![What‘s a document?
Single record that can be stored in a collection
JSON = JavaScript Object Notation (internal representation BSON = Binary JSON)
var doc = {
title: „MongoDB_Live_Hacking.pptx“,
tags: [ „cc“, „mongodb“, „nosql“ ],
slides: [
{ nr = 1, header = „MongoDB User Groups by codecentric“},
{ nr = 2, header = „MongoDB at codedcentric WiKi“},
…
]
};
codecentric AG](https://image.slidesharecdn.com/mongodblivecoding-120821014638-phpapp02/85/MongoDB-Live-Hacking-6-320.jpg)
![Geospatial Queries
Queries based on
2-dimensional coordinates
_id: "A", position: [0.001, -0.002]
_id: "B", position: [0.75, 0.75]
_id: "C", position: [0.5, 0.5]
_id: "D", position: [-0.5, -0.5]
Queries based on distances
& shapes
Details:
http://blog.codecentric.de/en/2012/02/spring-data-mongodb-geospatial-queries/
codecentric AG](https://image.slidesharecdn.com/mongodblivecoding-120821014638-phpapp02/85/MongoDB-Live-Hacking-8-320.jpg)
![Map/Reduce example
We want to count occurences of tags assigned to our documents:
{name: „Doc 1“, tags: [ „cc“, „mongodb“, „nosql“ ] }
{name: „Doc 2“, tags: [ „cc“, „agile“ ] } Map output:
{name: „Doc 3“, tags: [ „cc“ ] } key = „cc“, value = {count: 1}
key = „mongodb“, value = {count: 1}
key = „nosql“, value = {count: 1}
Map function:
key = „cc“, value = {count: 1}
function() { this.tags.forEach( function(tag) { key = „agile“, value = {count: 1}
emit( tag, {count: 1} ) key = „cc“, value = {count: 1}
})
}
Reduce function: Reduce input:
function(key, values) { key = „cc“, values = [ {count: 1}, {count: 1}, {count: 1} ]
var result = {count: 0};
key = „mongodb“, values = [ {count: 1} ]
values.forEach(function(value) {
key = „nosql“, values = [ {count: 1} ]
result.count += value.count;
key = „agile“, values = [ {count: 1} ]
});
return result;
}
codecentric AG](https://image.slidesharecdn.com/mongodblivecoding-120821014638-phpapp02/85/MongoDB-Live-Hacking-10-320.jpg)
![What‘s a document?
Single record that can be stored in a collection
JSON = JavaScript Object Notation (internal representation BSON = Binary JSON)
var doc = {
title: „MongoDB_Live_Hacking.pptx“,
tags: [ „cc“, „mongodb“, „nosql“ ],
slides: [
{ nr = 1, header = „MongoDB User Groups by codecentric“},
{ nr = 2, header = „MongoDB at codedcentric WiKi“},
…
]
};
codecentric AG](https://image.slidesharecdn.com/mongodblivecoding-120821014638-phpapp02/75/MongoDB-Live-Hacking-6-2048.jpg)
![Geospatial Queries
Queries based on
2-dimensional coordinates
_id: "A", position: [0.001, -0.002]
_id: "B", position: [0.75, 0.75]
_id: "C", position: [0.5, 0.5]
_id: "D", position: [-0.5, -0.5]
Queries based on distances
& shapes
Details:
http://blog.codecentric.de/en/2012/02/spring-data-mongodb-geospatial-queries/
codecentric AG](https://image.slidesharecdn.com/mongodblivecoding-120821014638-phpapp02/75/MongoDB-Live-Hacking-8-2048.jpg)
![Map/Reduce example
We want to count occurences of tags assigned to our documents:
{name: „Doc 1“, tags: [ „cc“, „mongodb“, „nosql“ ] }
{name: „Doc 2“, tags: [ „cc“, „agile“ ] } Map output:
{name: „Doc 3“, tags: [ „cc“ ] } key = „cc“, value = {count: 1}
key = „mongodb“, value = {count: 1}
key = „nosql“, value = {count: 1}
Map function:
key = „cc“, value = {count: 1}
function() { this.tags.forEach( function(tag) { key = „agile“, value = {count: 1}
emit( tag, {count: 1} ) key = „cc“, value = {count: 1}
})
}
Reduce function: Reduce input:
function(key, values) { key = „cc“, values = [ {count: 1}, {count: 1}, {count: 1} ]
var result = {count: 0};
key = „mongodb“, values = [ {count: 1} ]
values.forEach(function(value) {
key = „nosql“, values = [ {count: 1} ]
result.count += value.count;
key = „agile“, values = [ {count: 1} ]
});
return result;
}
codecentric AG](https://image.slidesharecdn.com/mongodblivecoding-120821014638-phpapp02/75/MongoDB-Live-Hacking-10-2048.jpg)
Uploaded byTobias Trelle
MongoDB Live Hacking
This document summarizes a MongoDB live coding session presented by Tobias Trelle. It introduces MongoDB concepts like documents, collections, CRUD operations, queries including geospatial queries, replication, sharding, and the Java and Spring Data APIs. It also advertises MongoDB user groups in Dusseldorf and Frankfurt organized by codecentric AG.
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MongoDB Live Hacking
- 1. MongoDB Live CodingSession tobias.trelle@codecentric.de @tobiastrelle codecentric AG
- 2. „It‘s not myfault the chapters are short, MongoDB is just easy to learn“ from „The Little MongoDB book“ codecentric AG
- 3. MongoDB User Groupsby codecentric MongoDB User-Gruppe Düsseldorf https://www.xing.com/net/mongodb-dus @MongoDUS Contact: Tobias Trelle MongoDB User-Gruppe Frankfurt/Main https://www.xing.com/net/mongodb-ffm Contact: Uwe Seiler codecentric AG
- 4. What is MongoDB? Named from „humongous“ = gigantic http://www.mongodb.org NoSQL datastore, Open Source https://github.com/mongodb support from manufacturer 10gen http://www.10gen.com Highly scalable (scale-out) Stores so called „documents“ Supports replication & sharding Map/Reduce Geospatial indexes / queries codecentric AG
- 5. Basic structure ofa MongoDB server Server Database Relational counterpart But … Flexible Table Collection Schema Row Document - Arrays Column Field - recursive codecentric AG
- 6. What‘s a document? Single record that can be stored in a collection JSON = JavaScript Object Notation (internal representation BSON = Binary JSON) var doc = { title: „MongoDB_Live_Hacking.pptx“, tags: [ „cc“, „mongodb“, „nosql“ ], slides: [ { nr = 1, header = „MongoDB User Groups by codecentric“}, { nr = 2, header = „MongoDB at codedcentric WiKi“}, … ] }; codecentric AG
- 7. Live Session CRUD operations Queries Geospatial Queries Map/Reduce Replication Sharding Raw Java API & Spring Data API codecentric AG
- 8. Geospatial Queries Queries based on 2-dimensional coordinates _id: "A", position: [0.001, -0.002] _id: "B", position: [0.75, 0.75] _id: "C", position: [0.5, 0.5] _id: "D", position: [-0.5, -0.5] Queries based on distances & shapes Details: http://blog.codecentric.de/en/2012/02/spring-data-mongodb-geospatial-queries/ codecentric AG
- 9. Map/Reduce Data processing algorithm based on two phases: map & reduce Code execution co-located with the data Map phase can be run in parallel (on multiple nodes etc.) on huge data sets MongoDB map / reduce: runs on a subset of / all documents of a collection Map / Reduce algorithms are JS functions Output documents of the map function are input to the reduce function Results are documents stored in a target collection codecentric AG
- 10. Map/Reduce example We want to count occurences of tags assigned to our documents: {name: „Doc 1“, tags: [ „cc“, „mongodb“, „nosql“ ] } {name: „Doc 2“, tags: [ „cc“, „agile“ ] } Map output: {name: „Doc 3“, tags: [ „cc“ ] } key = „cc“, value = {count: 1} key = „mongodb“, value = {count: 1} key = „nosql“, value = {count: 1} Map function: key = „cc“, value = {count: 1} function() { this.tags.forEach( function(tag) { key = „agile“, value = {count: 1} emit( tag, {count: 1} ) key = „cc“, value = {count: 1} }) } Reduce function: Reduce input: function(key, values) { key = „cc“, values = [ {count: 1}, {count: 1}, {count: 1} ] var result = {count: 0}; key = „mongodb“, values = [ {count: 1} ] values.forEach(function(value) { key = „nosql“, values = [ {count: 1} ] result.count += value.count; key = „agile“, values = [ {count: 1} ] }); return result; } codecentric AG
- 11. MongoDB Replication A cluster is called „replica set“ Uses Master/Slave replication Writes from clients go to the master only If the master goes down, the slaves elect a new master (n > 2) Replica set w/ n = 3 Slave 1 Client Master Slave 2 codecentric AG
- 12. MongoDB Sharding Data is distributed over n nodes, each record is persisted only once Data only on the shard nodes Config Server = book keeper, knows where the data is Switch: Gateway for clients Sharding setup Config Server Shard 1 Shard 2 Client Switch codecentric AG
- 13. MongoDB Sharding inProduction Each shard is a replica set + 3 config servers Source: http://www.mongodb.org/display/DOCS/Sharding+Introduction codecentric AG
- 14. MongoDB Sharding Example:Initial State mongos> sh.status() --- Sharding Status --- sharding version: { "_id" : 1, "version" : 3 } shards: 2 Shards { "_id" : "shard0000", "host" : "tmp-pc:9000" } { "_id" : "shard0001", "host" : "tmp-pc:9001" } databases: { "_id" : "admin", "partitioned" : false, "primary" : "config" } { "_id" : "data", "partitioned" : true, "primary" : "shard0000" } data.foo chunks: shard0000 1 { "age" : { $minKey : 1 } } -->> { "age" : { $maxKey : 1 } } on : shard0000 { "t" : 1000, "i" : 0 } codecentric AG
- 15. MongoDB Sharding Example:Multiple Chunks mongos> sh.status() --- Sharding Status --- sharding version: { "_id" : 1, "version" : 3 } shards: 2 Shards { "_id" : "shard0000", "host" : "tmp-pc:9000" } { "_id" : "shard0001", "host" : "tmp-pc:9001" } databases: { "_id" : "admin", "partitioned" : false, "primary" : "config" } { "_id" : "data", "partitioned" : true, "primary" : "shard0000" } data.foo chunks: shard0001 4 shard0000 5 Chunks { "age" : { $minKey : 1 } } -->> { "age" : 50 } on : shard0001 { "t" : 2000, "i" : 0 } are equally distributed { "age" : 50 } -->> { "age" : 53 } on : shard0001 { "t" : 3000, "i" : 0 } { "age" : 53 } -->> { "age" : 54 } on : shard0001 { "t" : 4000, "i" : 0 } { "age" : 54 } -->> { "age" : 58 } on : shard0001 { "t" : 5000, "i" : 0 } { "age" : 58 } -->> { "age" : 60 } on : shard0000 { "t" : 5000, "i" : 1 } { "age" : 60 } -->> { "age" : 63 } on : shard0000 { "t" : 1000, "i" : 14 } { "age" : 63 } -->> { "age" : 65 } on : shard0000 { "t" : 1000, "i" : 11 } { "age" : 65 } -->> { "age" : 69 } on : shard0000 { "t" : 1000, "i" : 12 } { "age" : 69 } -->> { "age" : { $maxKey : 1 } } on : shard0000 { "t" : 1000, "i" : 4 } codecentric AG
- 16. MongoDB API Drivers for many languages (Java, Ruby, PHP, C++, …) Low level Java API: MongoDB Java Driver Spring Data MongoDB: Repository Support + Objekt/Collection Mapping Spring Data CrudRepository PagingAndSortingRepository Spring Data Spring Data Spring Data Spring Data JPA MongoDB Neo4j … JpaRepository MongoRepository GraphRepository MongoTemplate Neo4jTemplate Embedded REST JPA Mongo Java Driver JDBC RDBMS MongoDB Neo4j … codecentric AG
- 17. QUESTION? Tobias Trelle codecentric AG MerscheiderStr. 1 42699 Solingen tel +49 (0) 212.233628.47 fax +49 (0) 212.233628.79 mail Tobias.Trelle@codecentric.de twitter @tobiastrelle www.codecentric.de www.mbg-online.de blog.codecentric.de www.xing.com/net/mongodb-dus codecentric AG 20.08.2012 17