Membase Intro from Membase Meetup San Francisco

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Membase Intro from Membase Meetup San Francisco

  1. 1. The Very First
  2. 2. 2 Thanks!
  3. 3. Tonight 3 • Membase Overview • Use Cases and Customer Examples • Zynga and Membase • Membase Architecture • Demo! • Developing with Membase • A Glimpse into the Future
  4. 4. What is Membase?
  5. 5. Membase is a distributed database 5 Membase Servers In the data center Web application server Application user On the administrator console Web application serverWeb application server
  6. 6. Five minutes or less to a working cluster • Downloads for Linux and Windows • Start with a single node • One button press joins nodes to a cluster Easy to develop against • Just SET and GET – no schema required • Drop it in. 10,000+ existing applications already “speak membase” (via memcached) • Practically every language and application framework is supported, out of the box Easy to manage • One-click failover and cluster rebalancing • Graphical and programmatic interfaces • Configurable alerting Membase is Simple, Fast, Elastic 6
  7. 7. Membase is Simple, Fast, Elastic 7 Predictable • “Never keep an application waiting” • Quasi-deterministic latency and throughput Low latency • Built-in Memcached technology High throughput • Multi-threaded • Low lock contention • Asynchronous wherever possible • Automatic write de-duplication
  8. 8. Membase is Simple, Fast, Elastic 8 Zero-downtime elasticity • Spread I/O and data across commodity servers (or VMs) • Consistent performance with linear cost • Dynamic rebalancing of a live cluster All nodes are created equal • No special case nodes • Any node can replace any other node, online • Clone to grow Extensible • Filtered TAP interface provides hook points for external systems (e.g. full-text search, backup, warehouse) • Data bucket – engine API for specialized container types
  9. 9. Built-in Memcached Caching Layer 9 Memcached Membase Database Membase Cache Membase Database Memcached Mode Membase Mode Fact: Membase development team has also contributed over half of the code to the Memcached project.
  10. 10. Use Cases
  11. 11. Ad targeting 11 events profiles, campaigns profiles, real time campaign statistics 40 milliseconds to come up with an answer. 2 3 1
  12. 12. Search and Gaming Portal 12 Database
  13. 13. (Zynga slides not available)
  14. 14. Membase Architecture
  15. 15. Clustering • Underlying cluster functionality based on erlang OTP • Have a custom, vector clock based way of storing and propagating... – Cluster topology – vBucket mapping • Collect statistics from many nodes of the cluster – Identify hot keys, resource utilization 15
  16. 16. TAP • A generic, scalable method of streaming mutations from a given server – As data operations arrive, they can be sent to arbitrary TAP receivers • Leverages the existing memcached engine interface, and the non-blocking IO interfaces to send data • Three modes of operation Working set Data Mutations Working set Data Mutations Working set 17
  17. 17. Membase data flow – under the hood 18 SET request arrives at KEY’s master server Listener-Sender Master server for KEY Replica Server 2 for KEYReplica Server 1 for KEY 3 3 1 SET acknowledgement returned to application2 DiskDisk Disk RAM membasestorageengine DiskDisk Disk 4
  18. 18. ns_server membase (memcached + membase engine) moxi ns_server vbucketmigrator TAP memcached operations with tap commands memcached operations Client port 11211 memcached operations moxi + Client port 11210 memcached operations REST/comet cluster topology and vbucket map Clients, nodes and other nodes 19
  19. 19. Data buckets are secure membase “slices” 20 Membase data servers In the data center Web application server Application user On the administrator console Bucket 1 Bucket 2 Aggregate Cluster Memory and Disk Capacity
  20. 20. vBucket mapping 21
  21. 21. Disk > Memory BucketConfiguration mem_high_wat mem_low_wat memory quota 22 Dataset may have many items infrequently accessed. However, memcached has different behavior (LRU) than wanted with membase. Still, traditional (most) RDBMS implementations are not 100% correct for us either. The speed of a miss is very, very important.
  22. 22. Membase Demo
  23. 23. Key-Value Patterns
  24. 24. Key-Value 25
  25. 25. Key-Value 25 Items have: Key Value Expiration Flags CAS (more on this later) Operations include: Get/Set Increment/Decrement Append/Prepend
  26. 26. Key-Value 25
  27. 27. Key-Value Image courtesy http://www.flickr.com/photos/brenda-starr/3509344100/sizes/m/in/photostream/ (with a replica ) 25
  28. 28. Membase Datatypes 26
  29. 29. Membase Datatypes • byte[] – Does your data have 1s and 0s? 26
  30. 30. Membase Datatypes • byte[] – Does your data have 1s and 0s? 26 “Any customer can have a car painted any colour that he wants so long as it is black.”
  31. 31. Membase Datatypes • byte[] – Does your data have 1s and 0s? 26 “Any customer can have a car painted any colour that he wants so long as it is black.” • Items do have flags – Many clients use flags –Data type options • Google protobuf • Thrift • Avro
  32. 32. Transactions • Lock == slow me down • CAS operations – Optimistic locking • Very useful with complex datatypes – Imagine two clients trying to update a complex item • You’re likely using CAS already... if you use a CPU 27 User 1 Fail! User 2 Success
  33. 33. Common Use: Sessions • Web user sessions – Highly read, less writes in many case – Protocol advantage of memcached • Options already for PHP, Ruby and Java • Application state – Not necessarily “entity” style things – May be appropriate for a “cache” pool 28
  34. 34. Common Use (cache): Rate Limiting • Want to provide API calls into the system – Twitter search – Google search services • Use the atomic increment – Set an item with a unique ID – Upon API request, increment and check • HTTP 420: go away and come back later 29 Your Users Your App ¡Ouch!
  35. 35. Looking Ahead: NodeCode Frank Weigel, Membase
  36. 36. Beyond key-value • Indexing/Range Queries • Advanced Data Structures • Sub-object direct manipulation Validation and In-flight transformation • Block mutations failing validation • Enrich or transform objects Connectors (Integrate easily with other systems) • Solr • Hadoop • MySQL NodeCode – Motivation 31
  37. 37. NodeCode - What is it? Method for extending & customizing Membase Separate code modules Defined interface to datapath and cluster manager Notification on events • Synchronous • Asynchronous 32
  38. 38. Simple • Packaged modules for easy install and enable • Library of “off the shelf” modules • Module monitoring • Straight forward development and debugging Fast • Low latency/high-throughput • Per-bucket process isolation • Don’t break data manager performance/correctness Elastic • Automatically migrate and instantiate on rebalance • Provide support for migration of internal data • Leverage native Membase engine for internal data storage NodeCode – Drivers 33
  39. 39. Block-level architecture 34
  40. 40. Java only – jar format Must implement minimal module API • Initial module startup • Module removal • Association with bucket NodeCode library helper functions • Register synchronous & asynchronous listeners/callbacks • Register protocol extension/callbacks • Register rebalance callback • Register cluster manager event callbacks • Membase data access NodeCode 1.0 Plans 35
  41. 41. 37 Q&A
  42. 42. Attributions • http://commons.wikimedia.org/wiki/ File:Flag_of_China.png • http://commons.wikimedia.org/wiki/ File:Flag_of_South_Korea.svg • http://commons.wikimedia.org/wiki/ File:Flag_of_Japan.svg 38

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