X'inhu l-aggregation pipeline?

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Accepted Answer

L-**aggregation pipeline** huwa l-framework qawwi ta' MongoDB għal **processing u analiżi tad-data** — jgħaddi d-dokumenti permezz ta' sekwenza ta' **stages**, kull wieħed jittrasforma d-data (filtering, grouping, computing). Huwa l-ekwivalenti ta' MongoDB ta' SQL's GROUP BY u queries analitikali kumplessi, iżda aktar flessibili.

## Il-kunċett tal-pipeline: stages jittrasformaw id-data

```js
db.orders.aggregate([
  { $match: { status: "completed" } },          // 1. FILTER (like WHERE)
  { $group: {                                    // 2. GROUP and aggregate
      _id: "$customerId",                         //    group by customerId
      total: { $sum: "$amount" },                 //    sum amounts per customer
      count: { $sum: 1 }                          //    count orders
  }},
  { $sort: { total: -1 } },                       // 3. SORT by total
  { $limit: 10 }                                  // 4. top 10
]);
// documents flow through each stage; each stage's output feeds the next
```

Id-dokumenti jgħaddu permezz tal-stages f'ordni — kull stage jittrasformahom u jippassa r-riżultati għall-wieħed li jmiss. Il-pipeline dan jikkalkulaw totali per-customer, sorted, top 10 — bħal query GROUP BY ta' SQL.

## Common pipeline stages

```text
$match    → filter documents (like WHERE) — put EARLY to reduce data
$group    → group by a key and aggregate ($sum, $avg, $max, $min, $push, etc.)
$sort     → order documents
$project  → reshape documents (include/exclude/compute fields)
$limit / $skip → pagination
$unwind   → deconstruct an array field into multiple documents (one per element)
$lookup   → JOIN with another collection
$addFields → add computed fields
$count    → count documents
```

## $lookup — joining collections

```js
// $lookup performs a left-outer JOIN to another collection
db.orders.aggregate([
  { $lookup: {
      from: "customers",
      localField: "customerId",
      foreignField: "_id",
      as: "customer"           // joined customer data added as an array field
  }}
]);
```

`$lookup` jippermetti joins (li MongoDB inkella jevitwahom permezz ta' embedding) — utli meta għandek bżonn tikkkombina collections.

## $unwind — expand arrays

```js
// turn one document with an array into multiple documents (one per array element)
db.posts.aggregate([
  { $unwind: "$tags" },                           // one doc per tag
  { $group: { _id: "$tags", count: { $sum: 1 } } } // count posts per tag
]);
```

## Għaliex importanti

L-aggregation pipeline huwa wieħed mill-features l-aktar qawwi u importanti ta' MongoDB — huwa l-primary tool għal **data analysis, reporting, u transformations kumplessi**, għalhekk il-fehim tiegħu huwa essenzjali għal serious MongoDB work il-là minn basic queries.

Il-**stage-based model** tal-pipeline (dokumenti li jgħaddu permezz ta' sequential transformation stages, kull wieħed jiffiltra, jiggruppja, jirreforma, jew jikkalkulaw) huwa konċettwalment elegant u jippermetti data processing sofistikatu li simple `find` queries ma jistgħux — huwa l-ekwivalenti ta' MongoDB ta' SQL's GROUP BY u analytical queries, iżda aktar flessibili u composable.
/_il-fehim tal-common stages — **`$match`** (filtering, idealment kmieni biex tnaqqas id-data), **`$group`** (grouping u aggregating b'`$sum`, `$avg`, eċċ. — il-core tal-analytics), **`$sort`/`$limit`** (ordering u pagination), **`$project`** (reshaping ta' dokumenti), **`$unwind`** (expanding arrays fil-dokumenti — importanti għall-analiżi ta' array data, komuni f'MongoDB), u **`$lookup`** (joining collections — jippermetti l-joins li MongoDB inkella jevitwahom) — jikopri l-toolkit għal real data processing.

Il-pipeline jħaddem reporting, analytics, data transformation, u complex queries (aggregations, joins, array processing) li huma bżonnijiet komuni f'applikazzjoniet.

Billi data analysis u complex querying huma bżonnijiet importanti ta' kwalunkwe database, u billi l-aggregation pipeline huwa l-mekkaniżmu qawwi u flessibili ta' MongoDB għalihom (li jmur ħafna lil hinn minn basic CRUD), il-fehim tal-aggregation pipeline — il-stage model u key stages ($match, $group, $sort, $project, $unwind, $lookup) — huwa essenzjali, frequently-applied MongoDB knowledge għal analytics, reporting, u complex data transformation, hallmark ta' advanced MongoDB skill u wieħed mill-most important MongoDB topics għall-kisba ta' real analytical value mid-database.