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![Indexes // Index nested documents > db.customers.ensureIndex( “policies.agent”:1 ) > db.customers.find({‘policies.agent’:’Fred’}) // geospatial index > db.customers.ensureIndex( “property.location”: “2d” ) > db.customers.find( “property.location” : { $near : [22,42] } ) // text index > db.customers.ensureIndex( “policies.notes”: “text” )](https://image.slidesharecdn.com/aemmongodbeffectivelydeploy-150625112110-lva1-app6891/75/Effectively-Deploying-MongoDB-on-AEM-8-2048.jpg)
![Documents are Rich Data Structures { ! first_name: ‘Paul’,! surname: ‘Miller’,! cell: 447557505611, ! city: ‘London’,! location: [45.123,47.232],! Profession: [banking, finance, trader],! cars: [ ! { model: ‘Bentley’,! year: 1973,! value: 100000, … },! { model: ‘Rolls Royce’,! year: 1965,! value: 330000, … }! ]! }! Fields can contain an array of sub-documents Fields Fields can contain arrays Typed field valuesString Number](https://image.slidesharecdn.com/aemmongodbeffectivelydeploy-150625112110-lva1-app6891/75/Effectively-Deploying-MongoDB-on-AEM-9-2048.jpg)
![Document Moves 2015-05-18T17:07:10.264+0200 [conn1298] command aem.$cmd command: findAndModify { findandmodify: "nodes", query: { _id: "10:/content/www/...", _modCount: 3 }, fields: { _id: 1 }, update: { $set: { ... }, $max: { _modified: 1431961630 }, $inc: { _modCount: 1 } } } update: { $set: { ... }, $max: { _modified: 1431961630 }, $inc: { _modCount: 1 } } nscanned:1 nscannedObjects:1 nmoved:1 nMatched:1 nModified:1 keyUpdates:0 numYields:0 locks(micros) w:116270 reslen:203 116ms! nscanned:1464 nscannedObjects:1044 nmoved:288 nMatched:1044 nModified:1044 keyUpdates:1 numYields:11 locks(micros) w:242369 169ms! nscanned:10829 nscannedObjects:10000 nmoved:1316 nMatched:10000 nModified:10000 keyUpdates:1 numYields:89 l! ocks(micros) w:2372208 1234ms!](https://image.slidesharecdn.com/aemmongodbeffectivelydeploy-150625112110-lva1-app6891/75/Effectively-Deploying-MongoDB-on-AEM-50-2048.jpg)
Uploaded byNorberto Leite
Effectively Deploying MongoDB on AEM
The document discusses using MongoDB as a scalable storage solution for Adobe Experience Manager (AEM). It introduces MongoDB and the MongoMK storage component that allows AEM to use MongoDB. The rest of the document covers best practices for sizing, deploying, and operating an AEM and MongoDB configuration including considerations for availability, volume, working set, latency, deployment automation, and operational monitoring.
Effectively Deploying MongoDB on AEM
- 1. Effectively Scale andOperate AEM with MongoDB
- 2.
- 3. Introduction Norberto Leite Technical Evangelist Madrid,Spain http://www.mongodb.com/norberto @nleite norberto@mongodb.com
- 4.
- 5. MongoDB GENERAL PURPOSE DOCUMENTDATABASE OPEN-SOURCE
- 6. MongoDB is FullyFeatured
- 7. Query Operators Condi&onal Operators $all, $exists, $mod, $ne, $in, $nin, $nor, $or, $size, $type $lt, $lte, $gt, $gte // find customers with any claims > db.customers.find( {claims: {$exists: true }} ) // find customers matching a regular expression > db.customers.find( {last: /^rog*/i } ) // count customers by city > db.customers.find( {city: ‘Philadelphia’} ).count()
- 8. Indexes // Index nesteddocuments > db.customers.ensureIndex( “policies.agent”:1 ) > db.customers.find({‘policies.agent’:’Fred’}) // geospatial index > db.customers.ensureIndex( “property.location”: “2d” ) > db.customers.find( “property.location” : { $near : [22,42] } ) // text index > db.customers.ensureIndex( “policies.notes”: “text” )
- 9. Documents are RichData Structures { ! first_name: ‘Paul’,! surname: ‘Miller’,! cell: 447557505611, ! city: ‘London’,! location: [45.123,47.232],! Profession: [banking, finance, trader],! cars: [ ! { model: ‘Bentley’,! year: 1973,! value: 100000, … },! { model: ‘Rolls Royce’,! year: 1965,! value: 330000, … }! ]! }! Fields can contain an array of sub-documents Fields Fields can contain arrays Typed field valuesString Number
- 10. Over 10,000,000 downloads 300,000 Students for MongoDB University 35,000 attendeesto MongoDB events annually Over 1,000 Partners Over 2,000! Paying Customers
- 12.
- 13. MongoDB MicroKernel • AEM6 Scalable Storage Solution • Flexible • Multi-Datacenter Deployments • Geo Distributed Content • Auto-Failover
- 14. MongoMK Nodes Blobs Se4ngs Changes ClusterNodes Metadata collec&on Content node structure Internal AEM indexes MulL version structures Blobs collec&on Binary file chunks Enforces data de-‐duplicaLon Se4ngs, Changes, ClusterNodes Internal AEM collecLons ConfiguraLon and seRngs data
- 15. MongoMK - Content Metadata Binary / Blobs
- 16. Binary / Blobs MongoMK – Metadata Metadata
- 17. MongoMK – DataModel
- 18. MongoMK – VersionControl Revisions of content are maintained as separate trees
- 19. MongoMK – DataModel
- 20. MongoMK – Versioning& Concurrency System provides version and concurrency control of content revisions.
- 21. MongoMK – Versioning& Concurrency
- 22. Binary / Blobs MongoMK – Binary Data Metadata
- 23. AEM Blob Storage TARMONGODB S3
- 24. Blobs on MongoMK Posi&ve Penalty Unified Storage Layer More Storage Requirements Reduced OperaLonal Overhead More I/O Intensive Binary De-‐duplicaLon Higher Bandwidth Requirements
- 25.
- 26.
- 27.
- 28. MONGODB SIZING Availability Volume Expected Latency Working Data Set
- 29.
- 30. Sizing - Availability AEM Edi&ng Cura&ng Valida&ng Primary Secondary Secondary
- 31. Sizing - Availability AEM Edi&ng Cura&ng Valida&ng Primary Secondary Primary
- 32. Sizing - Availability AEM -‐ author AEM -‐ author AEM -‐ author Primary Secondary Secondary Datacenter West Datacenter East Datacenter Center AEM -‐ author AEM -‐ author
- 33. Sizing - Availability AEM -‐ author AEM -‐ author AEM -‐ author Primary Secondary Secondary Backups (hidden) Hot Backups (delayed)
- 34.
- 35. Sizing - Volume Indexes ProperLes MulL Version Nodes Blobs Full Text Search Indexes Binary Chunks
- 36. Sizing - Volume • Space required by – Data – Indexes • Read / Write Ratio • Computational Unit Capacity – RAM – Disk • Types of Disks! – CPU
- 37.
- 38. Sizing – WorkingSet Working Set Rest of your Database
- 39. Sizing – WorkingSet • Percentage of data that is constantly request by the application – Indexes – Recent Used Data • Read / Write – Impacts the calculation of the RAM requirement • Working Set Should Fit In RAM
- 40. Working Set Notin RAM
- 41. Sizing – WorkingSet • AEM Calculation of Working Set – Internal MongoDB Indexes – Constantly accessed Assets • % of data access – AEM Indexes • Multi-version Indexes • Lucene Indexes
- 42. Working Set CanBe Distributed Across Shards
- 43. Sizing - Latency Primary Secondary Secondary AEM AEM AEM ONLY SECONDARY READS!
- 44.
- 45. Rules for aGood Deployment Prototype Test Monitor Scale Automate
- 46. AEM + OpsManager Scale Easily Meet SLAs Best PracLces, Automated Cut Management Overhead
- 47.
- 48.
- 49. Node Documents { "_id": "1:/norberto", "_deleted":{ "r14e211fe903-0-1": "false" }, "jcr:created": { "r14e211fe903-0-1": ""dat:2015-06-23T17:53:36.257+02:00"" }, "jcr:createdBy": { "r14e211fe903-0-1": ""admin"" }, "_commitRoot": { "r14e211fe903-0-1": "0" }, "jcr:primaryType": { "r14e211fe903-0-1": ""nam:nt:folder"" }, "_modified": NumberLong("1435074815"), "_modCount": NumberLong("1") } { "_id": "1:/norberto", … "_commitRoot": { "r14e211fe903-0-1": "0", "r14e2122a4bb-0-1": "0" }, … "_modified": NumberLong("1435074995"), "_modCount": NumberLong("3"), "_children": true, "_lastRev": { "r0-0-1": "r14e2122a4bb-0-1" } }
- 50. Document Moves 2015-05-18T17:07:10.264+0200 [conn1298]command aem.$cmd command: findAndModify { findandmodify: "nodes", query: { _id: "10:/content/www/...", _modCount: 3 }, fields: { _id: 1 }, update: { $set: { ... }, $max: { _modified: 1431961630 }, $inc: { _modCount: 1 } } } update: { $set: { ... }, $max: { _modified: 1431961630 }, $inc: { _modCount: 1 } } nscanned:1 nscannedObjects:1 nmoved:1 nMatched:1 nModified:1 keyUpdates:0 numYields:0 locks(micros) w:116270 reslen:203 116ms! nscanned:1464 nscannedObjects:1044 nmoved:288 nMatched:1044 nModified:1044 keyUpdates:1 numYields:11 locks(micros) w:242369 169ms! nscanned:10829 nscannedObjects:10000 nmoved:1316 nMatched:10000 nModified:10000 keyUpdates:1 numYields:89 l! ocks(micros) w:2372208 1234ms!
- 51. Fragmentation AEM will beconstantly growing the documents generating document moves and subsequently producing fragmentation db.adminCommand( { repairDatabase: 1 } )! h_p://docs.mongodb.org/manual/reference/command/repairDatabase/
- 52. Monitoring Performance Indicators Memory,Background Flushing Avg and Opcounters: make sure you understand these metrics! h_ps://docs.mms.mongodb.com/
- 53. Working Set Measurement h_ps://docs.mms.mongodb.com/ Page Faults and Memory aligned with Db Storage will give you and good indication of how well provision is your machine and if you need to scale out
- 54.
- 55. Takeway AEM + MongoDBis a Scalable Solution Provisioning is Key Monitor, monitor, monitor Wish List is Being Attended We Want to Help You!
- 58. MongoMK Deployment forAEM h_ps://info-‐mongodb-‐com.s3.amazonaws.com/MongoDB_AEM6_ConsulLng_Datasheet.pdf
- 59.
- 60.