Kepriye carane materialized views nggarap ing PostgreSQL?

Question

Accepted Answer

A **materialized view** nyimpen *asile* saka query kanthi fisik (precomputed), beda karo regular view (kang mbukak maneh queryé saben wektu). Iki ndadekake maca cepet kanggo query sing mahal, miturute data mung seger sumusuul kaya **refresh** pungkasan — mekanisme caching ing database.

## Regular view lawan materialized view

```sql
-- regular VIEW — runs the query EVERY time (always fresh, but recomputed)
CREATE VIEW sales_summary AS SELECT region, SUM(amount) FROM orders GROUP BY region;

-- MATERIALIZED VIEW — stores the RESULTS physically (fast reads, but can be stale)
CREATE MATERIALIZED VIEW sales_summary_mat AS
SELECT region, SUM(amount) AS total FROM orders GROUP BY region;

SELECT * FROM sales_summary_mat;     -- reads STORED results — fast (no recompute)
```

A materialized view precomputes lan nyimpen asile, dadi query cepet (kaya maca table) — ideale kanggo agregasi sing mahal sing kerep di-query.

## Refreshing (nganyarin data sing disimpen)

```sql
-- the data is stale until you refresh it
REFRESH MATERIALIZED VIEW sales_summary_mat;          -- recompute (locks reads during refresh)

-- CONCURRENTLY — refresh WITHOUT blocking reads (requires a unique index)
CREATE UNIQUE INDEX idx_sales_region ON sales_summary_mat(region);
REFRESH MATERIALIZED VIEW CONCURRENTLY sales_summary_mat;   -- reads continue during refresh
```

Sampeyan kudu **refresh** kanggo nganyarin data. `REFRESH ... CONCURRENTLY` (butuh unique index) nganyarin tanpa ngalangi maca concurrent — penting kanggo production.

## Kapan nggunakake materialized views

```text
✓ EXPENSIVE queries (complex aggregations, joins) queried FREQUENTLY
✓ Data that doesn't need real-time freshness (dashboards, reports, analytics)
✓ Reducing load from repeatedly running the same heavy query
→ Refresh on a schedule (cron / pg_cron) or after data changes.

✗ Data needing real-time accuracy → use a regular view or query directly
```

## Trade-off-ne

```text
Fast reads (precomputed) ⟷ Stale data (until refreshed) + storage cost.
You trade freshness and storage for read speed — a caching decision.
You can also index a materialized view (it's a physical table of results).
```

## Mengapa iki penting

Materialized views minangka fitur PostgreSQL sing berharga kanggo **optimisasi performance** — padha menehi mekanisme caching in-database kanggo query sing mahal, dadi ngerti cara kerjane iku berguna kanggo optimasi aplikasi sing duwe query larang.

Nilai inti minangka precomputing lan nyimpen asile query sing mahal (agregasi rumit, join abot) supaya maca cepet (kaya query table) tinimbang mbaleng query larang saben wektu — iku optimisasi serius kanggo dashboard, laporan, lan analytics nang query abot sing sama kebak mbaleng.

Ngerti trade-off kunci penting: materialized views menehi maca cepet nanging data **kuno** tekan di-refresh (lan butuh storage), dadi trade-off caching sing akeh kanggo data sing ora butuh freshness real-time.

Ngerti carane **refresh** — paling-paling `REFRESH ... CONCURRENTLY` (nganyarin tanpa ngalangi maca, penting kanggo availability production, butuh unique index) — lan strategi refresh (ing jadwal via cron/pg_cron, utawa sawise data owah) minangka ilmu praktis kanggo nggunakake kanthi epektif.

Ngerti **kapan nggunakake** materialized views (query larang, kerep mbaleng, toleran karo staleness sethitik — dashboard, analytics) lawan kapan ora (data butuh akurasi real-time) nggambarang pertimbangan cerdas.

Saiki query mbaleng sing larah minangka concern performance nyata, lan materialized views nerangake solusi caching in-database kanthi epektif (precomputed, hasil bisa di-index) karo trade-off freshness/speed sing jelas, ngerti cara kerjane — carane refresh (paling-paling concurrent), trade-off-ne, lan pemakaian sing sesuai — minangka ilmu PostgreSQL praktis lan penting kanggo optimasi performance query analytical lan reporting, butuh umum nang materialized views nawari solusi bersih lan built-in.