MongoDB Aggregation
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This document provides an overview of MongoDB aggregation which allows processing data records and returning computed results. It describes some common aggregation pipeline stages like $match, $lookup, $project, and $unwind. $match filters documents, $lookup performs a left outer join, $project selects which fields to pass to the next stage, and $unwind deconstructs an array field. The document also lists other pipeline stages and aggregation pipeline operators for arithmetic, boolean, and comparison expressions.
![Example
9
{
"_id" : 1,
"item" : "almonds",
"price" : 12,
"quantity" : 2,
"inventory_docs" : [
{ "_id" : 1, "sku" : "almonds", "description" : "product 1", "instock" : 120 }
]
}
{
"_id" : 2,
"item" : "pecans",
"price" : 20,
"quantity" : 1,
"inventory_docs" : [
{ "_id" : 4, "sku" : "pecans", "description" : "product 4", "instock" : 70 }
]
}
{
"_id" : 3,
"inventory_docs" : [
{ "_id" : 5, "sku" : null, "description" : "Incomplete" },
{ "_id" : 6 }
]
}
SELECT *, inventory_docs
FROM orders
WHERE inventory_docs IN (SELECT *
FROM inventory
WHERE sku= orders.item);](https://image.slidesharecdn.com/mongodb-180924043616/85/MongoDB-Aggregation-9-320.jpg)
![Example
{
"_id" : 1, "item" : "ABC1", sizes: [ "S", "M", "L"]
}
13
{ $unwind : "$sizes" }
{ "_id" : 1, "item" : "ABC1", "sizes" : "S" }
{ "_id" : 1, "item" : "ABC1", "sizes" : "M" }
{ "_id" : 1, "item" : "ABC1", "sizes" : "L" }](https://image.slidesharecdn.com/mongodb-180924043616/85/MongoDB-Aggregation-13-320.jpg)
MongoDB Aggregation
- 1. 1 Mongodb Aggregation Amit Ghosh Software Engineer Jeeon Bangladesh Ltd.
- 2. 2 • MongoDB Aggregation • Some Aggregation Pipeline Stages • Some Aggregation Pipeline Operator Objective
- 3. 3 What is MongoDB aggregation ? Processing data records and return computed results.
- 5. $match Filters the documents to pass only the documents that match the specified condition(s) to the next pipeline stage. 5
- 6. Example { $match : { author : "dave" } } { "_id":ObjectId("512bc95fe835e68f199c8686"), "author":"dave", "score":80, "views":100}, {"_id":ObjectId("512bc962e835e68f199c8687"), "author":"dave", "score":85, "views":521}, { "_id":ObjectId("55f5a192d4bede9ac365b257"), "author":"ahn", "score":60, "views":1000} { "_id":ObjectId("55f5a192d4bede9ac365b258"), "author":"li", "score":55, "views":5000} 6
- 7. $lookup Performs a left outer join Reshape documents Passes these reshaped documents to the next stage. { $lookup: { from: <collection to join>, localField: <field from the input documents>, foreignField: <field from the documents of the "from" collection>, as: <output array field> } } 7
- 8. Example { "_id" : 1, "item" : "almonds", "price" : 12, "quantity" : 2 }, { "_id" : 2, "item" : "pecans", "price" : 20, "quantity" : 1 }, { "_id" : 3 } { "_id" : 1, "sku" : "almonds", description: "product 1", "instock" : 120 }, { "_id" : 2, "sku" : "bread", description: "product 2", "instock" : 80 }, { "_id" : 3, "sku" : "cashews", description: "product 3", "instock" : 60 }, { "_id" : 4, "sku" : "pecans", description: "product 4", "instock" : 70 }, { "_id" : 5, "sku": null, description: "Incomplete" }, { "_id" : 6 } 8 inventory orders { $lookup: { from: "inventory", localField: "item", foreignField: "sku", as: "inventory_docs" } }
- 9. Example 9 { "_id" : 1, "item" : "almonds", "price" : 12, "quantity" : 2, "inventory_docs" : [ { "_id" : 1, "sku" : "almonds", "description" : "product 1", "instock" : 120 } ] } { "_id" : 2, "item" : "pecans", "price" : 20, "quantity" : 1, "inventory_docs" : [ { "_id" : 4, "sku" : "pecans", "description" : "product 4", "instock" : 70 } ] } { "_id" : 3, "inventory_docs" : [ { "_id" : 5, "sku" : null, "description" : "Incomplete" }, { "_id" : 6 } ] } SELECT *, inventory_docs FROM orders WHERE inventory_docs IN (SELECT * FROM inventory WHERE sku= orders.item);
- 10. $project Passes along the documents with the requested fields to the next stage in the pipeline. The specified fields can be existing fields from the input documents or newly computed fields. 10 { $project: { <specification(s)> } }
- 11. Example 11 { "_id" : 1, "title" : "abc123", "author" : { "last" : "zzz", "first" : "aaa" } } { "_id" : 1, title: "abc123", isbn: "0001122223334", author: { last: "zzz", first: "aaa" }, copies: 5 } { $project : { title : 1 , author : 1 } } Why _id ?
- 12. $unwind Deconstructs an array field from the input documents to output a document for each element. Each output document is the input document with the value of the array field replaced by the element. 12 { $unwind: <field path> } { $unwind: { path: <field path>, includeArrayIndex: <string>, preserveNullAndEmptyArrays: <boolean> } }
- 13. Example { "_id" : 1, "item" : "ABC1", sizes: [ "S", "M", "L"] } 13 { $unwind : "$sizes" } { "_id" : 1, "item" : "ABC1", "sizes" : "S" } { "_id" : 1, "item" : "ABC1", "sizes" : "M" } { "_id" : 1, "item" : "ABC1", "sizes" : "L" }
- 14. Other Aggregation Pipeline Stages 14 • $addFields • $bucket • $bucketAuto • $collStats • $count • $facet • $geoNear • $graphLookup • $group • $indexStats • $limit • $listSessions • $lookup • $match • $out • $project • $redact • $replaceRoot • $sample • $skip • $sort • $sortByCount
- 15. Aggregation Pipeline Operators 15 Arithmetic Expression Operators $abs $add $ceil $divide $exp $floor $log $log10 $mod $multiply $pow $sqrt $subtract $ln Boolean Operator $and $not $or Comparison Expression Operators $cmp $eq $gt $gte $lt $lte $ne
- 18. 18 Thanks