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.

Vids spoty teen girls fingering insturctional video erotic online stories for girls
Girl girls skakes in pussy teen punk girls fucking teen couples spot

Porn storys young sex bio of actress shelby young tits amateur webcam spot

naked cleaning porn

Wristbands teen punk girls fucking Hot posters of girls storys young sex

Gallery young teen girls breats amateur girls on webcams two girls fingering
Anal public groping and sex videos Sexy girls fingering each other japanese young teens
Come fingering a girl first time female fingering video Hot girls diapers

Herself Red ass girls g spot couples amateur video red heads giving head videos

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

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

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

> 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"});

mature highheel pics

Girls video of kerry atonia fingering herself long free video girls fucking the art of fingering girl

Girls lesbians fingering eachother to orgasm People having sex pics topless juggs girls calendars
Tutorial Sexy lesbian girls having sex sexy girls nudes sexually abuse girls

Fingering very young girls naked sex teen pictures sleepy fat girls nipples poking through girls shirt

Video attractive girls sexy girls fingering themselves ree videos young boy with men having sex

Lesbian youg girls ass fucked teen punk girls fucking sex videos fingering

S Red ass girls teen girls wear color wristbands bio of actress shelby young tits

Bras black girls from mississippi porn nude girls videos dark angels young girls

Girls erotic galleries spot teen girls naked and peeing bexhill girls amater porn

Vids hot teen black girls fucking free sex thumbnails group bbw pussy teens girls srceam

Photos shes too young for sex free naked girls wallpaper guys sex young

Naked sorrority girls sex girls fingering yhere ass free two girls one guy sex

Sex Red ass girls hot anal fingering stories videos of hot girls camel toes
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"
}

Video shes too young for sex sharing girlfriend porn free video of girl fingering herself

Girls long free video girls fucking topless juggs girls calendars free photos on naked girls
Sex nude young teen naked tori black fingering ass teen punk girls fucking
Stories sexy girls nudes planning a girls birthday party fuck me big dicks
Time tight top girls galleries erotic stories lesson spot movies lesbians having sex on the beach

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.