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Modern Applications With Azure Search (Video link in description)

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The video of the presentation: https://vimeo.com/191753332

Azure Search is the new cloud search-as-a-service solution in the Azure suite. In this demo driven talk, we'll show how developers can benefit from this ready-to-use service to add search experiences to their applications.

Starting out with a quick high level introduction, we'll then dive into demos showing how to create and push data into the index. Further, we'll spend the rest of the talk showing how to use the query language and build search capabilities modern applications require.

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Peter Lillevold works as lead developer and architect at 4Subsea, building digital services for the oil & gas industry. With close to 20 years slinging code, of which 15 years on the .NET platform, Peter have seen Azure go live and have pushed apps to the cloud ever since. He has previously held presentations at NNUG, back in the good old days, talking about continuous integration and whatnot.

Loc Tan Vo works as a senior consultant at Forse. He has been working full time with .NET since 2007, and Azure the last 4-5 years. Loc is active in the community being one of the organizers of the NNUG Oslo Meetup since 2014. He has previously held two presentations at NNUG about Lucene and Mono.

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Modern Applications With Azure Search (Video link in description)

  1. 1. B U I L D I N G M O D E R N W E B A P P L I C A T I O N S W I T H AZURE SEARCH
  2. 2. AGENDA INTRODUCTION DEMO INDEX DEMO APPLICATIONS
  3. 3. W H O I S 1 2 7. 0 . 0 . 1 ? P E T E R LILLE VO LD @ OC C UL T O LO C TA N VO @ L OC T AN V O
  4. 4. WHAT?
  5. 5. WHY?
  6. 6. NORMALIZED DATA Optimized for Write Optimized for Query? Not so much…
  7. 7. CONCEPTUALLY SEARCH INDEX A PP A PP A PP
  8. 8. IaaS, PaaS, SaaS IaaS (VMs) PaaS SaaS Source: MatVelloso, Microsoft, LEAP2016
  9. 9. Azure Search Search as a Service
  10. 10. The Index • Simple table structure defined by schema • Basic value types • string, int, long, double, DateTimeOffset • GeographyPoint • Collection ofstrings • No relationships • Up to 1000 fields per index • 16 MB per document • Scoring profiles • Give fields more weight when queried • Functions: boost weight by freshness, magnitude, distance and tags
  11. 11. Free tier • One service per subscription • Up to 3 indexes • Up to 50MB storage • Up to 10.000 documents • Shared resource environment • Locked to one replica, one partition • No SLA • Price: 0,-/SU
  12. 12. Basic tier • 12 services per subscription • Up to 100 fields per index • Up to 5 indexes • Up to 2GB storage • Up to 1.000.000 documents • Up to 3 replicas, 1 partition • SLA on queries with 2 replicas • SLA on indexing with 3 replicas • Price: 610,-/SU
  13. 13. Standard tier S1 S2 S3 S3 HD Services per sub 12 6 6 6 Indexes 50 200 200 1000 pr partition Storage per partition 25GB 100GB 200GB 200GB Partitions per service 12 12 12 3 Documents per partition 15M 60M 120M 200M or 1000 pr index Replicas 12 12 12 12 Max SUs per sub 36 36 36 36 Price per SU 2028,- 8114,- 16227,- 16227,-
  14. 14. Replica 1 Partition 1 • Inx-1 • Inx-2 Partition 2 • Inx-1 • Inx-2 Replica 2 Partition 1 • Inx-1 • Inx-2 Partition 2 • Inx-1 • Inx-2 Replica 3 Partition 1 • Inx-1 • Inx-2 Partition 2 • Inx-1 • Inx-2 Partitions, Replicas and Search Units Replicas x Partitions = Search Units (SU) = Machines = BillableUnit
  15. 15. Partitions and Replica combos 1 Partition 2 Partitions 3 Partitions 4 Partitions 6 Partitions 12 Partitions 1 replica 1 SU 2 SU 3 SU 4 SU 6 SU 12 SU 2 replicas 2 SU 4 SU 6 SU 8 SU 12 SU 24 SU 3 replicas 3 SU 6 SU 9 SU 12 SU 18 SU 36 SU 4 replicas 4 SU 8 SU 12 SU 16 SU 24 SU - 5 replicas 5 SU 10 SU 15 SU 20 SU 30 SU - 6 replicas 6 SU 12 SU 18 SU 24 SU 36 SU - 12 replicas 12 SU 24 SU 36 SU - - -
  16. 16. Queries Per Second (QPS) Free Basic S1 S2 S3 S3 HD QPS pr replica Bingo ~3 ~15 ~60 ~60 >60 Max QPS Random ~9 ~180 ~720 ~720 >720
  17. 17. Indexers • Enable populating indexes without code • Pull data in from • Azure SQL Database • DocumentDB • Blob and Table Storage • Multiple indexers write into on index • Schedule indexing on demand or recurring • Minimum 15 min intervals
  18. 18. Blob Storage Indexer • Read metadata AND content from known file types • File types supported • PDF, HTML, XML, ZIP, EML, TXT, JSON, CSV • DOCX/DOC, XLSX/XLS, PPTX/PPT, Outlook MSG • «One Document per file» • Indexing JSON arrays: «one document per object» • Supports content-specific metadata (author, title,..) • Automatic incremental index and deletion
  19. 19. Architectural Patterns
  20. 20. S ERV IC E P ER T EN AN T pro d qa t e s t Search Service Search Service Search Service
  21. 21. S H AR ED S ERV IC E PAT T ER N pro d qa t e s t Search Service
  22. 22. S H AR ED IN D EX PAT T ER N T-1Search Service T-2 $filter: tenant eq 1 $filter: tenant eq 2 $filter: tenant eq ‘ ’
  23. 23. THE DEMOS
  24. 24. INDEXING
  25. 25. DEMOGHOST
  26. 26. Search Traffic Analytics
  27. 27. R ES O U R C ES § Azure Search Documentation https://azure.microsoft.com/en- us/documentation/services/search/ § Azure Search Rest Service API https://msdn.microsoft.com/en-us/library/azure/dn798927.aspx § Query Syntaxes https://msdn.microsoft.com/library/azure/dn798920.aspx https://msdn.microsoft.com/library/azure/mt589323.aspx § ODATA FilterExpressions https://msdn.microsoft.com/library/azure/dn798921.aspx § Architectural Patterns https://blogs.technet.microsoft.com/privatecloud/2014/12/02/mo dern-datacenter-architectural-patterns-azure-search-tier/

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