Apa wae pola-pola pemodelan data MongoDB sing umum?

Question

IT Interview Practice · Accepted Answer

Saliyane keputusan dasar embed-vs-reference, MongoDB nduweni **pola-pola pemodelan data** — solusi sing wis terbukti kanggo skenario-skenario umum kaya array gedhe, data polimorfik, lan hubungan-hubungan. Ngerti pola-pola iki tulung desain skema sing efektif kanggo situasi nyata.

## Pola Bucket — grupkan data time-series/terkait

```js
// instead of one document per reading (millions of tiny docs), BUCKET them:
{
  sensorId: "s1",
  date: ISODate("2024-01-15"),
  readings: [                            // a day's readings in one document
    { time: "10:00", value: 23 },
    { time: "10:01", value: 24 }
  ]
}
// → fewer documents, efficient for time-series/IoT data
```

## Pola Subset — embed subset sing sering digunakan

```js
// embed the most-used part, reference the rest (for large related data)
{
  _id: ObjectId("..."),
  title: "Product",
  recentReviews: [ /* 5 most recent — embedded for fast display */ ],
  // full reviews live in a separate collection (referenced)
}
// → fast common reads without loading ALL related data
```

## Pola Computed — hitung sebelumnya lan simpen

```js
// store precomputed values (avoid recomputing on every read)
{ productId: "p1", totalReviews: 1500, avgRating: 4.5 }
// → update these when reviews change; reads are fast (no aggregation needed)
```

## Pola Extended Reference — embed field-field referensi kunci

```js
// embed the OFTEN-NEEDED fields of a referenced document (avoid a join for common reads)
{ orderId: "o1", customer: { _id: "u1", name: "Ann", city: "NY" } }  // enough for display
// → reference customer._id for full data; embed name/city for the common read
```

## Pola-pola liyane

```text
Polymorphic    → different document shapes in one collection (with a "type" field)
Schema Versioning → a version field to handle evolving schemas in one collection
Outlier        → handle rare documents that don't fit the common pattern specially
Approximation  → store approximate values (e.g. view counts) to reduce write load
Tree/Hierarchy → patterns for hierarchical data (parent refs, arrays of ancestors, etc.)
```

## Apa gunane

Ngerti pola-pola pemodelan data MongoDB umum iku berharga kanggo **ndesain skema efektif kanggo skenario real-world**, dadi iku pengetahuan berguna sing bangun atas keputusan embed-vs-reference dasar.

Mangkono embedding vs referencing kuwi pilihan inti, aplikasi nyata menghadapi tantangan pemodelan berulang sing pola-pola terbukti iki atasi: pola **Bucket** (grouping time-series/IoT readings mengo dokumen-dokumen luwih sithik — penting kanggo use case time-series umum, ngindhari jutaan dokumen cilik), pola **Subset** (embed subset sing sering digunakan manawa reference data lengkap — balancing performa baca karo ukuran dokumen kanggo data terkait gedhe), pola **Computed** (precomputing lan simpen nilai kaya total/rata-rata kanggo indhari recomputation mahal nalika baca), pola **Extended Reference** (embed field-field sering dibutuhake saka dokumen sing direferensikan kanggo indhari join kanggo baca-baca umum — hybrid praktis), lan liyane-liyane (polymorphic kanggo bentuk beda-beda, schema versioning kanggo evolusi, pola pohon kanggo hirarki).

Ngerti pola-pola iki nyedhiyake **solusi terbukti** kanggo skenario-skenario umum tinimbang ngiseng desain maneh, tulung nggawé keputusan pemodelan suara kanggo situasi kaya data time-series, koleksi terkait gedhe, komputasi mahal, lan data hierarki.

Mangkono aplikasi MongoDB nyata menghadapi tantangan desain berulang iki, lan mengingat pola-pola established nyedhiyake solusi tested, efektif (ningkatake performa lan maintainability), ngerti pola-pola pemodelan data MongoDB umum — pola bucket, subset, computed, extended reference, lan pola-pola liyane — iku pengetahuan berharga, relevan praktis sing nongkatake desain skema saka pilihan embed/reference dasar mengo nerapake solusi terbukti kanggo skenario nyata, nampakake skill desain MongoDB mateng lan tulung bangun skema sing urip apik kanggo access pattern spesifik lan karakteristik data aplikasi.

Pola Bucket — grupkan data time-series/terkait

Pola Subset — embed subset sing sering digunakan

Pola Computed — hitung sebelumnya lan simpen

Pola Extended Reference — embed field-field referensi kunci

Pola-pola liyane

Apa gunane

Pitakon sing gegandhengan