Porn hot girls on beach pics Amanda bynes naked pics bizarre mom sex pics

very young boy older women porn

girl sexy non nude

Pics sexy school girls strip young teens girls pics teen treesome pics

Ferns xxx fuck free pics free pics of naked mature woman interracial blow job pics

Sports black girls on motorcycle Teen pics videos skinny girls with large tits

HTML5: Download Attribute with Value

1
2
3

 <a href="Picture1.jpg" download="book.jpg">
    Download Book Cover
 </a>

Download Attribute: HTML5


You need to a flashplayer enabled browser to view this YouTube video



Full Free Code: HTML5 Download Attribute with Value

1
2
3
4
5
6
7
8
9
10
11
12
13

< !doctype html>
<html>
<head>
<title>Download Attribute</title>
</head>
<body>
 
 <a href="Picture1.jpg" download="book.jpg">
    Download Book Cover
 </a>
 
</body>
</html>

Bikini oiled girl pics kim kardshian naked pics jailbait pics young

Pics sex curious girls free pics black lactating tits young girl pics xxx

Pics Naked nuns pics big thick brazilian booty porn pics girls who like it anal

Porn holly marie combs pussy pics girls shaved xxx girls feeling boobs

Pics amateur cam girls really young schoolgirls porn video tubes free crazy girls porn

Girls Sex with mother pics gallery girls finger thug jerking big black cock pics

temp: database name
name: collection name

Inserting 1000 Documents

1
2
3
4
5
6
7
8

MongoDB shell version: 2.6.1
connecting to: test
 
> use temp
switched to db temp
 
> for(i = 1; i < = 1000; i++) db.name.insert({a: i, b: i, c: i});
WriteResult({ "nInserted" : 1 })

Basic Cursor 

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

> db.name.find({a: 5})
{ "_id" : ObjectId("53dcd070340ac74e061d7215"), "a" : 5, "b" : 5, "c" : 5 }
 
> db.name.find({a: 5}).explain()
{
        "cursor" : "BasicCursor",
        "isMultiKey" : false,
        "n" : 1,
        "nscannedObjects" : 1000,
        "nscanned" : 1000,
        "nscannedObjectsAllPlans" : 1000,
        "nscannedAllPlans" : 1000,
        "scanAndOrder" : false,
        "indexOnly" : false,
        "nYields" : 7,
        "nChunkSkips" : 0,
        "millis" : 1,
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

explain() method: MongoDB


Porn maked girls having sex Naked girls doing the splits yes books with porn pics
Az ok girls basketball coach movie men and shee sex free pics Sexy girls vidio

Pussy facesitting porn galleries naked girls fighting free video the simpson erotic pics

Facesitting Teen pics videos topless ladies pics naked girls fighting free video
You need to a flashplayer enabled browser to view this YouTube video



Creating Index on fields “a” and “b”

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43

> db.name.ensureIndex({a: 1, b: 1});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}
 
> db.name.find({a: 5}).explain()
{
        "cursor" : "BtreeCursor a_1_b_1",
        "isMultiKey" : false,
        "n" : 1,
        "nscannedObjects" : 1,
        "nscanned" : 1,
        "nscannedObjectsAllPlans" : 1,
        "nscannedAllPlans" : 1,
        "scanAndOrder" : false,
        "indexOnly" : false,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "indexBounds" : {
                "a" : [
                        [
                                5,
                                5
                        ]
                ],
                "b" : [
                        [
                                {
                                        "$minElement" : 1
                                },
                                {
                                        "$maxElement" : 1
                                }
                        ]
                ]
        },
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

indexOnly: true

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41

> db.name.find({a: 5})
{ "_id" : ObjectId("53dcd070340ac74e061d7215"), "a" : 5, "b" : 5, "c" : 5 }
 
> db.name.find({a: 5}, {a: 1, b: 1, _id: 0})
{ "a" : 5, "b" : 5 }
 
> db.name.find({a: 5}, {a: 1, b: 1, _id: 0}).explain()
{
        "cursor" : "BtreeCursor a_1_b_1",
        "isMultiKey" : false,
        "n" : 1,
        "nscannedObjects" : 0,
        "nscanned" : 1,
        "nscannedObjectsAllPlans" : 0,
        "nscannedAllPlans" : 1,
        "scanAndOrder" : false,
        "indexOnly" : true,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "indexBounds" : {
                "a" : [
                        [
                                5,
                                5
                        ]
                ],
                "b" : [
                        [
                                {
                                        "$minElement" : 1
                                },
                                {
                                        "$maxElement" : 1
                                }
                        ]
                ]
        },
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

temp: database name
stu: collection name

Inserting 10 Million Documents

1
2
3
4
5

use temp
switched to db temp
 
for(i=1; i < = 10000000; i++)
db.no.insert({"student_id": i});

index creation in the foreground 

1
2
3
4
5
6
7

> db.stu.ensureIndex({student_id: 1});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}

Background Index Creation: MongoDB


You need to a flashplayer enabled browser to view this YouTube video



index creation in the background

1
2
3
4
5
6
7

> db.stu.ensureIndex({student_id: 1}, {background: true});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}

It takes time to complete the process, as there are 10 Million documents in the collection.

example: database name
company: collection name

Insert documents

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31

MongoDB shell version: 2.6.1
connecting to: test
> use example
switched to db example
 
> db.company.insert({name: "Apple", product: "iPhone"});
WriteResult({ "nInserted" : 1 })
 
> db.company.insert({name: "Motorola", product: "Smart Watch"});
WriteResult({ "nInserted" : 1 })
 
> db.company.insert({name: "Technotip"});
WriteResult({ "nInserted" : 1 })
 
> db.company.insert({name: "Google"});
WriteResult({ "nInserted" : 1 })
 
 
> db.company.find().pretty()
{
        "_id" : ObjectId("53d9f5125d1942042b4e092b"),
        "name" : "Apple",
        "product" : "iPhone"
}
{
        "_id" : ObjectId("53d9f52d5d1942042b4e092c"),
        "name" : "Motorola",
        "product" : "Smart Watch"
}
{ "_id" : ObjectId("53d9f5385d1942042b4e092d"), "name" : "Technotip" }
{ "_id" : ObjectId("53d9f53f5d1942042b4e092e"), "name" : "Google" }

Sparse Index – Unique Key: MongoDB


You need to a flashplayer enabled browser to view this YouTube video



Duplicate key error

1
2
3
4
5
6
7
8
9

> db.company.ensureIndex({product: 1}, {unique: true});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "ok" : 0,
        "errmsg" : "E11000 duplicate key error index: example.company.$product_1
  dup key: { : null }",
        "code" : 11000
}

Sparse Index

1
2
3
4
5
6
7

> db.company.ensureIndex({product: 1}, {unique: true, sparse: true});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}

This creates a sparse index on “product” key/field.

system.indexes collection

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

> db.system.indexes.find().pretty()
{
        "v" : 1,
        "key" : {
                "_id" : 1
        },
        "name" : "_id_",
        "ns" : "example.company"
}
{
        "v" : 1,
        "unique" : true,
        "key" : {
                "product" : 1
        },
        "name" : "product_1",
        "ns" : "example.company",
        "sparse" : true
}

sort() method

Tubes little virgin girls fuck hairy pussy ethnic galleries pics asian girls fucking one guy
Girls free femdom facesitting porn movies japanese girls lick free crazy girls porn
Fuck julia louis dreyfus young pics free pics hot naked young men teen asian naked pics nudism
Pics free pics of amateaur naked pussy abby porn pics free interracial licking porn pics
Pics nasty hardcore girls ebony ayes girls of erotic naked girls s
1
2
3
4
5
6
7
8
9
10
11
12
13

> db.company.find().sort({product: 1}).pretty();
{ "_id" : ObjectId("53d9f5385d1942042b4e092d"), "name" : "Technotip" }
{ "_id" : ObjectId("53d9f53f5d1942042b4e092e"), "name" : "Google" }
{
        "_id" : ObjectId("53d9f52d5d1942042b4e092c"),
        "name" : "Motorola",
        "product" : "Smart Watch"
}
{
        "_id" : ObjectId("53d9f5125d1942042b4e092b"),
        "name" : "Apple",
        "product" : "iPhone"
}

Basic Cursor

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

> db.company.find().sort({product: 1}).explain()
{
        "cursor" : "BasicCursor",
        "isMultiKey" : false,
        "n" : 4,
        "nscannedObjects" : 4,
        "nscanned" : 4,
        "nscannedObjectsAllPlans" : 4,
        "nscannedAllPlans" : 4,
        "scanAndOrder" : true,
        "indexOnly" : false,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

hint() method

1
2
3
4
5
6
7
8
9
10
11

> db.company.find().sort({product: 1}).hint({product: 1}).pretty();
{
        "_id" : ObjectId("53d9f52d5d1942042b4e092c"),
        "name" : "Motorola",
        "product" : "Smart Watch"
}
{
        "_id" : ObjectId("53d9f5125d1942042b4e092b"),
        "name" : "Apple",
        "product" : "iPhone"
}

Btree Cursor

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29

> db.company.find().sort({product: 1}).hint({product: 1}).explain()
{
        "cursor" : "BtreeCursor product_1",
        "isMultiKey" : false,
        "n" : 2,
        "nscannedObjects" : 2,
        "nscanned" : 2,
        "nscannedObjectsAllPlans" : 2,
        "nscannedAllPlans" : 2,
        "scanAndOrder" : false,
        "indexOnly" : false,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "indexBounds" : {
                "product" : [
                        [
                                {
                                        "$minElement" : 1
                                },
                                {
                                        "$maxElement" : 1
                                }
                        ]
                ]
        },
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

Insert documents

1
2
3
4
5
6
7
8
9
10
11
12

> db.system.indexes.find()
{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "foo.test" }
 
 
> db.test.insert({name: "Satish", age: 27});
WriteResult({ "nInserted" : 1 })
 
> db.test.insert({name: "Kiran", age: 28});
WriteResult({ "nInserted" : 1 })
 
> db.test.insert({name: "Satish", age: 27});
WriteResult({ "nInserted" : 1 })

dropDups() To Remove Duplicate Documents: MongoDB


You need to a flashplayer enabled browser to view this YouTube video



Creating unique key on field “name”

1
2
3
4
5
6
7
8
9

> db.test.ensureIndex({name: 1}, {unique: true});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "ok" : 0,
        "errmsg" : "E11000 duplicate key error index: foo.test.$name_1  dup key:
 { : \"Satish\" }",
        "code" : 11000
}

This creates error, as the collection “test” already has duplicate entries/documents.

Create Unique Key by dropping random duplicate entries

1
2
3
4
5
6
7
8
9
10
11

> db.test.ensureIndex({name: 1}, {unique: true, dropDups: true});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}
 
> db.test.find();
{ "_id" : ObjectId("53d8f1268019dce2ce61eb86"), "name" : "Satish", "age" : 27 }
{ "_id" : ObjectId("53d8f12f8019dce2ce61eb87"), "name" : "Kiran", "age" : 28 }

Pics Naked pics of lil kim natalie bad girls club nude pics girls with butt plugs

Az hardcore old bitches free pics beautiful asian sexy girls topless ladies pics

Pics country girls pictures charlotte ton naked pics really young schoolgirls porn video tubes

foo: database name
name: collection name

Primary Key in MongoDB: _id

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

> db.name.insert({_id: 1, a: 1});
WriteResult({ "nInserted" : 1 })
 
> db.system.indexes.find()
{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "foo.name" }
 
> db.name.insert({_id: 1, a: 2});
WriteResult({
        "nInserted" : 0,
        "writeError" : {
                "code" : 11000,
                "errmsg" : "insertDocument :: caused by :: 11000 E11000 
                            duplicate key error index: foo.name.$_id_  dup key: { : 1.0 }"
        }
})

Creating Unique Key/index: MongoDB


You need to a flashplayer enabled browser to view this YouTube video



Creating Key/Index

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

> db.name.insert({a: 1});
WriteResult({ "nInserted" : 1 })
 
> db.name.find()
{ "_id" : ObjectId("53d8cadbbbfe6d81d0bcc364"), "a" : 1 }
{ "_id" : 1, "a" : 1 }
 
> db.name.ensureIndex({a: 1});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}
> db.system.indexes.find()
{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "foo.name" }
{ "v" : 1, "key" : { "a" : 1 }, "name" : "a_1", "ns" : "foo.name" }

Here we create index on field “a”.

Inserting duplicate values into key field

1
2
3
4
5
6
7

> db.name.insert({a: 1});
WriteResult({ "nInserted" : 1 })
 
> db.name.find()
{ "_id" : ObjectId("53d8cadbbbfe6d81d0bcc364"), "a" : 1 }
{ "_id" : 1, "a" : 1 }
{ "_id" : ObjectId("53d8cb4dbbfe6d81d0bcc365"), "a" : 1 }

Removing documents and Key/Index on field “a”

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

> db.name.find()
{ "_id" : ObjectId("53d8cadbbbfe6d81d0bcc364"), "a" : 1 }
{ "_id" : 1, "a" : 1 }
{ "_id" : ObjectId("53d8cb4dbbfe6d81d0bcc365"), "a" : 1 }
 
> db.name.remove({a: 1});
WriteResult({ "nRemoved" : 3 })
 
> db.name.find()
 
> db.name.dropIndex({a: 1});
{ "nIndexesWas" : 2, "ok" : 1 }
 
> db.system.indexes.find()
{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "foo.name" }

Creating Unique key/index on field “a”

1
2
3
4
5
6
7

> db.name.ensureIndex({a: 1}, {unique: true});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}

Duplicate key error on our Unique Key!

1
2
3
4
5
6
7
8
9
10
11
12

> db.name.find()
{ "_id" : ObjectId("53d8cb85bbfe6d81d0bcc366"), "a" : 1 }
 
> db.name.insert({a: 1});
WriteResult({
        "nInserted" : 0,
        "writeError" : {
                "code" : 11000,
                "errmsg" : "insertDocument :: caused by :: 11000 E11000 
                            duplicate key error index: foo.name.$a_1  dup key: { : 1.0 }"
        }
})

Now if we try to insert duplicate values into field “a” it throws duplicate key error.

foo: database name
name: collection name

Insert a document

1
2
3
4
5
6
7
8

MongoDB shell version: 2.6.1
connecting to: test
 
> use foo
switched to db foo
 
> db.name.insert({a: 1, b: 2, c: 3});
WriteResult({ "nInserted" : 1 })

Here we insert {a: 1, b: 2, c: 3} into “name” collection.

Multi-key Indexes and Arrays: MongoDB


You need to a flashplayer enabled browser to view this YouTube video



Basic Cursor

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

> db.name.find({a: 1, b: 2})
{ "_id" : ObjectId("53d8982b79142c385cddc607"), "a" : 1, "b" : 2, "c" : 3 }
 
> db.name.find({a: 1, b: 2}).explain()
{
        "cursor" : "BasicCursor",
        "isMultiKey" : false,
        "n" : 1,
        "nscannedObjects" : 1,
        "nscanned" : 1,
        "nscannedObjectsAllPlans" : 1,
        "nscannedAllPlans" : 1,
        "scanAndOrder" : false,
        "indexOnly" : false,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

Lets create index on a and b

1
2
3
4
5
6
7

> db.name.ensureIndex({a: 1, b: 1});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}

Btree Cursor with multi-key as false

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31

> db.name.find({a: 1, b: 2}).explain()
{
        "cursor" : "BtreeCursor a_1_b_1",
        "isMultiKey" : false,
        "n" : 1,
        "nscannedObjects" : 1,
        "nscanned" : 1,
        "nscannedObjectsAllPlans" : 1,
        "nscannedAllPlans" : 1,
        "scanAndOrder" : false,
        "indexOnly" : false,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "indexBounds" : {
                "a" : [
                        [
                                1,
                                1
                        ]
                ],
                "b" : [
                        [
                                2,
                                2
                        ]
                ]
        },
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

Lets insert another document

1
2

> db.name.insert({a: [0, 1, 2], b: 2, c: 3});
WriteResult({ "nInserted" : 1 })

Btree Cursor with Multi-key true

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37

> db.name.find({a: 1, b: 2})
{ "_id" : ObjectId("53d8982b79142c385cddc607"), 
  "a" : 1, "b" : 2, "c" : 3 }
{ "_id" : ObjectId("53d8986f79142c385cddc608"), 
  "a" : [ 0, 1, 2 ], "b" : 2, "c": 3 }
 
> db.name.find({a: 1, b: 2}).explain()
{
        "cursor" : "BtreeCursor a_1_b_1",
        "isMultiKey" : true,
        "n" : 2,
        "nscannedObjects" : 2,
        "nscanned" : 2,
        "nscannedObjectsAllPlans" : 2,
        "nscannedAllPlans" : 2,
        "scanAndOrder" : false,
        "indexOnly" : false,
        "nYields" : 0,
        "nChunkSkips" : 0,
        "millis" : 0,
        "indexBounds" : {
                "a" : [
                        [
                                1,
                                1
                        ]
                ],
                "b" : [
                        [
                                2,
                                2
                        ]
                ]
        },
        "server" : "Satish-PC:27017",
        "filterSet" : false
}

Multi-Key Condition in MongoDB

1
2
3
4
5
6
7
8
9

> db.name.insert({a: [0, 1, 2], b: [3, 4], c: 3});
WriteResult({
        "nInserted" : 0,
        "writeError" : {
                "code" : 10088,
                "errmsg" : "insertDocument :: caused by :: 10088 cannot 
                            index parallel arrays [b] [a]"
        }
})

Sample document

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22

> use temp
switched to db temp
> show collections
no
system.indexes
 
> db.no.find({"student_id": {$lt: 3}}).pretty()
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cda"),
        "student_id" : 0,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cdb"),
        "student_id" : 1,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cdc"),
        "student_id" : 2,
        "name" : "Satish"
}

Fetch Index and Drop / remove Index: MongoDB


You need to a flashplayer enabled browser to view this YouTube video



We shall take a look at “system.indexes” collection

1
2
3
4
5

> db.system.indexes.find()
{ "v" : 1, "key" : { "_id" : 1 }, 
           "name" : "_id_", "ns" : "temp.no" }
{ "v" : 1, "key" : { "student_id" : 1 }, 
           "name" : "student_id_1", "ns" : "temp.no" }

Create “another” collection

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

> db.another.insert({"name": "Satish", "age": 27});
WriteResult({ "nInserted" : 1 })
 
> show collections
another
no
system.indexes
 
> db.system.indexes.find()
{ "v" : 1, "key" : { "_id" : 1 }, 
           "name" : "_id_", "ns" : "temp.no" }
{ "v" : 1, "key" : { "student_id" : 1 }, 
           "name" : "student_id_1", "ns" : "temp.no" }
{ "v" : 1, "key" : { "_id" : 1 }, 
           "name" : "_id_", "ns" : "temp.another" }

To get index on individual collection

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Pics ebony girls ride the sybian kendall bikini pics japanese girls lick
Pics free peter north porn pics sexy naked girls playing sports Amanda bynes naked pics
Pics super really hot young girls free femdom facesitting porn movies asian girls fucking one guy
Girls pubescent girl pics hardcore old bitches free pics free pics hot naked young men
> db.another.getIndexes()
[
        {
                "v" : 1,
                "key" : {
                        "_id" : 1
                },
                "name" : "_id_",
                "ns" : "temp.another"
        }
]
 
> db.no.getIndexes()
[
        {
                "v" : 1,
                "key" : {
                        "_id" : 1
                },
                "name" : "_id_",
                "ns" : "temp.no"
        },
        {
                "v" : 1,
                "key" : {
                        "student_id" : 1
                },
                "name" : "student_id_1",
                "ns" : "temp.no"
        }
]

Removing / deleting / dropping – index / key

1
2
3
4
5
6
7
8
9
10
11
12
13
14

> db.no.dropIndex({"student_id": 1});
{ "nIndexesWas" : 2, "ok" : 1 }
 
> db.no.getIndexes()
[
        {
                "v" : 1,
                "key" : {
                        "_id" : 1
                },
                "name" : "_id_",
                "ns" : "temp.no"
        }
]

Lets learn to create index and to optimize the database in MongoDB.

1
2
3
4
5

use temp
switched to db temp
 
for(i=0; i< = 10000000; i++)
db.no.insert({"student_id": i, "name": "Satish"});

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119

MongoDB shell version: 2.6.1
connecting to: test
> show dbs
admin    (empty)
daily    0.078GB
local    0.078GB
nesting  0.078GB
school   0.078GB
temp     3.952GB
test     0.078GB
> use temp
switched to db temp
> show collections
no
system.indexes
> db.no.find().pretty()
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cda"),
        "student_id" : 0,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cdb"),
        "student_id" : 1,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cdc"),
        "student_id" : 2,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cdd"),
        "student_id" : 3,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cde"),
        "student_id" : 4,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cdf"),
        "student_id" : 5,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce0"),
        "student_id" : 6,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce1"),
        "student_id" : 7,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce2"),
        "student_id" : 8,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce3"),
        "student_id" : 9,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce4"),
        "student_id" : 10,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce5"),
        "student_id" : 11,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce6"),
        "student_id" : 12,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce7"),
        "student_id" : 13,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce8"),
        "student_id" : 14,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ce9"),
        "student_id" : 15,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cea"),
        "student_id" : 16,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ceb"),
        "student_id" : 17,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cec"),
        "student_id" : 18,
        "name" : "Satish"
}
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833ced"),
        "student_id" : 19,
        "name" : "Satish"
}
Type "it" for more
 
> it

index creation: MongoDB


You need to a flashplayer enabled browser to view this YouTube video



1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

> db.no.find({"student_id": 5}).pretty()
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cdf"),
        "student_id" : 5,
        "name" : "Satish"
}
 
 
> db.no.findOne({"student_id": 5});
{
        "_id" : ObjectId("53c9020abcdd1ea7fb833cdf"),
        "student_id" : 5,
        "name" : "Satish"
}
> db.no.find({"student_id": 5000000}).pretty()
{
        "_id" : ObjectId("53c90ca6bcdd1ea7fbcf881a"),
        "student_id" : 5000000,
        "name" : "Satish"
}

Creating index

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

> show collections
no
system.indexes
 
> db.system.indexes.find()
{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "temp.no" }
 
> db.no.ensureIndex({"student_id": 1});
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}
 
> db.system.indexes.find()
{ "v" : 1, "key" : { "_id" : 1 }, 
                     "name" : "_id_", "ns" : "temp.no" }
{ "v" : 1, "key" : { "student_id" : 1 }, 
                     "name" : "student_id_1", "ns" : "temp.no" }

1
2
3
4
5
6
7
8
9
10
11
12
13

> db.no.find({"student_id": 5000000}).pretty()
{
        "_id" : ObjectId("53c90ca6bcdd1ea7fbcf881a"),
        "student_id" : 5000000,
        "name" : "Satish"
}
> db.no.find({"student_id": 10000000}).pretty()
{
        "_id" : ObjectId("53c914adbcdd1ea7fb1bd35a"),
        "student_id" : 10000000,
        "name" : "Satish"
}
>

So the querys/commands can be optimized by creating indexes on frequently accessed fields.

Lets look at some basics of indexes in MongoDB.

indexes / keys: MongoDB


You need to a flashplayer enabled browser to view this YouTube video