Vortrag für die .NET User Group Frankfurt

1. aus der Praxis
13.12.2011
Dipl.-Inf. (FH) Johannes Hoppe
M.Sc. Johannes Hofmeister

2. Johannes Hoppe
.NET Webentwickler
www.johanneshoppe.de

3. Johannes Hofmeister
.NET Domänenexperte
www.twitter.com/pro_cessor

4. 01
Not only SQL

5. Daten
2002 2004 2006 2008 2010 2012

6. Daten
› Facebook hat 60k Server (2010)
› Google hat 450k Server (2006)
› Microsoft: hat 100k - 500k Server (seit Azure)
Facebook Server Footprint

7. Trend 1: increasing data sizes
Trend 2: more connectedness (“web 2.0”)
Trend 3: more individualization (fever structure)

9. verteilte und horizontale Skalierbarkeit
kein relationales Datenmodell (kein SQL)
schemafrei / schwache Schemarestriktionen
anderes Konsistenzmodell

10. Scale-up
Vertikale Skalierung
Server auf mehr Leistungsfähigkeit trimmen

11. Scale-out
horizontale Skalierung
Einfügen von Nodes (Rechnerknoten)

12. Schemafrei
kein ALTER TABLE
kein Wartungsfenster *
Datenversionierung im Code!
* morgens ausschlafen

13. Anforderungen
an ein verteiltes System
Consistency
Konsistenz
Partition
Availability
Tolerance Verfügbarkeit
Ausfalltoleranz

14. CAP Theorem
› 2000: E. Brewer, N. Lynch
› You can satisfy
at most 2 out of the 3 requirements

15. Consistency
› The system is in a consistent state after an operation
› All clients see the same data
› Strong consistency (ACID)
vs. eventual consistency (BASE)
ACID: Atomicity, Consistency, Isolation and Durability
BASE: Basically Available, Soft state, Eventually consistent

16. Availability
› System is “always on”, no downtime
› Node failure tolerance
– all clients can find some available replica
› Software/hardware upgrade tolerance

17. Partition tolerance
› System continues to function even when
split into disconnected subsets (network disruption)
› Not only for reads, but writes as well

18. “Drum prüfe,
wer sich ewig bindet.”
Friedrich Schiller

19. Kategorisierung
› Key-Value stores
› Document stores 
› Wide Column stores
› Graphdatenbanken
› weitere

20. 02
MongoDB

21. NoSQL
MongoDB Quick Reference Cards
http://www.10gen.com/reference

22. “Deployment”
› Standardverzeichnis erstellen: c:datadb
› Server-Start: mongod.exe
› Shell: mongo.exe

24. BSON Master/Slave
JavaScript C# Driver
Sharding GNU AGPL

25. JSON  BSON
All JSON documents are stored in a binary
format called BSON. BSON supports a
richer set of types than JSON.
http://bsonspec.org

26. CRUD – Create
(in the shell)
› db.people.save({name: 'Smith', age: 30});
See how the save command works:
› db.foo.save

27. CRUD – Create
…with a bit JavaScript
for(i=0; i<1000; i++) {
['quiz', 'essay', 'exam'].forEach(function(name) {
var score = Math.floor(Math.random() * 50) + 50;
db.scores.save({student: i, name: name, score: score});
});
}
db.scores.count();

28. CRUD – Read
Queries are specified using a document-style syntax!
› db.scores.find();
› db.scores.find({score: 50});
› db.scores.find({score: {"$gte": 70}});
› db.scores.find({score: {"$gte": 70}});

29. CRUD – Update
› db.people.update({name: 'Smith'}, {'$set': {interests: []}});
› db.people.update({name: 'Smith'},
{'$push': {interests: ['chess']}});

30. CRUD – Delete
› db.dropDatabase();
› db.foo.drop();
› db.foo.remove();

31. “Map Reduce is the Uzi of aggregation
tools. Everything described with count,
distinct and group can be done with
MapReduce, and more.”
Kristina Chadorow, Michael Dirolf in MongoDB – The Definitive Guide

32. https://webnote.codeplex.com

33. 03
RavenDB

34. NoSQL
Raven Db Documentation – All you need to know
http://beta.ravendb.net/docs

35. JSON Transactional
LINQ Lucene
100% .NET AGPL / dual

36. RavenDb
› Written by Oren Eini aka Ayende Rahien
› Hibernating Rhinos
› Rhino Mocks & Rhino.ServiceBus
› Written in C#

37. Deployment
› Get it via NuGet
› Change defaults in Raven.Server.exe.config
› It’s safe by default
› Just run the Raven.Server.exe in the /server/ folder

39. Safe by default
› Useful defaults
› E.g. Limited page size – No Accidental SELECT *
› ACID
› Client / Server
› Cross shard

40. Units
› Documents
› Collections
› Indexes
› Attachments

41. Designed to “just work”
› Schema Free
› Hardly any mapping required
› dynamic (C# 4) yields great power

42. Designed to “just work”
› Sleek Client API
› Fluent API
› Unit of Work Pattern
› Extensible – Plugin Support

43. Makes developers happy
› Testable
› Interfaces all over
› In-Memory Database
› Extensible – Plugin Support

44. APIs
› Native .NET Client API
› HTTP API (Pseudo REST)

45. Indexes
› Written as Linq Queries
› Indexed with Lucene .NET
› Lucene Syntax for querying

46. “While being RESTful is a goal of the
HTTP API, it is secondary to the goal of
exposing easy to use and powerful
functionality”
Ayende Rahien on the HTTP API - http://ravendb.net/documentation/docs-http-api-restful

47. HTTP API
› Caching
› E-Tags
› Lucene Queries possible
C:>curl -X GET http://localhost:8080/docs/Categories/1 -i
HTTP/1.1 200 OK
Content-Type: application/json; charset=utf-8
ETag: 00000000-0000-0200-0000-000000000004
{
"Name" : "Normal Importance",
"Color" : "green"
}

48. Lucene Style Queries
Classic Linq Style Lucene Style
var notes = session var notes = session.Advanced
.Query<Note>() .LuceneQuery<Note>()
.Where(n => n.Category == “Important") .Where(“Category:Important")
.ToArray(); .ToArray();

49. 04
Tabellen  Dokumente

50. 05
Key and Index Strategies

52. FRAGEN?

53. https://webnote.codeplex.com/

54. Vielen Dank!
Johannes Hoppe
Johannes Hofmeister

55. Bildnachweise
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Warnhinweis-Schild © Sascha Tiebel – Fotolia.com
Liste abhaken © Dirk Schumann – Fotolia.com
Stressed businessman © Selecstock – Fotolia.com