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Introduction à DocumentDB

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1er décembre 2015
Groupe Azure

Sujet: Introduction à DocumentDB
Conférencier: Vicent-Philippe Lauzon, Microsoft

Azure DocumentDB est une base de données de type NoSQL. Lors de cette introduction à DocumentDB, vous verrez:

• Ce qu'est une base de données NoSQL
• Comment DocumentDB se compare t-il face aux autres base de données Azure
• Comment DocumentDB se compare t-il face aux autres base de données NoSQL
• Comment créer et gérer une base DocumentDB
• Comment l'utiliser (outils + C#)
• Sécurité
• Performance / Capacité

Vincent-Philippe Lauzon est un Microsoft Azure Solution Architect & Machine Learning / Consultant Sénior chez CGI. Vous pouvez lire son blog http://vincentlauzon.com et le suivre sur Twitter https://twitter.com/vplauzon

1er décembre 2015
Groupe Azure

Sujet: Introduction à DocumentDB
Conférencier: Vicent-Philippe Lauzon, Microsoft

Azure DocumentDB est une base de données de type NoSQL. Lors de cette introduction à DocumentDB, vous verrez:

• Ce qu'est une base de données NoSQL
• Comment DocumentDB se compare t-il face aux autres base de données Azure
• Comment DocumentDB se compare t-il face aux autres base de données NoSQL
• Comment créer et gérer une base DocumentDB
• Comment l'utiliser (outils + C#)
• Sécurité
• Performance / Capacité

Vincent-Philippe Lauzon est un Microsoft Azure Solution Architect & Machine Learning / Consultant Sénior chez CGI. Vous pouvez lire son blog http://vincentlauzon.com et le suivre sur Twitter https://twitter.com/vplauzon

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Introduction à DocumentDB

  1. 1. MS Azure DocumentDB MSDEVMTL GROUPE AZURE OCTOBER 26TH, 2015
  2. 2. Who am I? Vincent-Philippe Lauzon Cloud Solution Architect Microsoft Canada Blog: http://vincentlauzon.com Twitter: http://twitter.com/@vplauzon
  3. 3. Audience I’ve read about Azure I’ve tried Azure Working with Azure Azure is what I do
  4. 4. No SQL  NO SQL → Not Only SQL  Other than Tabular / Relational model  Less / No up-front (schema) design  Easier to scale horizontally (cluster)  Make them a better match for big data  Each Product makes different tradeoffs  Younger & less complete feature set
  5. 5. No SQL on Azure  Fully Managed  Table Storage (Key Value)  Redis (Key Value)  Hadoop HBase (Wide Column)  Hadoop Hive (ad hoc tables)  DocumentDB (Document)  Through Marketplace  MongoDB (Document)  CouchBase (Document)  Cassandra (Wide Column)  Neo4J (Graph)
  6. 6. Azure DocumentDB  NoSQL document database as-a-service  Query JSON docs: whole docs are indexed  Familiar languages: SQL & JavaScript  Fast / Predictable Performance (SSD)  Tunable consistency  Flexible document schema without sacrificing queryability  Will be available on Azure Stack (on premise)
  7. 7. Conceptual Domain 101 010 DocumentDB account Databases Users Permissions Collections Documents Attachments Stored procedures Triggers User-defined functions your Documents here { } { } JS JS JS
  8. 8. Demo: Account Creation & Adding Documents
  9. 9. Collections  Collections are not tables  Unit of partitioning / Scaling Unit  Transaction boundary  No enforced schema, flexible  Queries or updates stay within one collection  Size of 10 Gb  For more, you need to shard through multiple collections  e.g. Spill-over, Range
  10. 10. Demo: Simple Querying
  11. 11. More on querying  Visit the Querying Playground:  https://www.documentdb.com/sql/demo  Use the cheat sheet  http://aka.ms/docdbcheatsheet  Data Migration Tool:  https://azure.microsoft.com/en- us/documentation/articles/documentdb-import-data/
  12. 12. Querying limitation  Within a collection  No inter-document joins  (yet?)  Beside filtering, only ORDER BY is supported  No aggregation yet   No COUNT  No GROUP BY  No SUM, AVG, etc.  SQL for queries only  No batch UPDATE or DELETE or CREATE
  13. 13. Indexing  Every property is indexed!  Unless you opt out  You can opt-out selectively  Leave out paths  Per collection (policy) or per document  Indexing mode: consistent vs lazy  Kind: hash, range & spatial  Automatic vs manual  You might want to fiddle with it: indexes take space  You can now change them online!
  14. 14. Demo: Looking at indexing policy
  15. 15. Consistency  Set at the account level  Can be overridden at the query level  4 Levels  Strong  Bounded staleness  Session  Eventual
  16. 16. Demo: Looking at consistency level
  17. 17. DocumentDB at Microsoft over 425 millionunique users store 20TB of JSON document data under 15ms writes and single digit ms reads store for 40+ app / device combinations available globally to serve all markets user data store
  18. 18. Other objects 101 010 DocumentDB account Databases Users Permissions Collections Documents Attachments Stored procedures Triggers User-defined functions your Documents here { } { } JS JS JS
  19. 19. Limitations / Quotas https://azure.microsoft.com/en-us/documentation/articles/documentdb-limits/ Entity Quota Accounts 5 (soft) Dbs / Account 100 Permissions / Account 2M Sprocs, Triggers & UDFs / collection 25 Max Execution Time / Sproc, Triggeer 5 seconds Collections / DB 100 (soft) ID Length 255 chars AND, OR / query 20
  20. 20. Demo: .NET SDK
  21. 21. Data Modeling – Polymorphism  Put every document type in a collection  Discriminate on document type somehow  documentType property or other mechanism  Use Collection as scaling units not as categorization unit
  22. 22. Data Modeling – Denormalization  Optimize for read (no inter-doc joins)  Embed relationships in document  One-to-few relationships  Data changing infrequently  Data that is integral to documents  When embed provides better reading perf  Make sure the pattern fit: you read much more than you write  Gone wrong: blog posts & comments  Leverage x-doc transaction (stored procs)
  23. 23. Data Modeling – Normalization  Normalize  One-to-many (unbound)  Many-to-many  Frequent changes  If nothing in here fits: stick with relational
  24. 24. Integration within Azure  Indexer for Azure Search  https://azure.microsoft.com/en- us/documentation/articles/search-howto-connecting- azure-sql-database-to-azure-search-using-indexers- 2015-02-28/  Power BI:  https://azure.microsoft.com/en-us/blog/unleashing- insights-from-data-in-documentdb-with-power-bi/  Data Factory: both source & sink  Sink in Stream Analytics:  https://azure.microsoft.com/en-us/blog/azure-stream- analytics-and-documentdb-for-your-iot-application/
  25. 25. IMDB import Batch Event Hub Stream Analytics DocumentDB
  26. 26. Log Analysis Example DocumentDBWeb SiteApp Logs { eventName = “busRead“, duration = “0:0:21.423“, subscription = “XYZ”, messageCount=“3” } http://bit.ly/1JQbkTH { eventName = “requestFailed“, duration = “0:0:0.231“, error = “…”, endPoint=“http://oursite.com/...” }
  27. 27. Thank you!  All demo material is available here: http://bit.ly/1SrhVcA

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