Let the Tiger Roar - MongoDB 3.0
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MongoDB 3.0 comes with a set of innovations regarding storage engine, operational facilities and improvements has well of security enhancements. This presentations describes these improvements and new features ready to be tested. https://www.mongodb.com/lp/white-paper/mongodb-3.0
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Let the Tiger Roar - MongoDB 3.0
- 2. Let the Tiger Roar! MongoDB 3.0 Norberto Leite Technical Evangelist norberto@mongodb.com @nleite
- 3. Agenda • MongoDB 3.0 • Pluggable Storage Engine API • Storage Engines – MMAPv1 – WiredTiger – WT vs MMAPv1 • Improvements
- 5. A lot of good things come with 3 • USB • 3G • Tricycle
- 6. MongoDB 3.0 • Pluggable Storage Engine API • Storage Engines • Large Replica Sets • Big Polygon • Security Enhancements – SCRAM • Audit Trail • Simplified Operations – Ops Manager • Tools Rewrite
- 7. MongoDB 3.0 is a bag full of goodies!
- 9. How does MongoDB persist data? • <= MongoDB 2.6 – One unique mechanism using Memory Mapped Files – "mmapv1" Storage Engine • MongoDB 3.0 has a few more options – mmapv1 – default – wiredTiger – (in_memory – experimental only)
- 10. Pluggable Storage Engine API h"p://www.livingincebuforums.com/ipb/uploads/monthly_10_2011/post-‐198-‐0-‐67871200-‐1318223706.jpg
- 11. Storage Engine API • Allows to "plug-in" different storage engines – Different work sets require different performance characteristics – mmapv1 is not ideal for all workloads – More flexibility • Can mix storage engines on same replica set/ sharded cluster • Opportunity to integrate further ( HDFS, native encrypted, hardware optimized …)
- 13. MMAPv1
- 14. MMAPv1 • Improved concurrency control • Great performance on read-heavy workloads • Data & Indexes memory mapped into virtual address space • Data access is paged into RAM • OS evicts using LRU • More frequently used pages stay in RAM
- 15. WiredTiger
- 16. What is WiredTiger? • Storage engine company founded by BerkeleyDB alums • Recently acquired by MongoDB • Available as a storage engine option in MongoDB 3.0
- 17. Why is WiredTiger Awesome • Document-level concurrency • Disk Compression • Consistency without journaling • Better performance on certain workloads – write heavy
- 18. Improving Concurrency • 2.2 – Global Lock • 2.4 – Database-level Locking • 3.0 MMAPv1 – Collection-level Locking • 3.0 WT – Document-level – Writes no longer block all other writes – Higher level of concurrency leads to more CPU usage
- 19. Compression • WT uses snappy compression by default • Data is compressed on disk • 2 supported compression algorithms – snappy: default. Good compression, relatively low overhead – zlib: Better • Indexes are compressed using prefix compression – Allows compression in memory
- 20. Consistency without Journaling • MMAPv1 uses write-ahead log (journal) to guarantee consistency • WT doesn't have this need: no in-place updates – Write-ahead log committed at checkpoints • 2GB or 60sec by default – configurable! – No journal commit interval: writes are written to journal as they come in – Better for insert-heavy workloads • Replication guarantees the durability
- 21. MMAPv1 vs. WT
- 22. How to run MMAPv1 • MMAPv1 is the default
- 23. How to run WT • mongod now has --storageEngine option
- 24. MMAPv1 Database Files • MMAPv1 persists data to files per databases – Indexes – Data
- 25. WT Database Files • Each collection & indexes stored in own file
- 26. Playing nice together • Can not – Can't copy database files – Can't just restart w/ same dbpath • Yes we can! – Initial sync from replica set works perfectly! – mongodump/restore • Rolling upgrade of replica set to WT: – Shutdown secondary – Delete dbpath – Relaunch w/ --storageEngine=wiredTiger – Rollover
- 27. Other WT configuration options • Compression: --wiredTigerCollectionBlockCompressor • YAML format for configuration
- 28. Gotcha's!!! • No 32-bit Support – WT is 64bit only • system.indexes & system.namespaces deprecated – Explicit commands: db.getIndexes() db.getCollectionNames()
- 30. Improvements
- 31. Benefits
- 32. Wider Range of Use Cases How: Flexible Storage Architecture • Fundamental rearchitecture, with new pluggable storage engine API • Same data model, same query language, same ops • But under the hood, many storage engines optimized for many use cases Single View Content Management Real-Time Analytics Catalog Internet of Things (IoT)Messaging Log Data Tick Data
- 33. Up to 95% Lower Operational Overhead How: MongoDB Ops Manager • The best way to run MongoDB • Automates core management tasks • Single-click provisioning, scaling, upgrades, administration • Monitoring, with charts, dashboards & alerts on 100+ metrics • Backup and restore, with point-in- time recovery
- 34. 7x-10x Performance, 50%-80% Less Storage How: WiredTiger Storage Engine • Same data model, same query language, same ops • Write performance gains driven by document-level concurrency control • Storage savings driven by native compression • 100% backwards compatible • Non-disruptive upgrade MongoDB 3.0MongoDB 2.6 Performance
- 35. h"p://www.humanandnatural.com/data/media/178/badan_jaran_desert_oasis_china.jpg Please go and test it! 3.0.0-RC7 https://www.mongodb.org/downloads http://www.mongodb.com/lp/misc/norberto-leite https://jira.mongodb.org/secure/Dashboard.jspa h"p://www.@nypm.com/blog/wp-‐content/uploads/2015/01/hammer.jpg