Mongo shell script and sample documents used for my aggregation talks 12/2011

aggregation.js

// make sure we're using the right db; this is the same as "use aggdb;" in shell
db = db.getSiblingDB("aggdb");

// simple projection
var p1 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	tags : 1,
	pageViews : 1
    }}
]});


// unwinding an array
var u1 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $unwind : "$tags" }
]});


// combining pipeline operations
var p2 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	author : 1,
	tags : 1,
	pageViews : 1
    }},
    { $unwind : "$tags" }
]});


// pulling values out of subdocuments
var p3 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	otherfoo : "$other.foo",
	otherbar : "$other.bar"
    }}
]});


// projection includes a computed value
var p4 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	author : 1,
	daveWroteIt : { $eq:["$author", "dave"] }
    }}
]});


// projection includes a virtual (fabricated) document
var p5 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	author : 1,
	pageViews : 1,
	tags : 1
    }},
    { $unwind : "$tags" },
    { $project : {
	author : 1,
	subDocument : { foo : "$pageViews", bar : "$tags"  }
    }}
]});


// nested computed expression; $ifNull
var p7 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	theSum : { $add:["$pageViews",
			 { $ifNull:["$other.foo",
				    "$other.bar"] } ] }
    }}
]});


// dotted path inclusion; _id exclusion
var p8 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	_id : 0,
	author : 1,
	tags : 1,
	"comments.author" : 1
    }}
]});


// simple sort
var p10 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $sort : { title : 1 }
    }
]});


// date tests
var p19 = db.runCommand(
{aggregate : "article", pipeline : [
    { $project : {
        authors : 1,
        seconds: {$second: "$posted"},
        minutes: {$minute: "$posted"},
        hour: {$hour: "$posted"},
        dayOfYear: {$dayOfYear: "$posted"},
        dayOfMonth: {$dayOfMonth: "$posted"},
        dayOfWeek: {$dayOfWeek: "$posted"},
        month: {$month: "$posted"},
        week: {$week: "$posted"},
        year: {$year: "$posted"}
    }}
]});


// ternary conditional operator
var p21 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	_id : 0,
	author : 1,
	pageViews : { $cond : [ {$eq:["$author", "dave"]},
				{$add:["$pageViews", 1000]}, "$pageViews" ]
	}
    }}
]});


// simple matching
var m1 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $match : { author : "dave" } }
]});


// combining matching with a projection
var m2 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	title : 1,
	author : 1,
	pageViews : 1,
	tags : 1,
	comments : 1
    }},
    { $unwind : "$tags" },
    { $match : { tags : "nasty" } }
]});


// grouping
var g1 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	author : 1,
	tags : 1,
	pageViews : 1
    }},
    { $unwind : "$tags" },
    { $group : {
	_id : "$tags",
	docsByTag : { $sum : 1 },
	viewsByTag : { $sum : "$pageViews" },
	mostViewsByTag : { $max : "$pageViews" },
	avgByTag : { $avg : "$pageViews" }
    }}
]});


// $addToSet as an accumulator; can pivot data
var g5 = db.runCommand(
{ aggregate : "article", pipeline : [
    { $project : {
	author : 1,
	tags : 1,
    }},
    { $unwind : "$tags" },
    { $group : {
	_id : { tags : 1 },
	authors : { $addToSet : "$author" }
    }}
]});

articles.js

/* sample articles for aggregation demonstrations */

// make sure we're using the right db; this is the same as "use mydb;" in shell
db = db.getSiblingDB("aggdb");
db.article.drop();

db.article.save( {
    title : "this is my title" , 
    author : "bob" , 
    posted : new Date(1079895594000) , 
    pageViews : 5 , 
    tags : [ "fun" , "good" , "fun" ] ,
    comments : [ 
        { author :"joe" , text : "this is cool" } , 
        { author :"sam" , text : "this is bad" } 
    ],
    other : { foo : 5 }
});

db.article.save( {
    title : "this is your title" , 
    author : "dave" , 
    posted : new Date(4121381470000) , 
    pageViews : 7 , 
    tags : [ "fun" , "nasty" ] ,
    comments : [ 
        { author :"barbara" , text : "this is interesting" } , 
        { author :"jenny" , text : "i like to play pinball", votes: 10 } 
    ],
    other : { bar : 14 }
});

db.article.save( {
    title : "this is some other title" , 
    author : "jane" , 
    posted : new Date(978239834000) , 
    pageViews : 6 , 
    tags : [ "nasty" , "filthy" ] ,
    comments : [ 
        { author :"will" , text : "i don't like the color" } , 
        { author :"jenny" , text : "can i get that in green?" } 
    ],
    other : { bar : 14 }
});

In 2.2 you can do db.result.save(r.result) since 2.2 will save an array into multiple documents (one per array entry).