS query
  WHERE search_vector @@ query
  ORDER BY rank DESC
  LIMIT ${limit} OFFSET ${offset}
`;

---

3. Meilisearch

import { MeiliSearch } from "meilisearch";

const client = new MeiliSearch({ host: "http://localhost:7700", apiKey });

// Index configuration
const index = client.index("products");
await index.updateSettings({
  searchableAttributes: ["name", "description", "category"],
  filterableAttributes: ["category", "price", "inStock"],
  sortableAttributes: ["price", "createdAt"],
  rankingRules: ["words", "typo", "proximity", "attribute", "sort", "exactness"],
});

// Index documents
await index.addDocuments(products);

// Search
const results = await index.search("running shoes", {
  filter: "category = \'footwear\' AND price < 200",
  sort: ["price:asc"],
  limit: 20,
  offset: 0,
  attributesToRetrieve: ["id", , , ],
  : [, ],
});

---

4. Algolia

import algoliasearch from "algoliasearch";

const client = algoliasearch(APP_ID, ADMIN_API_KEY);
const index = client.initIndex("products");

// Index
await index.saveObjects(products, { autoGenerateObjectIDField: "id" });

// Search (client-side, use Search-Only API Key)
const { hits } = await index.search("query", {
  filters: "category:shoes AND price < 200",
  hitsPerPage: 20,
  page: 0,
});

---

5. Autocomplete Pattern

// Debounced autocomplete
const [query, setQuery] = useState("");
const debouncedQuery = useDebounce(query, 300);

const { data: suggestions } = useQuery({
  queryKey: ["autocomplete", debouncedQuery],
  queryFn: () => search(debouncedQuery),
  enabled: debouncedQuery.length >= 2,
  staleTime: 30_000,
});

// Cache popular queries
// Suggest based on: partial matches + popular searches + user history

---

6. Search UX Patterns

Pattern	Description
Instant search	Results update as user types
Autocomplete	Suggestions dropdown (300ms debounce)
Faceted filters	Sidebar refinements (category, price, etc.)
Sort options	Relevance, price, date, rating
Pagination / infinite	Page controls or scroll-to-load
Highlighting	Bold matched terms in results
"Did you mean?"	Spell correction suggestion
Empty state	No results → suggest alternatives
Recent searches	Stored locally, quick re-search

---

7. Relevance Tuning

Ranking factors:
├── Text match quality (exact > partial > fuzzy)
├── Field weight (title > description > tags)
├── Recency (newer = more relevant for some domains)
├── Popularity (views, sales, clicks)
├── User context (location, history)
└── Business rules (promoted items, in-stock boost)

---

8. Indexing Strategy

Sync strategy:
├── On write: index immediately (simple apps)
├── Queue-based: write → queue → indexer (robust)
├── Scheduled: batch re-index nightly (analytics)

What to index:
├── Only searchable + filterable fields
├── Denormalize: include category name, not just ID
├── Strip HTML before indexing
└── Normalize: lowercase, remove diacritics

"""