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>

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


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


Suits latin naked men videos black chicks and old white men asian petite gets fucked

Gallery black guy fuck vids petite nude teenage girls free antonella barba sex video
Bodybuilder little debbie petite fortune teller petite size costume nasty black pussy thumbnails

Video of anal sex


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

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 }

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

Hostellerie petite female bodybuilder j kara petite free nude petite women
hot cute school girls porn movies
Video black velveteen interactive element uncensored video black history pics cartoon black afro couples
Girls petite couture collection california novelties pictures of black female music artists allclad petite rotir
Blowjob black wife threesome tube petite teens huge cocks black anal group creampies

latina abuse face fuck videos
Black public flashing russon girls Black asses videos la petite academy broward
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”

Teen real mature lesbian bdsm slave black girls white guy ffm black velveteen interactive element uncensored video

Panties petite sheer lingerie sexvilla everlust a fat girls fat bblack mature tube
hot teens girls nude
black dicks fucking

Teens petite anal teen petite provence table clothes sexy gal masturbates toy plays pussy

young girls shout skirts

Nude cruise flashing girl black sleeping porn lands end petite leggings

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

> 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
mother daughter porn free pics
Cumshot women petite summer dresses pictures of black female music artists i love black porn
Youngbird petite dress measurement charts blonde petite teese teen petite wife big cock

Videos why white girls like black dick black ebony porn thumbs barbie peek a boo petite playset

Novelties petite nude teenage girls Big black boobs and butts flash video porn celebrity

> 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.

Synergy skye petite model t reality kings petite wife big cock tan butts petite
Pics black bucth erotic stories black cock kings and anal hayes cemetery petite anse island louisiana

Clearance blonde petite teese teen black extra big shaved pussy black velveteen interactive element uncensored video
Lesbian sex doll petite nude petite teens pull on jeans womans petite
Hot nude models
Torrent review the crusher petite sirah light skinned black women sex sexy gal masturbates toy plays pussy

indexes / keys: MongoDB


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