The presentation discusses Wordnik's use of MongoDB, highlighting its robust performance and necessary management strategies for maintaining large datasets. It covers various operational insights, including replication, incremental backups, and disaster recovery scenarios. The document emphasizes the importance of careful data handling and the collaborative efforts between engineering and IT operations.

1. Mongo SVKeeping the lights on with MongoDBTony Tam12/3/2010

2. Presentation OverviewData >>> codeTreat it appropriatelyManage and maintain MongoMongo is young (and robust!)Performance and FeaturesThe right hooks exist

3. Who is WordnikWordnik is:The world’s largest English Language reference ~10M words!Mapping every word, based on real data(free ) API to add word information, everywhere

4. Wordnik’s MongoDB DeploymentOver 12 Months with MongoCorpus/UGC/Structured Data/StatisticsMaster/Slave~3TB data~12B recordsWe love Mongo’s performanceRead more:http://blog.wordnik.com/12-months-with-mongodb

5. Engineering + IT OpsFirst, Guiding PrinciplesKnow your dataDon’t rely on IT magicEqual Importance in WebApps / SaaSHold hands and be friendsIf you can’t manage it, don’t deploy it

6. Admins: Be Preparedok, this sucks.

7. How?Replicate!Is that enough?Well, not if your company is on the lineSnapshotEvery minute???Export oftenReally???

8. Then What?Yes, Mongo can do IncrementalUse the mongo slave mechanismIt’s exposedIt’s supportedIt’s very easyIt’s extremely fastHow?Snapshot your dataStream write ops to diskRepeat

9. Better than FreeTake our tools-They work!!!SnapshotUtilSelectively snapshot in BSONIndex info too!IncrementalBackupUtilTail the oplog, stream to diskOnly the collections you want!Compress & rotateRestoreUtilRecover your snapshotsApply indexes yourselfReplayUtilApply your Incremental backups

10. What if ScenariosOne collection gets corrupt?Restore itApply all operations to it“My top developer dropped a collection!”Restore just that oneApply operations to it until that POT“We got hacked!”Restore it allApply operations until that POT

11. What else is possible?ReplicationWhy not use built-in?Control, of courseSame logic as Incremental + ReplayAdd some filters and it gets interesting

12. Hot DatacenterCreate incremental backupsCompressPush to DC in batchApply to masterPrimary DatacenterHot DatacenterIncremental Backup FilesMasterMasterReplay UtilSCP

13. Dev EnvironmentDevelopers need production-ish dataAnonymize while replicating to dev server

14. Multiple Upstream MastersAggregate to single collectionTarget can be a master!Master AMaster BMaster Cdb.page_viewsdb.page_views

15. Unblock MapReduceMap Reduce can lock up your serverReplicate source data to another mongodReplicate results back to masterMasterMR Serverdb.source_datadb.summary_data

16. Mesh ModeWrite to Multiple MastersFilter by “Server Identifier”> db.documents.find().limit(2){"_id":99887,"src":2,"title":"favorite.png","fsid":33774}{"_id":128773,"src":1,"title":"select.png","fsid":837743}db.documentsdocuments.src != 1Master 1Master 2db.documentsdocuments.src != 2

17. What’s NextMulti-Master in Wordnik ProductionMultiple Datacenter PresenceMore data => more challenges

18. Try it outhttp://blog.wordnik.com/mongoutilsQuestions?