No Sql
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This document provides an introduction to NoSQL databases. It discusses that NoSQL refers to non-relational databases that are not based on SQL and are focused on scalability. Some common types of NoSQL databases include column stores, key-value stores, document stores, graph databases, and XML databases. NoSQL databases are designed to handle large volumes of data across many servers and provide high availability with no single point of failure. Common uses of NoSQL databases include distributed systems like social networks where data is highly distributed and needs to be replicated across servers.
![Data Model
Documents
{ schemaless
“_id”: “abc”,
“title”: “NoSQL”, JSON
“tags”:
[ binary attachments
“data model”,
“scalability”
],
“_rev”: 1234
}](https://image.slidesharecdn.com/nosql-100407111005-phpapp01/85/No-Sql-23-320.jpg)
![example: map-reduce
{
{ "total_rows":2,
id: “abc”, "offset":0,
title: “nosql”, "rows":
type: “talk” [
} function(doc) { {
if (doc.type == "talk") { "id":"abc",
emit(doc.title, doc); "key":"nosql",
} "value": {id: “abc”,
{ title: “nosql”, type: “talk”}
id: “xyz”, }
},
title: “ajax”, {
type: “talk” "id":"xyz",
} "key":"ajax",
map "value": {id: “xyz”,
title: “ajax”, type: “talk”}
}
]
}](https://image.slidesharecdn.com/nosql-100407111005-phpapp01/85/No-Sql-28-320.jpg)
![example: map-reduce
{
"total_rows":2,
"offset":0,
"rows":
[
{
"id":"abc",
"key":"nosql", function (key, values, rereduce) {
"value": {id: “abc”, return sum(values);
title: “nosql”, type: “talk”} }
},
{
"id":"xyz",
"key":"ajax",
re duce
"value": {id: “xyz”,
title: “ajax”, type: “talk”}
}
]
}](https://image.slidesharecdn.com/nosql-100407111005-phpapp01/85/No-Sql-29-320.jpg)
No Sql
- 1. NoSQL An Introduction Internet Briefing Developer Konferenz, 7/4/2010 Michael Marth @michaelmarth | www.marth.ch marth.software.services
- 2. “NoSQL” ??? Product? Technology?
- 3. “NoSQL” ??? Product? Technology? persistence Bunch of proje cts w ih share d interes t
- 4. relational non-relational your requirements Not only SQL
- 5. NoSQL Focus data models scalability
- 6. NoSQL Focus ly? shard al ing Re read- slave vertic s al sc aling data models scalability
- 7. NoSQL Focus what is scaling 1. Horizontal scale: scalability more ser vers crea capacity tes more 2. Trans parent t applicati o the on: the busin ess logic app shou of the ld be se from con parated cerns of server re scaling sources 3. No sin gle point no one s of failur erver wh e: lost, cau ich, if ses down the appl time of ication http://adam.blog.heroku.com/past/2009/7/6/sql_databases_dont_scale/
- 8. reme mber the ambrian E xplosion? C
- 9. according to http://nosql-database.org: Column stores Key Value / Tuple Store Document stores Eventually Consistent Key Value Store Graph Databases XML Databases
- 10. Column stores Key Value / Tuple Store Chordless Hadoop / HBase Berkeley DB Redis! Cassandra MemcacheDB Scalaris Hypertable Mnesia Tokyo Cabinet / Tyrant LightCloud GT.M HamsterDB Document stores Scalien Jackrabbit Riak Eventually Consistent CouchDB Terrastore MongoDB ThruDB Key Value Store Terrastore CloudKit Voldemort Dynomite a lm o KAI ope s t a l l n s o a re u rc e Graph Databases XML Databases Neo4J Mark Logic Server InfoGrid Sedna EMC Documentum xDB ! Sones Xindice Tamino HyperGraphDB Berkeley DB XML eXist
- 13. Background check large contributions by web content management system vendor Day (Basel)
- 14. Data Model stuc ture mandatory fields d field types schem allowed parents a etc. unst ruct ured look Ma, no schema! s schemales
- 15. 1 Data First 2 Structure Structure First later (maybe)
- 16. Data Model title: granular nosql date: 20/3/2010 binary
- 17. Data Model granular binary 1 ordere d 2
- 18. Data Model granular binary ordered node-level access control
- 19. Data Model granular binary ordered node-level access control versioning
- 20. The Sweet Spot web content http://www.flickr.com/photos/blentley/2951836266/
- 22. Background check ideas and 1st implementations by ex-Notes developer
- 23. Data Model Documents { schemaless “_id”: “abc”, “title”: “NoSQL”, JSON “tags”: [ binary attachments “data model”, “scalability” ], “_rev”: 1234 }
- 24. Interface ODBC? JDBC? HTTP! + JSON
- 25. Interface read GET /somedatabase/some_doc_id?rev=946B7D1C HTTP/1.0 write POST /somedatabase/ HTTP/1.0 Content-Length: 245 Content-Type: application/json { "Subject":"I like Plankton", "Author":"Rusty" } delete DELETE /somedatabase/some_doc?rev=1582603387 HTTP/1.0
- 26. quer y “No SQL”, remember? meet “map-reduce”
- 27. all documents results of map 1 map() reduce() 2 result 1 3 result 2 result of reduce result 3 parallel
- 28. example: map-reduce { { "total_rows":2, id: “abc”, "offset":0, title: “nosql”, "rows": type: “talk” [ } function(doc) { { if (doc.type == "talk") { "id":"abc", emit(doc.title, doc); "key":"nosql", } "value": {id: “abc”, { title: “nosql”, type: “talk”} id: “xyz”, } }, title: “ajax”, { type: “talk” "id":"xyz", } "key":"ajax", map "value": {id: “xyz”, title: “ajax”, type: “talk”} } ] }
- 29. example: map-reduce { "total_rows":2, "offset":0, "rows": [ { "id":"abc", "key":"nosql", function (key, values, rereduce) { "value": {id: “abc”, return sum(values); title: “nosql”, type: “talk”} } }, { "id":"xyz", "key":"ajax", re duce "value": {id: “xyz”, title: “ajax”, type: “talk”} } ] }
- 30. Designed for Replication t io n e not the excep co nflicts ar master master (incremental) replication on demand master
- 31. Distributed Address Book server desktop mobile (partial replication)
- 32. The Sweet Spot distributed databases with schemaless data http://www.flickr.com/photos/blentley/2951836266/
- 33. Eric Brewer: CAP Theorem Consistency choose any 2 Availability application trade-off Partition tolerance
- 34. client 1 client 2 write reads consistent value db replicate db 1 transaction 1 Partition 2 Consistency
- 35. client 1 client 2 write reads inconsistent data until replication een time betw db replicate db clicks? DNS 1 Partition 2 Availability
- 37. Background check first developed by Facebook for inbox search now also used by Twitter, Digg, ...
- 39. Data Model k v on s tero id s
- 40. Data Model keyspace Twitter column family Statuses key columns 123 user_id: “abc” text: “i can haz cheesburger” 456 user_id: “abc” reply-to: “123” text: “nom nom” plus super-co lumns column family Users
- 41. High Lights datacenter aware • High availability • Eventually consistent • Tunable tradeoffs between consistency and latency • No Single Point of Failure no no de in the clus ter is spec ial
- 42. The Sweet Spot really large data sets, really high availability http://www.flickr.com/photos/blentley/2951836266/
- 43. I’ve seen this before
- 44. reme mber the ambrian E xplosion? C extinct
- 45. “Polyglot Programming” Neal Ford, 2006 “Polyglot Persistence” Scott Leberknight , 2009
- 46. questions ? @michaelmarth | www.marth.ch