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Moving from SQL Server to MongoDB

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Moving from SQL Server to MongoDB - Lessons Learned

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Moving from SQL Server to MongoDB

  1. 1. BuzzNumbers Presentation<br />Moving From SQL Server to MongoDB<br />
  2. 2. Todays Presentation<br />Problems faced with Social Media Monitoring/Analytics<br />Why choose NoSQL over SQL <br />Why choose MongoDB<br />NOSQL Vs SQL Schema Design<br />Infinite scalability with commodity hardware & .NET<br />Why we still use .NET (why not Ruby/Java/Python)<br />Lessons Learned<br />
  3. 3. NOSQL at BuzzNumbers<br />About BuzzNumbers<br />
  4. 4. About BuzzNumbers<br />SaaSWeb Product Company<br />Web and Social Media Analytics<br /> Collect “big data”web content<br />Near-Realtime data capture<br />News, Blogs, Social Mediaetc<br />Scraping, API’s, Feeds<br />Analytics & Business Intelligence<br />BI, Text, Sentiment, Locations, NLP, Machine Learning <br />
  5. 5. BuzzNumbers Project Team<br /> Nick Holmes a Court - @nickhac<br />Brett Anderson - @brehtt<br />Steve Casey - @stevencasey<br />Jacinto Santamaria<br />Chris Fulstow - @chrisfulstow<br />Josie Kidd - @jose9 <br />
  6. 6. NOSQL at BuzzNumbers<br />Problems Faced at BuzzNumbers<br />
  7. 7. Problems faced at BuzzNumbers<br /> Large and fast growing DB Tables<br />Lots of Read/Writes from data collection 24/7<br /> Massive Table Scans for user reports (< 3 sec SLA)<br /> Large Joins (10+ Tables) with Nested Views<br /> Complex Queries (Aggregates, Where’s, FullText) <br />FullText Search Indexes needed real-time updates <br /> Read/Write Contention <br /> Rapid Index fragmentation, Slow rebuilds <br /> DB Locks occurring (with no implicit Transactions)<br /> Blocking Transactions (both small/large tables)<br />
  8. 8. Outgrew SQL Server Enterprise 2008<br />“Free” Software from MSFT from BizSpark<br /> Tried everything with SQL Enterprise<br />Significant SQL Performance Tuning <br /> Dirty Reads (nolock), Offline Index Rebuilds<br />Replication / Clustering / Multi-Instance<br /> Problems<br /> Schema changes impossible with uptime requirements<br />DBA tasks made system unavailable for hours/days<br />Hardware / SQL DBA got very expensive<br /> Web users experienced annoying / unnecessary waits on blocked queries that were non-complex because of joins<br />
  9. 9. BuzzNumbers NOSQL Presentation<br />Why NOSQL over SQL<br />
  10. 10. What is NOSQL<br /> New generation of “Databases”<br /> “Not Only SQL” - Mostly Open Source <br /> NOSQL Distributed database designed to deliver<br /> Distributed “Big Data” storage<br /> Distributed processing of queries/calculations<br /> NOSQL Examples include<br />Google– BigTable<br />Yahoo -Hadoop (30k+ Nodes)<br />Facebook - Cassandra<br />FourSquare - MongoDB<br />
  11. 11. Why NoSQL over SQL<br />SQL <br />Guaranteed consistency<br />Transactions<br />Schemas / DataTypes<br />Joins / Foreign Keys<br />TSQL/PL-SQL (Views, Procs)<br />Scale Up (hardware)<br />Many Benefits including<br />Ease of use<br />Many developers skilled in SQL<br />Trusted for decades / Proven<br />NoSQL<br />Eventual Consistency<br />No Transaction Support<br />Key/Value Data (mostly)<br />Flat Data (no joins)<br />Key Lookups / MapReduce / Code<br />Scale out (distributed)<br />Many Benefits including<br />Performance / Scale<br />Lower license costs<br />Solves Web2 problems<br />
  12. 12. Why NoSQL over SQL<br />CAP Theorem <br />Consistency<br />Availability<br />Partitioning<br />Only 2 of 3 are Possible<br />Consistency/Availability <br />RDBMS<br />Availability / Partitioning <br />NOSQL<br />Consistency / Partitioning <br />Availability Issues (No one wants this)<br />
  13. 13. BuzzNumbers NOSQL Presentation <br />Why MongoDB for NOSQL?<br />
  14. 14. NOSQL Providers<br />
  15. 15. Who uses Mongo?<br />
  16. 16. Why Mongo<br /> Proven for multiple usage scenarios<br />High performance (eventual consistency) <br /> Data stored in JSON (not only Key/Value)<br />Supports Multiple Indexes (Anywhere in JSON)<br />Easy to Install, Easy to Use(Linux/Windows)<br />Easy to Scale for High Volume Writes (Sharding)<br />Easy to Scale for High Volume Reads (Replica Sets)<br />Automatic Failover and Redundancy (Replica Sets)<br />REST Interface and Drivers for Ruby/.NET/Java/Etc<br />Easy to Query via multiple techniques<br />Key/Value, Mongo Query, JavaScript, MapReduce<br />
  17. 17. BuzzNumbers NOSQL Presentation <br />Moving from SQL Schema to No-Schema<br />
  18. 18. BuzzNumbers NOSQL Presentation <br />RDMBS Schema (Tables)<br />Mongo Collection (JSON)<br />
  19. 19. BuzzNumbers NOSQL Presentation <br />RDMBS Schema<br />Mongo JSON Document<br />
  20. 20. BuzzNumbers NOSQL Presentation <br />RDMBS Schema<br />Mongo JSON Document<br />One Document Per Website Per Day<br />
  21. 21. BuzzNumbers NOSQL Presentation <br />RDMBS Schema<br />Mongo JSON Document<br />Pre-Aggregate SUM/COUNT/AVG Calculations using UPSERT<br />
  22. 22. BuzzNumbers NOSQL Presentation <br />RDMBS Schema<br />Mongo JSON Document<br />Store Line Items with rich data as Nested Arrays .<br />Use JavaScript or MapReduce to Query<br />
  23. 23. Basic SQL vs Mongo Syntax<br />Select * from Clients<br />db.clients.find()<br />Select * from Clients where clientid = 1<br />db.clients.find({”ClientID” :1})<br />Insert into clients (ClientID, Name) Values (1, “ACME”)<br />db.clients.ìnsert({”ClientID” :1,”Name”:”ACME” })<br />Create Table / Alter Table<br /> Just start inserting db.client.insert({JSON HERE})<br />Create Index<br />db.clients.ensureIndex({“ClientID”:1, “Name”:1})<br />
  24. 24. Basic SQL vs Mongo Syntax<br />Select * from Clients<br />db.clients.find()<br />Select * from Clients where clientid = 1<br />db.clients.find({”ClientID” :1})<br />Insert into clients (ClientID, Name) Values (“ACME”, 1)<br />db.clients.ìnsert({”ClientID” :1,”Name”:”ACME” })<br />Create Table<br /> Just start inserting<br />Create Index<br />db.clients.ensureIndex({“ClientID”:1, “Name”:1})<br />
  25. 25. BuzzNumbers NOSQL Presentation <br />Infinite Scale with .NET and NOSQL<br />
  26. 26. Infinite Scale with .NET<br /> Use .NET for Rapid Product Development<br /> Web Applications (IIS, ASP.NET, User Databases)<br /> Server Applications (Scraping, Apps, Services, Data)<br />Scheduled Tasks / Backend Jobs<br /> Use Open Source for Infinite Scale on Linux<br />MongoDB for Big Data Storage <br /> SOLR (distributed Lucene) for Full Text Indexing<br />.NET Drivers Available for Mongo/SOLR<br />
  27. 27. Infinite Scale with .NET<br /> Cloud Hosting for Low Cost Scale<br /> Rackspace Cloud ($200 p/m per 4GB-RAM server)<br /> Windows and Ubuntu – Image/Clone/API support<br />Zabbix Monitoring – notify when near capacity<br /> Amazon/Heroku/dotCloud alternates<br /> Tips to deliver fantastic performance at scale<br /> Indexes MUST fit in RAM (Disk Reads are Slow)<br />SSD’s HardDisks are worth the extra price<br />4GB RAM / 160GB Disk seems to be optimum price/performance per node in distributed system<br />
  28. 28. BuzzNumbers NOSQL Presentation <br />Why we stay with .NET?<br />
  29. 29. Why we stay with .NET<br /> Visual Studio best IDE!!!<br />SQL Server great database for most Data<br /> Proven Tech Stack (low corporate risk) <br /> Lots of support (MSFT and Consultants)<br /> Large online community with code samples<br /> Many Open Source libraries <br /> ASP.NET MVC RAZOR is RAD<br />Non-Complex Sysadmin for Windows Servers<br /> Drivers/Integration available for most OSS Projects<br /> Lots of Agile/Scrum/TDD/CI/Project Management tools<br /> Lots of smart .NET web developers & engineers<br />
  30. 30. BuzzNumbers NOSQL Presentation <br />Lessons Learned<br />
  31. 31. Lessons Learned<br />“Big Data” is not 100M records: but 1BN+ <br />Don’t scale until you need to (Premature optimisation costs - big time)<br />SQL RBDMS solves most problems but Scale up costs are prohibitive for startups so plan in advance when you might need to switch<br />Mixing SQL for SmallData and NOSQL for BigData delivers both ease/speed of development and performance<br />Mongo/SOLR works well to solve specific performance problems <br />Not all problems are equal: optimiseeach solution per performance problem<br />Don’t go NOSQL unless you absolutely need to<br />Very early technology with lots of learning overhead, risks and production issues<br />Skilled .NET/Mongo/SOLR engineers are very hard to find<br />If client/data segmentation is possible, multiple SQL instances can deliver<br />Ensure Indexes fit in Memory<br />Spend time planning your schema in advances based on query requirements<br />
  32. 32. BuzzNumbers NOSQL Presentation <br />Interested to learn more?<br />
  33. 33. Thanks for your time<br /> Speak with one of the Buzz Team tonight<br /> Join our Team? We’re Hiring!<br />Web Developers<br />Software Engineers<br />UX / Web Designers<br />Immediate and Future roles… Talk to us!<br />

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