SlideShare uma empresa Scribd logo
1 de 85
Baixar para ler offline
{
    "_id" : <unspecified>, //file      ID
    "length" : data_number, //          bytes
    "chunkSize" : data_number, //               :256KB
    "uploadDate" : data_date, //file
    "md5" : data_string //"filemd5"
}
{
    "filename" : data_string,
    "contentType" : data_string,
    "aliases" : data_array of data_string,
    "metadata" : data_object,
}
{
    "_id" : <unspecified>, //chunk           ID

    "files_id" : <unspecified>, //file            _id

    "n" : chunk_number, //0          chunk

        0,1,2...   chunk

    "data" : data_binary, // BSON

}
> db.fs.chunks.ensureIndex(
                    {files_id:1, n:1}, {unique: true});




> db.fs.chunks.findOne({files_id: myFileID, n: 0});
➜ ~ mongofiles --help
usage: mongofiles [options] command [gridfs filename]
command:
  one of (list|search|put|get)
  list - file
 search - file
 put - file
 get - file
 delete - file
➜ ~ mongofiles list
connected to: 127.0.0.1

➜ ~ mongofiles put ByeForNow.mp3
connected to: 127.0.0.1
added file: { _id: ObjectId('4df17f8d9d47ba5c0247e72e'),
filename: "ByeForNow.mp3", chunkSize: 262144, uploadDate:
new Date(1307672462538), md5:
"9ee9472200a2e18bf376ce622c3b0055", length: 11183104 }
done!

➜   ~   mongofiles list -v // -v
Fri Jun 10 11:21:05 creating new connection to:127.0.0.1
Fri Jun 10 11:21:05 BackgroundJob starting:
connected to: 127.0.0.1
ByeForNow.mp3   11183104
➜ ~ mongofiles put Maria.mp3
connected to: 127.0.0.1
added file: { _id: ObjectId('4df181fc5e354129e833193f'),
filename: "Maria.mp3", chunkSize: 262144, uploadDate: new
Date(1307673086293), md5:
"9d4f424fa1843711e196e502d8a00183", length: 12225353 }
done!
➜ ~ mongofiles list
connected to: 127.0.0.1
ByeForNow.mp3   11183104
Maria.mp3       12225353
➜ ~ mongofiles list M
connected to: 127.0.0.1
Maria.mp3       12225353
➜ ~ mongofiles search .mp3
connected to: 127.0.0.1
ByeForNow.mp3   11183104
Maria.mp3       12225353
➜   ~   mkdir tmp //      get
➜ ~ cd tmp
➜ mongofiles get Maria.mp3
connected to: 127.0.0.1
done write to: Maria.mp3
➜ ls
Maria.mp3
➜ mongofiles get Bye
ERROR: file not found
➜ mongofiles get ByeForNow.mp3
done write to: ByeForNow.mp3
➜ md5 Maria.mp3
MD5 (Maria.mp3) = 9d4f424fa1843711e196e502d8a00183
➜ md5 ../Maria.mp3
MD5 (../Maria.mp3) = 9d4f424fa1843711e196e502d8a00183
> db.fs.files.find().forEach(printjson)
{
        "_id" : ObjectId("4df17f8d9d47ba5c0247e72e"),
        "filename" : "ByeForNow.mp3",
        "chunkSize" : 262144,
        "uploadDate" : ISODate("2011-06-10T02:21:02.538Z"),
        "md5" : "9ee9472200a2e18bf376ce622c3b0055",
        "length" : 11183104
}
{
        "_id" : ObjectId("4df181fc5e354129e833193f"),
        "filename" : "Maria.mp3",
        "chunkSize" : 262144,
        "uploadDate" : ISODate("2011-06-10T02:31:26.293Z"),
        "md5" : "9d4f424fa1843711e196e502d8a00183",
        "length" : 12225353
}
> db.fs.chunks.findOne(
     {n:0,files_id:ObjectId("4df181fc5e354129e833193f")})
{
  "_id" : ObjectId("4df181fcd40994ca1de28d09"),
  "files_id" : ObjectId("4df181fc5e354129e833193f"),
  "n" : 0,
  "data" : BinData(0,"SUQzAwAAAABQdlRSQ0sAAAACAAAAM1RJVDIA
AAAHAAAAg32DioNBVUZJRAAAAGYAAGh0dHA6Ly93d3cuY2RkYi5jb20vaWQ
zL3RhZ2luZm8xLmh0bWwAM0NEM00xMTBRMjA3NTYwOTc4VjY4MTBCQTlBNj
UzN0JCQUQ1QTgyOUE4NTRCRkQ2QTdBRjNQOAAAAAAAAAAAAEdFT0IAACNgA
AAAYXBwbGljYX...)
}
>   db.fs.chunks.ensureIndex({files_id: 1});
>   db.runCommand({ shardcollection : "test.fs.chunks", key :
{   files_id : 1 }})
{   "collectionsharded" : "test.fs.chunks", "ok" : 1 }
MongoDB   GridFS
Replace Amazon S3 with MongoDB GridFS and Grails
{   loc   :   [   50 , 30 ] }
{   loc   :   {   x : 50 , y : 30 } }
{   loc   :   {   foo : 50 , y : 30 } }
{   loc   :   {   long : 40.739037, lat: 73.992964 } }
db.places.ensureIndex( { loc : "2d" } )
db.places.ensureIndex( { loc : "2d" } , { min : -500 , max : 500 } )
db.places.find( { loc : [50,50] } )




db.places.find( { loc : { $near : [50,50] } } )
db.places.find( { loc : { $near : [50,50] } } ).limit(20)
db.places.find( { loc : { $near : [50,50] ,
                          $maxDistance : 5 } } ).limit(20)
//
> box = [[40.73083, -73.99756], [40.741404, -73.988135]]
> db.places.find({"loc" : {"$within" : {"$box" : box}}})

//
> center = [50, 50]
> radius = 10
> db.places.find({"loc" : {"$within" : {"$center" : [center, radius]}}})

// v1.9
> polygonA = [ [ 10, 20 ], [   10, 40 ], [ 30, 40 ], [ 30, 20 ] ]
> polygonB = { a : { x : 10,   y : 20 }, b : { x : 15, y : 25 }, c : { x :
20, y : 20 } }
> db.places.find({ "loc" : {   "$within" : { "$polygon" : polygonA } } })
> db.places.find({ "loc" : {   "$within" : { "$polygon" : polygonB } } })
> db.runCommand( { geoNear : "places" , near : [ 50 , 50 ], num : 10,
query : { type : "museum" } } );
{
       "ns" : "test.places",
       "near" : "1100110000001111110000001111110000001111110000001111",
       "results" : [
               {
                       "dis" : 69.29646421910687,
                       "obj" : {
                               "_id" : ObjectId("4b8bd6b93b83c574d8760280"),
                               "y" : [
                                       1,
                                       1
                               ],
                               "category" : "Coffee"
                       }
               },
               {
                       "dis" : 69.29646421910687,
                       "obj" : {
                               "_id" : ObjectId("4b8bd6b03b83c574d876027f"),
                                       1
...}
MongoDB
> db.points.insert({ pos : { long : 30, lat : 30 } })
> db.points.insert({ pos : { long : -10, lat : -20 } })
> db.points.ensureIndex({ pos : "2d" })

> db.points.find({ pos: { $nearSphere: [0,0], $maxDistance : 0.4 } })
{ "_id" : ObjectId("4df11e47b8e84370f84afdd3"), "pos" : { "long" : -10,
"lat" : -20 } }
> var earthRadius = 6378 // km
> var range = 3000 // km
> distances = db.runCommand({ geoNear : "points", near : [0, 0], spherical :
true, maxDistance : range / earthRadius }).results
[
        {
                "dis" : 0.3886630122897946, //
                "obj" : {
                        "_id" : ObjectId("4df11e47b8e84370f84afdd3"),
                        "pos" : {
                                "long" : -10,
                                "lat" : -20
                        }
                }
        }
]
> pointDistance = distances[0].dis * earthRadius
2478.89269238431 // km
http://www.slideshare.net/doryokujin/mongo-sharding
~   mkdir    -p   shard/shard00
~   mkdir    -p   shard/shard01
~   mkdir    -p   shard/shard02
~   mkdir    -p   shard/config




~   mongod   --shardsvr --port 27017 --dbpath    shard/shard00
~   mongod   --shardsvr --port 27018 --dbpath    shard/shard01
~   mongod   --shardsvr --port 27019 --dbpath    shard/shard02
~   mongod   --configsvr --port 27020 --dbpath   shard/config
~   mongos   --configdb localhost:27020 --port   27021
➜   ~    mongo localhost:27021 // mongos

MongoDB shell version: 1.8.0
connecting to: localhost:27021/test
> show dbs
config    0.1875GB // sharding

> db.adminCommand( { addshard: "localhost:27017", name: "shard00" } )
{ "shardAdded" : "shard00", "ok" : 1 }
> db.adminCommand( { addshard: "localhost:27018", name: "shard01" } )
{ "shardAdded" : "shard01", "ok" : 1 }
> db.adminCommand( { addshard: "localhost:27019", name: "shard02" } )
{ "shardAdded" : "shard02", "ok" : 1 }
//       mongos

> db.adminCommand( { enablesharding : "test" } )
{ "ok" : 1 }
> db.adminCommand( { moveprimary : "test", to : "shard02" } );
{ "primary " : "shard02:localhost:27019", "ok" : 1 }
> db.adminCommand( { shardcollection : "test.myshard", key : { n : 1 } } )
{ "collectionsharded" : "test.myshard", "ok" : 1 }
//       mongos

> db.adminCommand({split : "test.myshard", middle : { n: 0 } } )
{ "ok" : 1 }
> db.adminCommand({split : "test.myshard", middle : { n: 1 } } )
{ "ok" : 1 }
> db.adminCommand({split : "test.myshard", middle : { n: 2 } } )
{ "ok" : 1 }
> db.printShardingStatus() //

--- Sharding Status ---
  sharding version: { "_id" : 1, "version" : 3 }
  shards:
      { "_id" : "shard00", "host" : "localhost:27017" }
      { "_id" : "shard01", "host" : "localhost:27018" }
      { "_id" : "shard02", "host" : "localhost:27019" }
  databases:
        { "_id" : "admin", "partitioned" : false, "primary" : "config" }
        { "_id" : "test", "partitioned" : true, "primary" : "shard02" }
        test.myshard chunks:
            shard02 4
 { "n" : { $minKey : 1 } } -->> { "n" : 0 } on : shard02 { "t" : 1000, "i" : 1 }
 { "n" : 0 } -->> { "n" : 1 } on : shard02 { "t" : 1000, "i" : 3 }
 { "n" : 1 } -->> { "n" : 2 } on : shard02 { "t" : 1000, "i" : 5 }
 { "n" : 2 } -->> { "n" : { $maxKey : 1 } } on : shard02 { "t" : 1000, "i" : 6 }
//       mongos

> db.adminCommand({moveChunk: "test.myshard", find: { n: 0 }, to: "shard00" });
{ "millis" : 1051, "ok" : 1 }
> db.adminCommand({moveChunk: "test.myshard", find: { n: 1 }, to: "shard01" });
{ "millis" : 1046, "ok" : 1 }
> db.adminCommand({moveChunk :"test.myshard", find: { n: 2 }, to: "shard02" });
{ "ok" : 0, "errmsg" : "that chunk is already on that shard" }
> db.printShardingStatus()
--- Sharding Status ---
  sharding version: { "_id" : 1, "version" : 3 }
  shards:
      { "_id" : "shard00", "host" : "localhost:27017" }
      { "_id" : "shard01", "host" : "localhost:27018" }
      { "_id" : "shard02", "host" : "localhost:27019" }
  databases:
        { "_id" : "admin", "partitioned" : false, "primary" : "config" }
        { "_id" : "test", "partitioned" : true, "primary" : "shard02" }
        test.myshard chunks:
               shard02 2
               shard00 1
               shard01 1
   { "n" : { $minKey : 1 } } -->> { "n" : 0 } on : shard02 { "t" : 3000, "i" : 1 }
   { "n" : 0 } -->> { "n" : 1 } on : shard00 { "t" : 2000, "i" : 0 }
   { "n" : 1 } -->> { "n" : 2 } on : shard01 { "t" : 3000, "i" : 0 }
   { "n" : 2 } -->> { "n" : { $maxKey : 1 } } on : shard02 { "t" : 1000, "i" : 6 }
//         mongos

> for(var m=0; m<100; m++){ db.myshard.insert({n: m % 3}) } // n =0,1,2,0,1,...


> printShardingSizes()      // Shard

     ...
     test.myshard chunks:
     { "n" : { $minKey : 1 } } -->> { "n" : 0 } on : shard02 { "estimate" :
false, "size" : 0, "numObjects" : 0 }
     { "n" : 0 } -->> { "n" : 1 } on : shard00 { "estimate" : false, "size" :
1224, "numObjects" : 34 }
     { "n" : 1 } -->> { "n" : 2 } on : shard01 { "estimate" : false, "size" :
1188, "numObjects" : 33 }
     { "n" : 2 } -->> { "n" : { $maxKey : 1 } } on : shard02 { "estimate" :
false, "size" : 1188, "numObjects" : 33 }
➜    ~   mongo localhost:27017
> db.myshard.count()
34
> db.myshard.distinct("n")
[ 0 ]
➜    ~   mongo localhost:27018
> db.myshard.count()
33
> db.myshard.distinct("n")
[ 1 ]
➜    ~   mongo localhost:27019
> db.myshard.count()
33
> db.myshard.distinct("n")
[ 2 ]
> db.adminCommand( { addshard: "set00/delta1:27017,delta2:27017", name:
"shard00" } )
{ "shardAdded" : "shard00", "ok" : 1 }
> db.adminCommand( { addshard: "set01/delta3:27018,delta4:27018", name:
"shard01" } )
{ "shardAdded" : "shard01", "ok" : 1 }
> db.adminCommand( { addshard: "set02/delta5:27019,delta6:27019", name:
"shard02" } )
{ "shardAdded" : "shard02", "ok" : 1 }
Map-Reduce on Mongo
db.mycoll.mapReduce(
 map : <map                >,

 reduce : <reduce                >

 [, finalize : <finalize             >]

 [, query : <                        >]

 [, sort : <

     reduce                                       >]

 [, out : <                     >]

 [, scope : <object where fields go into javascript global scope >]

);
db.people.insert({userId:1,   age:24, type:"A"})
db.people.insert({userId:2,   age:47, type:"B"})
db.people.insert({userId:3,   age:34, type:"C"})
db.people.insert({userId:4,   age:4,   type:"B"})
db.people.insert({userId:5,   age:14, type:"A"})
db.people.insert({userId:6,   age:29, type:"C"})
db.people.insert({userId:7,   age:39, type:"C"})
db.people.insert({userId:8,   age:42, type:"B"})
db.people.insert({userId:9,   age:56, type:"A"})
db.people.insert({userId:10, age:12, type:"A"})
m = function() {
  emit(this.type, { age: this.age, num: 1 } );
}
r = function(key, values) {
    var result = { age: 0, num: 0 };
    values.forEach( function(value){
        result.age += value.age; // age
        result.num += value.num; //
    } );
    return result;
}
r = function(key, values) {
    var num = 0;
    var sum = 0;
    values.forEach( function(value){
        sum += value.age; // age
        num += value.num; //
    } );
    return sum/num;
}
m = function() {
  emit(this.type, { age: this.age, num: 1 } );
}
r = function(key, values) {
    var result = { age: 0, num: 0 };
    values.forEach( function(value){
        result.age += value.age; // age
        result.num += value.num; //
    } );
    return result;
}
m = function() {
  emit(this.type, { age: this.age, num: 1 } );
}
r = function(key, values) {
    var result = { age: 0, num: 0 };
    values.forEach( function(value){
        result.age += value.age; //
        result.num += value.num; //
    } );
    return result;
}
f = function( key, result ){
    result.avg = result.age / result.num;
    return result;
}
> res = db.people.mapReduce( m , r ,
        { finalize : f , out : "mr_out", verbose: true });
{
        "result" : "mr_out", //
        "timeMillis" : 18,     //
        "timing" : {
                "mapTime" : NumberLong(1),
                "emitLoop" : 12,
                "total" : 18
        },
        "counts" : {
                "input" : 10, // 10
                "emit" : 10,        // 10   emit
                "output" : 3        // 3
        },
        "ok" : 1,
}
> db.mr_out.find()
{ "_id" : "A",
  "value" : { "age" : 106, "num" : 4, "avg" : 26.5 } }
{ "_id" : "B",
  "value" : { "age" : 93, "num" : 3, "avg" : 31 } }
{ "_id" : "C",
  "value" : { "age" : 102, "num" : 3, "avg" : 34 } }
> res = db.people.mapReduce( m , r ,
  { finalize : f , out : "mr_out", query: { age: { $gte: 20 } } });
{
         "result" : "mr_out",
         "timeMillis" : 35,
         "counts" : {
                 "input" : 7, // 3
                "emit" : 7,
                "output" : 3
        },
        "ok" : 1,
}
> db.mr_out.find() //

{ "_id" : "A",
  "value" : { "age" : 80, "num" : 2, "avg" : 40 } }
{ "_id" : "B",
  "value" : { "age" : 89, "num" : 2, "avg" : 44.5 } }
{ "_id" : "C",
  "value" : { "age" : 102, "num" : 3, "avg" : 34 } }
db.items.insert({ date: "2011-06-01", item: "apple", price: 100 })
db.items.insert({ date: "2011-06-01", item: "banana", price: 200 })
db.items.insert({ date: "2011-06-01", item: "apple" , price :100})
db.items.insert({ date: "2011-06-02", item: "orange", price: 50 })
db.items.insert({ date: "2011-06-02", item: "orange", price: 50 })
db.items.insert({ date: "2011-06-02", item: "apple", price: 100 })
m = function() { emit(this.item, this.price); }
r = function(key,values) {
      var result = 0;
      values.forEach( function(value){ result += value } );
      return result;
}
> res = db.items.mapReduce( m, r, { query: {date: "2011-06-01"} ,
out: {replace: "mr_out2"}} );
{
        "result" : "mr_out2",
        "timeMillis" : 10,
        "counts" : {
                "input" : 3,
                "emit" : 3,
                "output" : 2
        },
        "ok" : 1,
}
>db.mr_out2.find()
{ "_id" : "apple", "value" : 200 }
{ "_id" : "banana", "value" : 200 }
> res = db.items.mapReduce( m, r,
  { query: {date: "2011-06-02"} , out: {reduce: "mr_out2"}} );
{
        "result" : "mr_out2",
        "timeMillis" : 23,
        "counts" : {
                "input" : 3,
                "emit" : 3,
                "output" : 3
        },
        "ok" : 1,
}
> db.mr_out2.find()
{ "_id" : "apple", "value" : 300 } //
{ "_id" : "banana", "value" : 200 } //
{ "_id" : "orange", "value" : 100 } //
MongoDB GridFS Stores and Retrieves Files
MongoDB GridFS Stores and Retrieves Files

Mais conteúdo relacionado

Mais procurados

MySQL flexible schema and JSON for Internet of Things
MySQL flexible schema and JSON for Internet of ThingsMySQL flexible schema and JSON for Internet of Things
MySQL flexible schema and JSON for Internet of ThingsAlexander Rubin
 
San Francisco Java User Group
San Francisco Java User GroupSan Francisco Java User Group
San Francisco Java User Groupkchodorow
 
MongoDB Europe 2016 - Enabling the Internet of Things at Proximus - Belgium's...
MongoDB Europe 2016 - Enabling the Internet of Things at Proximus - Belgium's...MongoDB Europe 2016 - Enabling the Internet of Things at Proximus - Belgium's...
MongoDB Europe 2016 - Enabling the Internet of Things at Proximus - Belgium's...MongoDB
 
MongoDB Performance Tuning
MongoDB Performance TuningMongoDB Performance Tuning
MongoDB Performance TuningPuneet Behl
 
Super Advanced Python –act1
Super Advanced Python –act1Super Advanced Python –act1
Super Advanced Python –act1Ke Wei Louis
 
From mysql to MongoDB(MongoDB2011北京交流会)
From mysql to MongoDB(MongoDB2011北京交流会)From mysql to MongoDB(MongoDB2011北京交流会)
From mysql to MongoDB(MongoDB2011北京交流会)Night Sailer
 
Mongo db modifiers
Mongo db modifiersMongo db modifiers
Mongo db modifierszarigatongy
 
Webinar: Replication and Replica Sets
Webinar: Replication and Replica SetsWebinar: Replication and Replica Sets
Webinar: Replication and Replica SetsMongoDB
 
Paris js extensions
Paris js extensionsParis js extensions
Paris js extensionserwanl
 
Embedding a language into string interpolator
Embedding a language into string interpolatorEmbedding a language into string interpolator
Embedding a language into string interpolatorMichael Limansky
 
Tipo virus espia con esto aprenderan a espiar a personas etc jeropas de mrd :v
Tipo virus espia con esto aprenderan a espiar a personas etc jeropas de mrd :v Tipo virus espia con esto aprenderan a espiar a personas etc jeropas de mrd :v
Tipo virus espia con esto aprenderan a espiar a personas etc jeropas de mrd :v Arian Gutierrez
 
Andreas Roth - GraphQL erfolgreich im Backend einsetzen
Andreas Roth - GraphQL erfolgreich im Backend einsetzenAndreas Roth - GraphQL erfolgreich im Backend einsetzen
Andreas Roth - GraphQL erfolgreich im Backend einsetzenDevDay Dresden
 
CouchDB on Android
CouchDB on AndroidCouchDB on Android
CouchDB on AndroidSven Haiges
 
MongoDB Aggregation Framework in action !
MongoDB Aggregation Framework in action !MongoDB Aggregation Framework in action !
MongoDB Aggregation Framework in action !Sébastien Prunier
 
Rapid and Scalable Development with MongoDB, PyMongo, and Ming
Rapid and Scalable Development with MongoDB, PyMongo, and MingRapid and Scalable Development with MongoDB, PyMongo, and Ming
Rapid and Scalable Development with MongoDB, PyMongo, and MingRick Copeland
 

Mais procurados (20)

MySQL flexible schema and JSON for Internet of Things
MySQL flexible schema and JSON for Internet of ThingsMySQL flexible schema and JSON for Internet of Things
MySQL flexible schema and JSON for Internet of Things
 
San Francisco Java User Group
San Francisco Java User GroupSan Francisco Java User Group
San Francisco Java User Group
 
Litebox
LiteboxLitebox
Litebox
 
MongoDB Europe 2016 - Enabling the Internet of Things at Proximus - Belgium's...
MongoDB Europe 2016 - Enabling the Internet of Things at Proximus - Belgium's...MongoDB Europe 2016 - Enabling the Internet of Things at Proximus - Belgium's...
MongoDB Europe 2016 - Enabling the Internet of Things at Proximus - Belgium's...
 
Mongo db presentation
Mongo db presentationMongo db presentation
Mongo db presentation
 
MongoDB Performance Tuning
MongoDB Performance TuningMongoDB Performance Tuning
MongoDB Performance Tuning
 
Super Advanced Python –act1
Super Advanced Python –act1Super Advanced Python –act1
Super Advanced Python –act1
 
From mysql to MongoDB(MongoDB2011北京交流会)
From mysql to MongoDB(MongoDB2011北京交流会)From mysql to MongoDB(MongoDB2011北京交流会)
From mysql to MongoDB(MongoDB2011北京交流会)
 
Mongo db modifiers
Mongo db modifiersMongo db modifiers
Mongo db modifiers
 
Webinar: Replication and Replica Sets
Webinar: Replication and Replica SetsWebinar: Replication and Replica Sets
Webinar: Replication and Replica Sets
 
Elm: give it a try
Elm: give it a tryElm: give it a try
Elm: give it a try
 
Paris js extensions
Paris js extensionsParis js extensions
Paris js extensions
 
Mongo db dla administratora
Mongo db dla administratoraMongo db dla administratora
Mongo db dla administratora
 
Embedding a language into string interpolator
Embedding a language into string interpolatorEmbedding a language into string interpolator
Embedding a language into string interpolator
 
Mongodb workshop
Mongodb workshopMongodb workshop
Mongodb workshop
 
Tipo virus espia con esto aprenderan a espiar a personas etc jeropas de mrd :v
Tipo virus espia con esto aprenderan a espiar a personas etc jeropas de mrd :v Tipo virus espia con esto aprenderan a espiar a personas etc jeropas de mrd :v
Tipo virus espia con esto aprenderan a espiar a personas etc jeropas de mrd :v
 
Andreas Roth - GraphQL erfolgreich im Backend einsetzen
Andreas Roth - GraphQL erfolgreich im Backend einsetzenAndreas Roth - GraphQL erfolgreich im Backend einsetzen
Andreas Roth - GraphQL erfolgreich im Backend einsetzen
 
CouchDB on Android
CouchDB on AndroidCouchDB on Android
CouchDB on Android
 
MongoDB Aggregation Framework in action !
MongoDB Aggregation Framework in action !MongoDB Aggregation Framework in action !
MongoDB Aggregation Framework in action !
 
Rapid and Scalable Development with MongoDB, PyMongo, and Ming
Rapid and Scalable Development with MongoDB, PyMongo, and MingRapid and Scalable Development with MongoDB, PyMongo, and Ming
Rapid and Scalable Development with MongoDB, PyMongo, and Ming
 

Destaque

Mongo dbのgridfsについて
Mongo dbのgridfsについてMongo dbのgridfsについて
Mongo dbのgridfsについてMasahiro Saito
 
MongoDBざっくり解説
MongoDBざっくり解説MongoDBざっくり解説
MongoDBざっくり解説知教 本間
 
はじめてのMongoDB
はじめてのMongoDBはじめてのMongoDB
はじめてのMongoDBTakahiro Inoue
 
Mongo DBを半年運用してみた
Mongo DBを半年運用してみたMongo DBを半年運用してみた
Mongo DBを半年運用してみたMasakazu Matsushita
 
MongoDB全機能解説1
MongoDB全機能解説1MongoDB全機能解説1
MongoDB全機能解説1Takahiro Inoue
 
イマドキのフロントエンドエンジニアの道具箱
イマドキのフロントエンドエンジニアの道具箱イマドキのフロントエンドエンジニアの道具箱
イマドキのフロントエンドエンジニアの道具箱Fumio SAGAWA
 
MongoDBと位置情報 ~地理空間インデックスの紹介
MongoDBと位置情報 ~地理空間インデックスの紹介MongoDBと位置情報 ~地理空間インデックスの紹介
MongoDBと位置情報 ~地理空間インデックスの紹介Koji Iwazaki
 

Destaque (7)

Mongo dbのgridfsについて
Mongo dbのgridfsについてMongo dbのgridfsについて
Mongo dbのgridfsについて
 
MongoDBざっくり解説
MongoDBざっくり解説MongoDBざっくり解説
MongoDBざっくり解説
 
はじめてのMongoDB
はじめてのMongoDBはじめてのMongoDB
はじめてのMongoDB
 
Mongo DBを半年運用してみた
Mongo DBを半年運用してみたMongo DBを半年運用してみた
Mongo DBを半年運用してみた
 
MongoDB全機能解説1
MongoDB全機能解説1MongoDB全機能解説1
MongoDB全機能解説1
 
イマドキのフロントエンドエンジニアの道具箱
イマドキのフロントエンドエンジニアの道具箱イマドキのフロントエンドエンジニアの道具箱
イマドキのフロントエンドエンジニアの道具箱
 
MongoDBと位置情報 ~地理空間インデックスの紹介
MongoDBと位置情報 ~地理空間インデックスの紹介MongoDBと位置情報 ~地理空間インデックスの紹介
MongoDBと位置情報 ~地理空間インデックスの紹介
 

Semelhante a MongoDB GridFS Stores and Retrieves Files

Map/Confused? A practical approach to Map/Reduce with MongoDB
Map/Confused? A practical approach to Map/Reduce with MongoDBMap/Confused? A practical approach to Map/Reduce with MongoDB
Map/Confused? A practical approach to Map/Reduce with MongoDBUwe Printz
 
Designing Opeation Oriented Web Applications / YAPC::Asia Tokyo 2011
Designing Opeation Oriented Web Applications / YAPC::Asia Tokyo 2011Designing Opeation Oriented Web Applications / YAPC::Asia Tokyo 2011
Designing Opeation Oriented Web Applications / YAPC::Asia Tokyo 2011Masahiro Nagano
 
MongoDB .local Houston 2019: Using Client Side Encryption in MongoDB 4.2
MongoDB .local Houston 2019: Using Client Side Encryption in MongoDB 4.2MongoDB .local Houston 2019: Using Client Side Encryption in MongoDB 4.2
MongoDB .local Houston 2019: Using Client Side Encryption in MongoDB 4.2MongoDB
 
Schema Design with MongoDB
Schema Design with MongoDBSchema Design with MongoDB
Schema Design with MongoDBrogerbodamer
 
MongoDB Performance Tuning
MongoDB Performance TuningMongoDB Performance Tuning
MongoDB Performance TuningMongoDB
 
Elasticsearch in 15 Minutes
Elasticsearch in 15 MinutesElasticsearch in 15 Minutes
Elasticsearch in 15 MinutesKarel Minarik
 
MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...
MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...
MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...MongoDB
 
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB
 
Webinar: General Technical Overview of MongoDB for Dev Teams
Webinar: General Technical Overview of MongoDB for Dev TeamsWebinar: General Technical Overview of MongoDB for Dev Teams
Webinar: General Technical Overview of MongoDB for Dev TeamsMongoDB
 
Apache CouchDB Presentation @ Sept. 2104 GTALUG Meeting
Apache CouchDB Presentation @ Sept. 2104 GTALUG MeetingApache CouchDB Presentation @ Sept. 2104 GTALUG Meeting
Apache CouchDB Presentation @ Sept. 2104 GTALUG MeetingMyles Braithwaite
 
MongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 Link
MongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 LinkMongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 Link
MongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 LinkMongoDB
 
NoSQL & MongoDB
NoSQL & MongoDBNoSQL & MongoDB
NoSQL & MongoDBShuai Liu
 
Peggy elasticsearch應用
Peggy elasticsearch應用Peggy elasticsearch應用
Peggy elasticsearch應用LearningTech
 
Geospatial Indexing and Querying with MongoDB
Geospatial Indexing and Querying with MongoDBGeospatial Indexing and Querying with MongoDB
Geospatial Indexing and Querying with MongoDBGrant Goodale
 
10 Key MongoDB Performance Indicators
10 Key MongoDB Performance Indicators  10 Key MongoDB Performance Indicators
10 Key MongoDB Performance Indicators iammutex
 

Semelhante a MongoDB GridFS Stores and Retrieves Files (20)

Map/Confused? A practical approach to Map/Reduce with MongoDB
Map/Confused? A practical approach to Map/Reduce with MongoDBMap/Confused? A practical approach to Map/Reduce with MongoDB
Map/Confused? A practical approach to Map/Reduce with MongoDB
 
MongoDB With Style
MongoDB With StyleMongoDB With Style
MongoDB With Style
 
Couchdb
CouchdbCouchdb
Couchdb
 
Designing Opeation Oriented Web Applications / YAPC::Asia Tokyo 2011
Designing Opeation Oriented Web Applications / YAPC::Asia Tokyo 2011Designing Opeation Oriented Web Applications / YAPC::Asia Tokyo 2011
Designing Opeation Oriented Web Applications / YAPC::Asia Tokyo 2011
 
MongoDB .local Houston 2019: Using Client Side Encryption in MongoDB 4.2
MongoDB .local Houston 2019: Using Client Side Encryption in MongoDB 4.2MongoDB .local Houston 2019: Using Client Side Encryption in MongoDB 4.2
MongoDB .local Houston 2019: Using Client Side Encryption in MongoDB 4.2
 
Books
BooksBooks
Books
 
Schema Design with MongoDB
Schema Design with MongoDBSchema Design with MongoDB
Schema Design with MongoDB
 
MongoDB Performance Tuning
MongoDB Performance TuningMongoDB Performance Tuning
MongoDB Performance Tuning
 
Elasticsearch in 15 Minutes
Elasticsearch in 15 MinutesElasticsearch in 15 Minutes
Elasticsearch in 15 Minutes
 
MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...
MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...
MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...
 
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
 
Latinoware
LatinowareLatinoware
Latinoware
 
Webinar: General Technical Overview of MongoDB for Dev Teams
Webinar: General Technical Overview of MongoDB for Dev TeamsWebinar: General Technical Overview of MongoDB for Dev Teams
Webinar: General Technical Overview of MongoDB for Dev Teams
 
Apache CouchDB Presentation @ Sept. 2104 GTALUG Meeting
Apache CouchDB Presentation @ Sept. 2104 GTALUG MeetingApache CouchDB Presentation @ Sept. 2104 GTALUG Meeting
Apache CouchDB Presentation @ Sept. 2104 GTALUG Meeting
 
MongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 Link
MongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 LinkMongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 Link
MongoDB World 2019: Using Client Side Encryption in MongoDB 4.2 Link
 
NoSQL & MongoDB
NoSQL & MongoDBNoSQL & MongoDB
NoSQL & MongoDB
 
Peggy elasticsearch應用
Peggy elasticsearch應用Peggy elasticsearch應用
Peggy elasticsearch應用
 
Geospatial Indexing and Querying with MongoDB
Geospatial Indexing and Querying with MongoDBGeospatial Indexing and Querying with MongoDB
Geospatial Indexing and Querying with MongoDB
 
Sensmon couchdb
Sensmon couchdbSensmon couchdb
Sensmon couchdb
 
10 Key MongoDB Performance Indicators
10 Key MongoDB Performance Indicators  10 Key MongoDB Performance Indicators
10 Key MongoDB Performance Indicators
 

Mais de Takahiro Inoue

Treasure Data × Wave Analytics EC Demo
Treasure Data × Wave Analytics EC DemoTreasure Data × Wave Analytics EC Demo
Treasure Data × Wave Analytics EC DemoTakahiro Inoue
 
トレジャーデータとtableau実現する自動レポーティング
トレジャーデータとtableau実現する自動レポーティングトレジャーデータとtableau実現する自動レポーティング
トレジャーデータとtableau実現する自動レポーティングTakahiro Inoue
 
Tableauが魅せる Data Visualization の世界
Tableauが魅せる Data Visualization の世界Tableauが魅せる Data Visualization の世界
Tableauが魅せる Data Visualization の世界Takahiro Inoue
 
トレジャーデータのバッチクエリとアドホッククエリを理解する
トレジャーデータのバッチクエリとアドホッククエリを理解するトレジャーデータのバッチクエリとアドホッククエリを理解する
トレジャーデータのバッチクエリとアドホッククエリを理解するTakahiro Inoue
 
20140708 オンラインゲームソリューション
20140708 オンラインゲームソリューション20140708 オンラインゲームソリューション
20140708 オンラインゲームソリューションTakahiro Inoue
 
トレジャーデータ流,データ分析の始め方
トレジャーデータ流,データ分析の始め方トレジャーデータ流,データ分析の始め方
トレジャーデータ流,データ分析の始め方Takahiro Inoue
 
オンラインゲームソリューション@トレジャーデータ
オンラインゲームソリューション@トレジャーデータオンラインゲームソリューション@トレジャーデータ
オンラインゲームソリューション@トレジャーデータTakahiro Inoue
 
事例で学ぶトレジャーデータ 20140612
事例で学ぶトレジャーデータ 20140612事例で学ぶトレジャーデータ 20140612
事例で学ぶトレジャーデータ 20140612Takahiro Inoue
 
トレジャーデータ株式会社について(for all Data_Enthusiast!!)
トレジャーデータ株式会社について(for all Data_Enthusiast!!)トレジャーデータ株式会社について(for all Data_Enthusiast!!)
トレジャーデータ株式会社について(for all Data_Enthusiast!!)Takahiro Inoue
 
この Visualization がすごい2014 〜データ世界を彩るツール6選〜
この Visualization がすごい2014 〜データ世界を彩るツール6選〜この Visualization がすごい2014 〜データ世界を彩るツール6選〜
この Visualization がすごい2014 〜データ世界を彩るツール6選〜Takahiro Inoue
 
Treasure Data Intro for Data Enthusiast!!
Treasure Data Intro for Data Enthusiast!!Treasure Data Intro for Data Enthusiast!!
Treasure Data Intro for Data Enthusiast!!Takahiro Inoue
 
Hadoop and the Data Scientist
Hadoop and the Data ScientistHadoop and the Data Scientist
Hadoop and the Data ScientistTakahiro Inoue
 
MongoDB: Intro & Application for Big Data
MongoDB: Intro & Application  for Big DataMongoDB: Intro & Application  for Big Data
MongoDB: Intro & Application for Big DataTakahiro Inoue
 
An Introduction to Fluent & MongoDB Plugins
An Introduction to Fluent & MongoDB PluginsAn Introduction to Fluent & MongoDB Plugins
An Introduction to Fluent & MongoDB PluginsTakahiro Inoue
 
An Introduction to Tinkerpop
An Introduction to TinkerpopAn Introduction to Tinkerpop
An Introduction to TinkerpopTakahiro Inoue
 
An Introduction to Neo4j
An Introduction to Neo4jAn Introduction to Neo4j
An Introduction to Neo4jTakahiro Inoue
 
The Definition of GraphDB
The Definition of GraphDBThe Definition of GraphDB
The Definition of GraphDBTakahiro Inoue
 
Large-Scale Graph Processing〜Introduction〜(完全版)
Large-Scale Graph Processing〜Introduction〜(完全版)Large-Scale Graph Processing〜Introduction〜(完全版)
Large-Scale Graph Processing〜Introduction〜(完全版)Takahiro Inoue
 
Large-Scale Graph Processing〜Introduction〜(LT版)
Large-Scale Graph Processing〜Introduction〜(LT版)Large-Scale Graph Processing〜Introduction〜(LT版)
Large-Scale Graph Processing〜Introduction〜(LT版)Takahiro Inoue
 

Mais de Takahiro Inoue (20)

Treasure Data × Wave Analytics EC Demo
Treasure Data × Wave Analytics EC DemoTreasure Data × Wave Analytics EC Demo
Treasure Data × Wave Analytics EC Demo
 
トレジャーデータとtableau実現する自動レポーティング
トレジャーデータとtableau実現する自動レポーティングトレジャーデータとtableau実現する自動レポーティング
トレジャーデータとtableau実現する自動レポーティング
 
Tableauが魅せる Data Visualization の世界
Tableauが魅せる Data Visualization の世界Tableauが魅せる Data Visualization の世界
Tableauが魅せる Data Visualization の世界
 
トレジャーデータのバッチクエリとアドホッククエリを理解する
トレジャーデータのバッチクエリとアドホッククエリを理解するトレジャーデータのバッチクエリとアドホッククエリを理解する
トレジャーデータのバッチクエリとアドホッククエリを理解する
 
20140708 オンラインゲームソリューション
20140708 オンラインゲームソリューション20140708 オンラインゲームソリューション
20140708 オンラインゲームソリューション
 
トレジャーデータ流,データ分析の始め方
トレジャーデータ流,データ分析の始め方トレジャーデータ流,データ分析の始め方
トレジャーデータ流,データ分析の始め方
 
オンラインゲームソリューション@トレジャーデータ
オンラインゲームソリューション@トレジャーデータオンラインゲームソリューション@トレジャーデータ
オンラインゲームソリューション@トレジャーデータ
 
事例で学ぶトレジャーデータ 20140612
事例で学ぶトレジャーデータ 20140612事例で学ぶトレジャーデータ 20140612
事例で学ぶトレジャーデータ 20140612
 
トレジャーデータ株式会社について(for all Data_Enthusiast!!)
トレジャーデータ株式会社について(for all Data_Enthusiast!!)トレジャーデータ株式会社について(for all Data_Enthusiast!!)
トレジャーデータ株式会社について(for all Data_Enthusiast!!)
 
この Visualization がすごい2014 〜データ世界を彩るツール6選〜
この Visualization がすごい2014 〜データ世界を彩るツール6選〜この Visualization がすごい2014 〜データ世界を彩るツール6選〜
この Visualization がすごい2014 〜データ世界を彩るツール6選〜
 
Treasure Data Intro for Data Enthusiast!!
Treasure Data Intro for Data Enthusiast!!Treasure Data Intro for Data Enthusiast!!
Treasure Data Intro for Data Enthusiast!!
 
Hadoop and the Data Scientist
Hadoop and the Data ScientistHadoop and the Data Scientist
Hadoop and the Data Scientist
 
MongoDB: Intro & Application for Big Data
MongoDB: Intro & Application  for Big DataMongoDB: Intro & Application  for Big Data
MongoDB: Intro & Application for Big Data
 
An Introduction to Fluent & MongoDB Plugins
An Introduction to Fluent & MongoDB PluginsAn Introduction to Fluent & MongoDB Plugins
An Introduction to Fluent & MongoDB Plugins
 
An Introduction to Tinkerpop
An Introduction to TinkerpopAn Introduction to Tinkerpop
An Introduction to Tinkerpop
 
An Introduction to Neo4j
An Introduction to Neo4jAn Introduction to Neo4j
An Introduction to Neo4j
 
The Definition of GraphDB
The Definition of GraphDBThe Definition of GraphDB
The Definition of GraphDB
 
Large-Scale Graph Processing〜Introduction〜(完全版)
Large-Scale Graph Processing〜Introduction〜(完全版)Large-Scale Graph Processing〜Introduction〜(完全版)
Large-Scale Graph Processing〜Introduction〜(完全版)
 
Large-Scale Graph Processing〜Introduction〜(LT版)
Large-Scale Graph Processing〜Introduction〜(LT版)Large-Scale Graph Processing〜Introduction〜(LT版)
Large-Scale Graph Processing〜Introduction〜(LT版)
 
Advanced MongoDB #1
Advanced MongoDB #1Advanced MongoDB #1
Advanced MongoDB #1
 

Último

The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...gurkirankumar98700
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsRoshan Dwivedi
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 

Último (20)

The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
Kalyanpur ) Call Girls in Lucknow Finest Escorts Service 🍸 8923113531 🎰 Avail...
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 

MongoDB GridFS Stores and Retrieves Files

  • 1.
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11. { "_id" : <unspecified>, //file ID "length" : data_number, // bytes "chunkSize" : data_number, // :256KB "uploadDate" : data_date, //file "md5" : data_string //"filemd5" }
  • 12. { "filename" : data_string, "contentType" : data_string, "aliases" : data_array of data_string, "metadata" : data_object, }
  • 13. { "_id" : <unspecified>, //chunk ID "files_id" : <unspecified>, //file _id "n" : chunk_number, //0 chunk 0,1,2... chunk "data" : data_binary, // BSON }
  • 14. > db.fs.chunks.ensureIndex( {files_id:1, n:1}, {unique: true}); > db.fs.chunks.findOne({files_id: myFileID, n: 0});
  • 15. ➜ ~ mongofiles --help usage: mongofiles [options] command [gridfs filename] command: one of (list|search|put|get) list - file search - file put - file get - file delete - file
  • 16. ➜ ~ mongofiles list connected to: 127.0.0.1 ➜ ~ mongofiles put ByeForNow.mp3 connected to: 127.0.0.1 added file: { _id: ObjectId('4df17f8d9d47ba5c0247e72e'), filename: "ByeForNow.mp3", chunkSize: 262144, uploadDate: new Date(1307672462538), md5: "9ee9472200a2e18bf376ce622c3b0055", length: 11183104 } done! ➜ ~ mongofiles list -v // -v Fri Jun 10 11:21:05 creating new connection to:127.0.0.1 Fri Jun 10 11:21:05 BackgroundJob starting: connected to: 127.0.0.1 ByeForNow.mp3 11183104
  • 17. ➜ ~ mongofiles put Maria.mp3 connected to: 127.0.0.1 added file: { _id: ObjectId('4df181fc5e354129e833193f'), filename: "Maria.mp3", chunkSize: 262144, uploadDate: new Date(1307673086293), md5: "9d4f424fa1843711e196e502d8a00183", length: 12225353 } done! ➜ ~ mongofiles list connected to: 127.0.0.1 ByeForNow.mp3 11183104 Maria.mp3 12225353 ➜ ~ mongofiles list M connected to: 127.0.0.1 Maria.mp3 12225353 ➜ ~ mongofiles search .mp3 connected to: 127.0.0.1 ByeForNow.mp3 11183104 Maria.mp3 12225353
  • 18. ~ mkdir tmp // get ➜ ~ cd tmp ➜ mongofiles get Maria.mp3 connected to: 127.0.0.1 done write to: Maria.mp3 ➜ ls Maria.mp3 ➜ mongofiles get Bye ERROR: file not found ➜ mongofiles get ByeForNow.mp3 done write to: ByeForNow.mp3 ➜ md5 Maria.mp3 MD5 (Maria.mp3) = 9d4f424fa1843711e196e502d8a00183 ➜ md5 ../Maria.mp3 MD5 (../Maria.mp3) = 9d4f424fa1843711e196e502d8a00183
  • 19. > db.fs.files.find().forEach(printjson) { "_id" : ObjectId("4df17f8d9d47ba5c0247e72e"), "filename" : "ByeForNow.mp3", "chunkSize" : 262144, "uploadDate" : ISODate("2011-06-10T02:21:02.538Z"), "md5" : "9ee9472200a2e18bf376ce622c3b0055", "length" : 11183104 } { "_id" : ObjectId("4df181fc5e354129e833193f"), "filename" : "Maria.mp3", "chunkSize" : 262144, "uploadDate" : ISODate("2011-06-10T02:31:26.293Z"), "md5" : "9d4f424fa1843711e196e502d8a00183", "length" : 12225353 }
  • 20. > db.fs.chunks.findOne( {n:0,files_id:ObjectId("4df181fc5e354129e833193f")}) { "_id" : ObjectId("4df181fcd40994ca1de28d09"), "files_id" : ObjectId("4df181fc5e354129e833193f"), "n" : 0, "data" : BinData(0,"SUQzAwAAAABQdlRSQ0sAAAACAAAAM1RJVDIA AAAHAAAAg32DioNBVUZJRAAAAGYAAGh0dHA6Ly93d3cuY2RkYi5jb20vaWQ zL3RhZ2luZm8xLmh0bWwAM0NEM00xMTBRMjA3NTYwOTc4VjY4MTBCQTlBNj UzN0JCQUQ1QTgyOUE4NTRCRkQ2QTdBRjNQOAAAAAAAAAAAAEdFT0IAACNgA AAAYXBwbGljYX...) }
  • 21. > db.fs.chunks.ensureIndex({files_id: 1}); > db.runCommand({ shardcollection : "test.fs.chunks", key : { files_id : 1 }}) { "collectionsharded" : "test.fs.chunks", "ok" : 1 }
  • 22. MongoDB GridFS
  • 23. Replace Amazon S3 with MongoDB GridFS and Grails
  • 24.
  • 25.
  • 26. { loc : [ 50 , 30 ] } { loc : { x : 50 , y : 30 } } { loc : { foo : 50 , y : 30 } } { loc : { long : 40.739037, lat: 73.992964 } }
  • 27. db.places.ensureIndex( { loc : "2d" } ) db.places.ensureIndex( { loc : "2d" } , { min : -500 , max : 500 } )
  • 28. db.places.find( { loc : [50,50] } ) db.places.find( { loc : { $near : [50,50] } } ) db.places.find( { loc : { $near : [50,50] } } ).limit(20) db.places.find( { loc : { $near : [50,50] , $maxDistance : 5 } } ).limit(20)
  • 29. // > box = [[40.73083, -73.99756], [40.741404, -73.988135]] > db.places.find({"loc" : {"$within" : {"$box" : box}}}) // > center = [50, 50] > radius = 10 > db.places.find({"loc" : {"$within" : {"$center" : [center, radius]}}}) // v1.9 > polygonA = [ [ 10, 20 ], [ 10, 40 ], [ 30, 40 ], [ 30, 20 ] ] > polygonB = { a : { x : 10, y : 20 }, b : { x : 15, y : 25 }, c : { x : 20, y : 20 } } > db.places.find({ "loc" : { "$within" : { "$polygon" : polygonA } } }) > db.places.find({ "loc" : { "$within" : { "$polygon" : polygonB } } })
  • 30. > db.runCommand( { geoNear : "places" , near : [ 50 , 50 ], num : 10, query : { type : "museum" } } ); { "ns" : "test.places", "near" : "1100110000001111110000001111110000001111110000001111", "results" : [ { "dis" : 69.29646421910687, "obj" : { "_id" : ObjectId("4b8bd6b93b83c574d8760280"), "y" : [ 1, 1 ], "category" : "Coffee" } }, { "dis" : 69.29646421910687, "obj" : { "_id" : ObjectId("4b8bd6b03b83c574d876027f"), 1 ...}
  • 32.
  • 33. > db.points.insert({ pos : { long : 30, lat : 30 } }) > db.points.insert({ pos : { long : -10, lat : -20 } }) > db.points.ensureIndex({ pos : "2d" }) > db.points.find({ pos: { $nearSphere: [0,0], $maxDistance : 0.4 } }) { "_id" : ObjectId("4df11e47b8e84370f84afdd3"), "pos" : { "long" : -10, "lat" : -20 } }
  • 34. > var earthRadius = 6378 // km > var range = 3000 // km > distances = db.runCommand({ geoNear : "points", near : [0, 0], spherical : true, maxDistance : range / earthRadius }).results [ { "dis" : 0.3886630122897946, // "obj" : { "_id" : ObjectId("4df11e47b8e84370f84afdd3"), "pos" : { "long" : -10, "lat" : -20 } } } ] > pointDistance = distances[0].dis * earthRadius 2478.89269238431 // km
  • 35.
  • 36.
  • 37.
  • 38.
  • 39.
  • 40.
  • 41.
  • 42.
  • 44.
  • 45.
  • 46. ~ mkdir -p shard/shard00 ~ mkdir -p shard/shard01 ~ mkdir -p shard/shard02 ~ mkdir -p shard/config ~ mongod --shardsvr --port 27017 --dbpath shard/shard00 ~ mongod --shardsvr --port 27018 --dbpath shard/shard01 ~ mongod --shardsvr --port 27019 --dbpath shard/shard02 ~ mongod --configsvr --port 27020 --dbpath shard/config ~ mongos --configdb localhost:27020 --port 27021
  • 47. ~ mongo localhost:27021 // mongos MongoDB shell version: 1.8.0 connecting to: localhost:27021/test > show dbs config 0.1875GB // sharding > db.adminCommand( { addshard: "localhost:27017", name: "shard00" } ) { "shardAdded" : "shard00", "ok" : 1 } > db.adminCommand( { addshard: "localhost:27018", name: "shard01" } ) { "shardAdded" : "shard01", "ok" : 1 } > db.adminCommand( { addshard: "localhost:27019", name: "shard02" } ) { "shardAdded" : "shard02", "ok" : 1 }
  • 48. // mongos > db.adminCommand( { enablesharding : "test" } ) { "ok" : 1 } > db.adminCommand( { moveprimary : "test", to : "shard02" } ); { "primary " : "shard02:localhost:27019", "ok" : 1 } > db.adminCommand( { shardcollection : "test.myshard", key : { n : 1 } } ) { "collectionsharded" : "test.myshard", "ok" : 1 }
  • 49. // mongos > db.adminCommand({split : "test.myshard", middle : { n: 0 } } ) { "ok" : 1 } > db.adminCommand({split : "test.myshard", middle : { n: 1 } } ) { "ok" : 1 } > db.adminCommand({split : "test.myshard", middle : { n: 2 } } ) { "ok" : 1 }
  • 50. > db.printShardingStatus() // --- Sharding Status --- sharding version: { "_id" : 1, "version" : 3 } shards: { "_id" : "shard00", "host" : "localhost:27017" } { "_id" : "shard01", "host" : "localhost:27018" } { "_id" : "shard02", "host" : "localhost:27019" } databases: { "_id" : "admin", "partitioned" : false, "primary" : "config" } { "_id" : "test", "partitioned" : true, "primary" : "shard02" } test.myshard chunks: shard02 4 { "n" : { $minKey : 1 } } -->> { "n" : 0 } on : shard02 { "t" : 1000, "i" : 1 } { "n" : 0 } -->> { "n" : 1 } on : shard02 { "t" : 1000, "i" : 3 } { "n" : 1 } -->> { "n" : 2 } on : shard02 { "t" : 1000, "i" : 5 } { "n" : 2 } -->> { "n" : { $maxKey : 1 } } on : shard02 { "t" : 1000, "i" : 6 }
  • 51. // mongos > db.adminCommand({moveChunk: "test.myshard", find: { n: 0 }, to: "shard00" }); { "millis" : 1051, "ok" : 1 } > db.adminCommand({moveChunk: "test.myshard", find: { n: 1 }, to: "shard01" }); { "millis" : 1046, "ok" : 1 } > db.adminCommand({moveChunk :"test.myshard", find: { n: 2 }, to: "shard02" }); { "ok" : 0, "errmsg" : "that chunk is already on that shard" }
  • 52. > db.printShardingStatus() --- Sharding Status --- sharding version: { "_id" : 1, "version" : 3 } shards: { "_id" : "shard00", "host" : "localhost:27017" } { "_id" : "shard01", "host" : "localhost:27018" } { "_id" : "shard02", "host" : "localhost:27019" } databases: { "_id" : "admin", "partitioned" : false, "primary" : "config" } { "_id" : "test", "partitioned" : true, "primary" : "shard02" } test.myshard chunks: shard02 2 shard00 1 shard01 1 { "n" : { $minKey : 1 } } -->> { "n" : 0 } on : shard02 { "t" : 3000, "i" : 1 } { "n" : 0 } -->> { "n" : 1 } on : shard00 { "t" : 2000, "i" : 0 } { "n" : 1 } -->> { "n" : 2 } on : shard01 { "t" : 3000, "i" : 0 } { "n" : 2 } -->> { "n" : { $maxKey : 1 } } on : shard02 { "t" : 1000, "i" : 6 }
  • 53. // mongos > for(var m=0; m<100; m++){ db.myshard.insert({n: m % 3}) } // n =0,1,2,0,1,... > printShardingSizes() // Shard ... test.myshard chunks: { "n" : { $minKey : 1 } } -->> { "n" : 0 } on : shard02 { "estimate" : false, "size" : 0, "numObjects" : 0 } { "n" : 0 } -->> { "n" : 1 } on : shard00 { "estimate" : false, "size" : 1224, "numObjects" : 34 } { "n" : 1 } -->> { "n" : 2 } on : shard01 { "estimate" : false, "size" : 1188, "numObjects" : 33 } { "n" : 2 } -->> { "n" : { $maxKey : 1 } } on : shard02 { "estimate" : false, "size" : 1188, "numObjects" : 33 }
  • 54. ~ mongo localhost:27017 > db.myshard.count() 34 > db.myshard.distinct("n") [ 0 ] ➜ ~ mongo localhost:27018 > db.myshard.count() 33 > db.myshard.distinct("n") [ 1 ] ➜ ~ mongo localhost:27019 > db.myshard.count() 33 > db.myshard.distinct("n") [ 2 ]
  • 55.
  • 56.
  • 57. > db.adminCommand( { addshard: "set00/delta1:27017,delta2:27017", name: "shard00" } ) { "shardAdded" : "shard00", "ok" : 1 } > db.adminCommand( { addshard: "set01/delta3:27018,delta4:27018", name: "shard01" } ) { "shardAdded" : "shard01", "ok" : 1 } > db.adminCommand( { addshard: "set02/delta5:27019,delta6:27019", name: "shard02" } ) { "shardAdded" : "shard02", "ok" : 1 }
  • 58.
  • 59.
  • 60.
  • 61.
  • 62.
  • 63.
  • 65.
  • 66.
  • 67. db.mycoll.mapReduce( map : <map >, reduce : <reduce > [, finalize : <finalize >] [, query : < >] [, sort : < reduce >] [, out : < >] [, scope : <object where fields go into javascript global scope >] );
  • 68. db.people.insert({userId:1, age:24, type:"A"}) db.people.insert({userId:2, age:47, type:"B"}) db.people.insert({userId:3, age:34, type:"C"}) db.people.insert({userId:4, age:4, type:"B"}) db.people.insert({userId:5, age:14, type:"A"}) db.people.insert({userId:6, age:29, type:"C"}) db.people.insert({userId:7, age:39, type:"C"}) db.people.insert({userId:8, age:42, type:"B"}) db.people.insert({userId:9, age:56, type:"A"}) db.people.insert({userId:10, age:12, type:"A"})
  • 69. m = function() { emit(this.type, { age: this.age, num: 1 } ); }
  • 70. r = function(key, values) { var result = { age: 0, num: 0 }; values.forEach( function(value){ result.age += value.age; // age result.num += value.num; // } ); return result; }
  • 71. r = function(key, values) { var num = 0; var sum = 0; values.forEach( function(value){ sum += value.age; // age num += value.num; // } ); return sum/num; }
  • 72. m = function() { emit(this.type, { age: this.age, num: 1 } ); } r = function(key, values) { var result = { age: 0, num: 0 }; values.forEach( function(value){ result.age += value.age; // age result.num += value.num; // } ); return result; }
  • 73. m = function() { emit(this.type, { age: this.age, num: 1 } ); } r = function(key, values) { var result = { age: 0, num: 0 }; values.forEach( function(value){ result.age += value.age; // result.num += value.num; // } ); return result; }
  • 74. f = function( key, result ){ result.avg = result.age / result.num; return result; }
  • 75. > res = db.people.mapReduce( m , r , { finalize : f , out : "mr_out", verbose: true }); { "result" : "mr_out", // "timeMillis" : 18, // "timing" : { "mapTime" : NumberLong(1), "emitLoop" : 12, "total" : 18 }, "counts" : { "input" : 10, // 10 "emit" : 10, // 10 emit "output" : 3 // 3 }, "ok" : 1, }
  • 76. > db.mr_out.find() { "_id" : "A", "value" : { "age" : 106, "num" : 4, "avg" : 26.5 } } { "_id" : "B", "value" : { "age" : 93, "num" : 3, "avg" : 31 } } { "_id" : "C", "value" : { "age" : 102, "num" : 3, "avg" : 34 } }
  • 77. > res = db.people.mapReduce( m , r , { finalize : f , out : "mr_out", query: { age: { $gte: 20 } } }); { "result" : "mr_out", "timeMillis" : 35, "counts" : { "input" : 7, // 3 "emit" : 7, "output" : 3 }, "ok" : 1, }
  • 78. > db.mr_out.find() // { "_id" : "A", "value" : { "age" : 80, "num" : 2, "avg" : 40 } } { "_id" : "B", "value" : { "age" : 89, "num" : 2, "avg" : 44.5 } } { "_id" : "C", "value" : { "age" : 102, "num" : 3, "avg" : 34 } }
  • 79.
  • 80.
  • 81. db.items.insert({ date: "2011-06-01", item: "apple", price: 100 }) db.items.insert({ date: "2011-06-01", item: "banana", price: 200 }) db.items.insert({ date: "2011-06-01", item: "apple" , price :100}) db.items.insert({ date: "2011-06-02", item: "orange", price: 50 }) db.items.insert({ date: "2011-06-02", item: "orange", price: 50 }) db.items.insert({ date: "2011-06-02", item: "apple", price: 100 })
  • 82. m = function() { emit(this.item, this.price); } r = function(key,values) { var result = 0; values.forEach( function(value){ result += value } ); return result; } > res = db.items.mapReduce( m, r, { query: {date: "2011-06-01"} , out: {replace: "mr_out2"}} ); { "result" : "mr_out2", "timeMillis" : 10, "counts" : { "input" : 3, "emit" : 3, "output" : 2 }, "ok" : 1, } >db.mr_out2.find() { "_id" : "apple", "value" : 200 } { "_id" : "banana", "value" : 200 }
  • 83. > res = db.items.mapReduce( m, r, { query: {date: "2011-06-02"} , out: {reduce: "mr_out2"}} ); { "result" : "mr_out2", "timeMillis" : 23, "counts" : { "input" : 3, "emit" : 3, "output" : 3 }, "ok" : 1, } > db.mr_out2.find() { "_id" : "apple", "value" : 300 } // { "_id" : "banana", "value" : 200 } // { "_id" : "orange", "value" : 100 } //