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// Let's say there is a fruits collection where it contains documents as follow
db.fruits.insert({'name':'pear'})
db.fruits.insert({'name':'apple'})
db.fruits.insert({'name':'pear'})

// Then, we want to prevent another document with name = pear can be inserted into fruits collection
// In the other words, we want to make the name property become unique.
// And also, duplicated document would be removed

db.fruits.ensureIndex({'name':1}, {'unique':true, 'dropDups':true})

saintc0d3r

// Let's create a tournaments database where it has fighters table with few documents in it 
use tournaments
db.fighters.insert({'name':'Ryu', 'ultimate': 'shinkuu hadou ken'})
db.fighters.insert({'name':'Ken', 'ultimate': 'Shoryureppa'})
db.fighters.insert({'name':'Dan'})
db.fighters.insert({'name':'Zangief'})

// We want to put an index on the name & ultimate fields to speed its query by name's performance (no multi key index applied)
db.fighters.ensureIndex({'name':1, 'ultimate':1})

saintc0d3r

// Let's say that there is a 'foo' collection has 10 mill documents in it
use foobar
for(var i=0;i<10000000;i++){db.foo.insert({'a':i,'b':i,'c':i})}

// Then, we'll add indexes for a,b,c on the 'foo' collection
db.foo.ensureIndex({'a':1, 'b':1, 'c':1})

// Let's do querying a doco by a field as the search criteria then note the millis value in the displayed result
db.foo.find({'a': 5678545}).explain()

saintc0d3r

// To show the statistic of a foo collection
db.foo.stats()

// To show the size of total index size of foo collection (in bytes)
db.foo.totalIndexSize()

saintc0d3r

// Let's say there is foobar db which have foo collection with some documents in it
use foo
var i = 0
for(i=0;i < 100;i++)(db.bar.insert({'a':i, 'b':i, 'c':i, 'd':i}))

// and we create indexes for each field
db.bar.ensureIndex({'a':1})
db.bar.ensureIndex({'b':1})
db.bar.ensureIndex({'c':1})
db.bar.ensureIndex({'d':1})

saintc0d3r

// Hint sample

var MongoClient = require('mongodb').MongoClient;

function query_hint_helper(db, query, hint, close_db){
	var cursor = db.collection('bar').find(query, {}, hint);

	// Explain the query
	cursor.explain(function(err, explain_output){
		if (err) throw err;

saintc0d3r

// Suppose, we have 10000000 documents stored in bar collections (foo database)
use foo
for(var i = 0; i< 10000000; i++)(db.bar.insert({'a':i, 'b':i, 'c':i}))

// We create indexes for them 
db.bar.ensureIndex({'a':1})
db.bar.ensureIndex({'b':1})
db.bar.ensureIndex({'c':1})
db.bar.ensureIndex({'a':1, 'b':1,'c':1})

saintc0d3r

// Let's say , we have a geo database that has places collection in it
use geo
db.places.insert({'name': 'pepito', 'type': 'dept. store', 'location': [40, 70]})
db.places.insert({'name': 'circle-k', 'type': 'mini mart', 'location': [40.232, -74.343]})
db.places.insert({'name': 'ayunadi', 'type': 'grocery', 'location': [41.232, -75.343]})

// Next, we want to put an index on the location field. 
// Since the location's value is the x-y coordinate of a place, we'll put '2d' index on it.
var index = {'location': '2d', 'type':1}
db.places.ensureIndex(index)

saintc0d3r

// Let's say , we have a geo database that has places collection in it
use geo
db.places.insert({'name': 'pepito', 'city': 'Badung, Bali', 'type': 'retail', 'location': {'type': 'Point', 'coordinates': [-8.738151,-25.1735585]}})
db.places.insert({'name': 'circle-k', 'city': 'Tuban, Bali', 'type': 'mini mart', 'location': {'type': 'Point', 'coordinates': [-8.7358627,-25.168867000000006]}})
db.places.insert({'name': 'ayunadi', 'city': 'Tuban, Bali', 'type': 'grocery', 'location': {'type': 'Point', 'coordinates': [-8.7394041,-25.1675752]}})

// Next, we'll put '2dsphere' index on the location field
// Caution: 2dsphere is limited to the range -180,180 for x coordinate/longitude, and -90,90 for y coordinate/latitude !
var index = {'location':'2dsphere', 'type':1, 'city':1}
db.places.ensureIndex(index)

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// Let's say we have a documents db where it has a sentences collection
use documents
db.sentences.insert({'words': 'Cat moss granite.'})
db.sentences.insert({'words': 'dog tree ruby.'})
db.sentences.insert({'words': 'dog tree obsidian.'})
db.sentences.insert({'words': 'dog tree granite.'})
db.sentences.insert({'words': 'dog shrub ruby.'})
db.sentences.insert({'words': 'dog shrub obsidian.'})
db.sentences.insert({'words': 'dog shrub granite.'})
db.sentences.insert({'words': 'dog moss ruby.'})