The document describes different MongoDB collections and queries. It shows examples of collections that store products, orders, user profiles and analytics data. It also demonstrates queries that retrieve, update and aggregate data across multiple collections using operators like $inc, $push, $unset and $or. The document provides examples of indexing, explain plans, and journaling configurations.

9. Collection “product”: Collection “order”:
{ {
"_id" : productId1, "_id" : orderId,
"name" : name1, "user" : userInfo,
"price" : price1, "items" : [
"desc" : description1 productId1,
}, productId2,
{ productId3
"_id" : productId2, ]
… }

10. Collection “product”: Collection “order”:
{ {
"_id" : productId1, "_id" : orderId,
"name" : name1, "user" : userInfo,
"price" : price1, "items" : [
"desc" : description1 productId1,
} productId2,
{ productId3
> db.product.findOne(“_id”:productId1)
"_id" : productId2, ]
> db.product.findOne(“_id”:productId2)
… }
> db.product.findOne(“_id”:productId3)

11. Collection “order”:
{
"_id" : orderId,
"user" : userInfo,
"items" : [
{
"_id" : productId1,
"name" : name1,
"price" : price1
}, {
"_id" : productId1,
"name" : name1,
"price" : price2
},...
] }

12. Collection “order”:
{ order
"_id" : orderId,
"user" : userInfo,
"items" : [ collection name
{ price order
"_id" : productId1,
"name" : name1, > db.order.find({ items :{
"price" : price1 $elemMatch: { name: name1 }
}, { } } )
"_id" : productId1,
"name" : name1, > db.order.find({ items :{
"price" : price2 $elemMatch: { price:{ $gt: 3000 } }
},... } } )
] }

13. Collection “order”: Collection “performance_rating”:
{ {
"_id" : orderId, "_id" : "employeeId",
"user" : userInfo, "name" : "name",
"items" : [ "post" : "section chief",
{ "abilities" : {
"_id" : productId1, "skillA" : 20,
"name" : name1, "skillC" : 12,
"price" : price1 "skillE" : 18,
}, { "skillF" : 24,
"_id" : productId1, "skillG" : 23
"name" : name1, }
"price" : price2 }
},...
] }

14. Collection “order”: Collection “performance_rating”:
{ {
"_id" : orderId, "_id" : "employeeId",
$elemMatch
"user" : userInfo, "name" : "name",
"items" : [ "post" : "section chief",
{ "abilities" : {
"_id" : productId1, "skillA" : 20,
"name" : name1, "skillC" : 12,
"price" : price1 "skillE" : 18,
}, { "skillF" : 24,
"_id" : productId1, "skillG" : 23
"name" : name1, } 1
"price" : price2 }
},... ”abilities.skillA”
] }

18. Collection “blog”:
{ comment
"_id" : blogId,
"user" : userInfo,
"tags" : [tag1, tag2, tag3] 16MB/document
"comment": [{ In-Place
"_id" : commentId1,
"user" : userInfo1,
"contents" : contents1
}, {
"_id" : commentId2,
"user" : userInfo2,
"contents" : contents2
},...
] }

19. Collection “comment”:
Collection “blog”: {
{ "_id" : commentId,
"_id" : blogId, "user" : userInfo,
"user" : userInfo, > "contents" : contents1,
db.comment.insert({
"tags" : [tag1, tag2, tag3] “_id”:commentId5,
"lastUpdate" : datetime,
"comment" : [ “user”:...
...
commentId1, })
},...
commentId3, {
commentId5 "_id" : commentId5,
],... "user" : userInfo,
}, "contents" : contents1,
> db.blog.update({“_id”:blogId},
{ "lastUpdate" : datetime,
{$push: { “comment”: commentId5 }}
...
})
}

21. > db.coll.stats()
{ ...
#1
"paddingFactor" : 1.4099999999940787,
...
}

23. Collection “access_history”:
{
"_id" : pageId, “start” 6
"start" : time, visitor
"visits" : {
"minutes" : [
“minites” []
[num0, num1, ..., num59],
( )
[num0, num1, ..., num59],
[num0, num1, ..., num59],
“minites” ”hours”
[num0, num1, ..., num59],
0
[num0, num1, ..., num59],
[num0, num1, ..., num59]
],
"hours" : [num0, ..., num5] }
}

24. Collection “access_history”:
{
"_id" : pageId,
"start" : time,
"visits" : {
"minutes" : [
[0,0, ..., 0],
[0,0, ..., 0],
[0,0, ..., 0],
[0,0, ..., 0],
[0,0, ..., 0],
[0,0, ..., 0]
],
"hours" : [0, ..., 0] }
}

25. Collection “access_history”:
{
"_id" : pageId,
$inc
"start" : time,
"visits" : {
"minutes" : [
[0,0, ..., 0],
[3,0, ..., 0],
> db.pages.update({
[0,0, ..., 0], "_id" : pageId,
[0,0, ..., 0], "start" : thisHour
},{
[0,0, ..., 0], "$inc": {"visits.minutes.1.0": 3}
[0,0, ..., 0] })
],
"hours" : [0, ..., 0] }
}

26. > collection.insert(
{ "_id" : 123,
/* other fields */,
"garbage" : someLongString})
> collection.update(
insert gabage
{ "_id": 123 },
{ $unset: { "garbage" : 1} })

30. # :( )
{
"_id" : BinData(5,"iiOI5R6P+dbut19O1mS1lA=="),
"reduce_id" : 0,
_id = user_id
"user_id" : 00000, + date
"date" : 20110727, + timeMilliSec
+ action_type
"action_type" : "a{Make}",
"key_depth" : 1, _id
"action_detail" : { Binary
"kakejiku" : 2,
# Python
"kaizokunojyuu" : 1, bson.Binary(
"matoryo-sika" : 1, hashlib.md5(
str(unique_id)
"syokudai" : 1 ).digest(),
} bson.binary.MD5_SUBTYPE
)
}

33. {
"_id" : id,
"name" : username,
"email" : email,
"phone" : phone,
"twitter" : username,
”fax”
"facebook" : username,
"linkedin" : username,
"google+" : number,
"street" : street
"city" : city,
"state" : state,
"zip" : zip, > db.profile.find({
"fax" : number “fax”: number
})
}

35. {
"_id" : id,
"name" : username,
“online”: {
"email" : email,
"twitter" : username,
...
},
”address”: { ”telephone”
"street" : street
"city" : city,
...
},
“telephone”: {
"phone" : phone, > db.profile.find({
"fax" : number “telephone.fax”: number
})
}

38. # A B C
> db.coll.find({“A”: a, “B”: b, “C”: c})
# C B A
> db.coll.find({“C”: c, “B”: b, “A”: a})
# A B C
> db.coll.find($or: [“A”: a, “B”: b, “C”: c])
# C B A
> db.coll.find($or: [“C”: c, “B”: b, “A”: a])

39. C
A A A
B B
C C C
A
B B

40. C C C
A
B B
C
A A A
B B

42. > db.coll.ensureIndex({ A: 1 })
> db.coll.ensureIndex({ B: 1 })
> db.coll.ensureIndex({ C: 1 })
# find 2 “Select A,B,C”
> db.coll.find({ A: a, B: b, C: c },
{ _id: -1, A: 1, B: 1, C: 1 })
(_id
) Covered Index

47. journaling
:buildIndexes=false
ReplicaSet 3
AWS
Single Instance

48. Slave Delay
1
journaling

49. Micro Instance
Small Instance
32bit
Large Instance
Arbiter
Small

51. $ ls /dbpath/rollback
dbname.collname.2011-08-14T18-27-14.0.bson
$ bsondump dbname.collname.2011-08-14T18-27-14.0.bson
{ "_id" : ... }
{ "_id" : ... }
{ "_id" : ... }
Wed Aug 15 13:33:32 3 objects found

57. DC1 P
DC1 S P
DC2
Master
DC2

59. > db.collname.insert({_id:...})
#
> db.getLastError()
# or
> db.runCommand("getlasterror")

60. > db.runCommand({ getlasterror: 1, fsync: true })
{ "err" : null, "n" : 0, "fsyncFiles" : 2, "ok" : 1 }
> db.runCommand({ getlasterror: 1, j: true })

61. > db.getLastError(2, 5000) // w=2, timeout 5000ms
> db.getLastError("majority")