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  1. 1. NoSQL Night! Singapore Spring@Pivotal User Group Clarence J M Tauro Sr. Instructor Couchbase
  2. 2. About the Speaker • Clarence J M Tauro – clarence@couchbase.com – Senior Instructor, Couchbase – ~11 Years Professional Teaching and Consulting Experience – Worked at Pivotal – Instructor/Consultant for Spring/Spring Security/Spring Web/Enterprise Integration with Spring/Spring JMS/Spring Web/Spring Batch, Pivotal Hadoop/Cloud Foundry – PhD in Computer Science from Christ University [thesis accepted] – Hard-core Dog lover
  3. 3. Disclaimer • Disclaimer: The views expressed in this presentation are our own and do not necessarily reflect the views of Couchbase
  4. 4. Objectives • Introduction to NoSQL • Are ACID Properties always desirable? • Basically available, Soft state, Eventually consistent (BASE) • The CAP Theorem • Introducing Couchbase • Couchbase Operations
  5. 5. Introduction RDBMS - predominant technology for storing structured data in web and business applications “one size fits all” - thinking concerning data-stores has been questioned Apply NoSQL databases for the persistence layer/Polyglot Programming
  7. 7. Are ACID Properties always desirable? • … But what about: – Latency – Partition Tolerance – High Availability – Scalability
  8. 8. the system is available, but not necessarily all items in it at any given point in time after a certain time all nodes are consistent, but at any given time this might not be the case information (state) the user put into the system that will go away if the user doesn't maintain it BASE
  9. 9. NoSQL Common Traits • Non-relational • Schema-free/Schema-on-read • Eventual consistency • Open source • Distributed • “web-scale”
  10. 10. The CAP Theorem • Consistency – can all nodes see identical data, at all times? • Availability – can all nodes be read from and written to, at all times? • Partition Tolerance – will nodes function normally, even when the cluster breaks? Consistency Partition Tolerance Availability CHOOSE ANY TWO
  11. 11. The CAP Theorem • CP: Consistency and Partition Tolerance - Immediately consistent data across a horizontally scaled cluster, even with network problems - Couchbase • AP: Availability and Partition Tolerance - Always services requests, across multiple data centers, even with network problems, data eventually consistent - Apache HBase or Cassandra, Couchbase (XDCR) • CA: Consistency and Availability - Always services requests with immediately consistent data, in a vertically scaled system - MySQL, Oracle, Microsoft SQL Server
  12. 12. What do you do with the Data? Operational Use •Real time intelligence •Focus on data flows and processes •Extremely fast (in-memory) reads •Extremely fast (log append) writes •Improve the current outcome Analytical Use •Batched workloads •Vast data aggregations •Retrospective analyses •Focus on data pools •Improve future outcomes
  13. 13. Hadoop vs. NoSQL Operational VelocityAnalytical Volume Real-time operational database systems improve current outcomes Batch-oriented analytical database systems improve future outcomes Hadoop NoSQL
  14. 14. Types of NoSQL • Key-value stores • Wide Column stores • Document stores • Graph databases
  15. 15. Key-Value Stores • The most common; not-necessarily the most popular • Key and a simple value - Speed - Scale - Simplicity • Find simple values by key extremely fast Clarenceuser::1234 Melisauser::1235 Michaeluser::1236
  16. 16. Document Stores • Key and a structured value (document) - Speed - Scale - Flexibility • Read/write ever-changing data about people, places, and things, at cloud-scale user::1234 { name: 'Frank', age: 37, kids: ['Sue', 'Ann', 'Bob'] } user::1235 { name: 'Carolyn', age: 56, kids: ['Tina'] } user::1236 { name: 'Tessa', age: 24}
  17. 17. Wide Column Stores • Key and nested set of tuples - Write vast volumes of data, with eventually consistent read access user::1234 name: text Frank age: number 37 kid: text Sue Ann Bob user::1235 name: text Carolyn age: number 56 kid: text Tina
  18. 18. Graph Databases • Linked list of keyed objects - Relationships • Monitor complex, dynamically networked connections user::1 234 Frank 37 Sue Ann Bob user::1 235 Carolyn 56 Tina user::1 236 Tessa 24
  19. 19. Polyglot Programming • Enterprise will have a variety of different data storage technologies for different kinds of data • We need to ask how we want to manipulate the data. This will help us figure out which persistence technologies are appropriate - User Sessions: Couchbase (Memcached)/Redis - Financial Data: RDBMS - Shopping Cart: Riak/Couchbase (Memcached) - Recommendation Systems: Neo4J - Product Catalog: Couchbase/MongoDB - Reporting: RDBMS/Couchbase Views - Analytics: Couchbase/Cassandra
  20. 20. History of Couchbase NorthScale developed a key-value storage engine Apache CouchDB database project Membase and CouchOne joined forces in February 2011 to create Couchbase, the first and only provider of a comprehensive, end-to-end family of NoSQL database products
  21. 21. What is Couchbase Server? • Couchbase Server • Is a “document” database solution • Has key/value based orientation • Is geared for JSON • Has no tables and no fixed schema • Runs on a networked cluster of nodes • Is highly scalable • Is lightning fast read/write • Has caching and persistence layers • Automatically fails-over • Couchbase Server is best suited for fast-changing data items of relatively small size
  22. 22. JavaScript Object Notation {      "firstName": "Clarence",      "lastName": "Tauro",      "age": 25,      "address":      {          "streetAddress": "21 2nd Street",          "city": "Bangalore",          "state": "KA",          "postalCode": "560059"      },      "phoneNumber":      [          {            "type": "home",            "number": "988 621-7674"          }      ] } JSON is a lightweight data-interchange format easy for humans to read and write
  23. 23. What is a Couchbase Document? {   "visibility": "PRIVATE",   "name": "Eclectic Summer Mix",   "userName": "suzyqrocks",   "type": "org.couchmusic.domain.Playlist",   "created": 1422138028037,   "updated": 1422138028072,   "tracks": [] } {   "id": "playlist:12345",   "rev": "1-0004ebc0000000000",   "flags": 0,   "expiration": 0,   "type": "json" } Document Content (Most recent in RAM and persisted to disk) Document Metadata (All keys unique and kept in RAM)
  24. 24. Couchbase Server Architecture
  25. 25. • Technology Stack for Data Manager: ­ Couchbase Client SDK (“Smart Client”) ­ Client Query API1 and Query Engine (Views) ­ Cache Layer: RAM Cache ­ Persistence Layer: Couchbase Couchbase Server Architecture
  26. 26. • Technology Stack for Cluster Manager: ­ Node Level – multiple vBuckets • Default 1024 vBuckets/number of nodes ­ Cluster Level – multiple nodes (with 1 .. * buckets)1 ­ Datacenter Level – multiple clusters (optional XDCR)2 ­ Erlang (cluster management and process supervision)3 Couchbase Server Architecture
  27. 27. Anatomy of a Couchbase Application Couchbase Client Software Cluster Map NS Server EP Engine NS Server EP Engine NS Server EP Engine {Server List} 1. REST request 8091 2. HTTP response 5. Create, Read, Update and Delete Documents Becomes a Smart Client 4. Connect CRUD Data Port 11210
  28. 28. 3333 22 Managed Cache DiskQueue Disk Replication Queue App Server Doc 1Doc 1 Doc 1 To other node Single Node – Couchbase Write Operation Couchbase Server Node
  29. 29. 3333 22 Managed Cache DiskQueue Replication Queue App Server Doc 1’ Doc 1 Doc 1’Doc 1 Doc 1’ Disk To other node Single Node – Couchbase Update Operation Couchbase Server Node
  30. 30. GET Doc1 3333 22 DiskQueue Replication Queue App Server Doc 1 Doc 1Doc 1 Managed Cache Disk To other node Single Node – Couchbase Read Operation Couchbase Server Node
  31. 31. 3333 22 2 DiskQueue Replication Queue App Server Couchbase Server Node Doc 1 Doc 6Doc 5Doc 4Doc 3Doc 2 Doc 1 Doc 6 Doc 5 Doc 4 Doc 3 Doc 2 Managed Cache Disk To other node Single Node – Couchbase Cache Eviction
  32. 32. 3333 22 2 DiskQueue Replication Queue App Server Couchbase Server Node Doc 1 Doc 3Doc 5 Doc 2Doc 4 Doc 6 Doc 5 Doc 4 Doc 3 Doc 2 Doc 4 GET Doc1 Doc 1 Doc 1 Managed Cache Disk To other node Single Node – Couchbase Cache Miss
  33. 33. Other Features of Couchbase 4.0 • Multi-dimensional Scaling • N1QL • XDCR
  34. 34. Training Get Started with Couchbase Server 4.0: www.couchbase.com/beta Get Trained on Couchbase: http://training.couchbase.com CD220: Developing Couchbase NoSQL Applications Oct 20 – Oct 23 2015 CS300: Couchbase NoSQL Server Administration Nov 17 – Nov 20 2015 Enroll Today!
  35. 35. Questions?

Notes de l'éditeur

  • 1. Most modern operating systems want a few gigabytes (Windows usually a bit more than Linux), and there may be other processes running on these nodes such as monitoring agents. There are also needs for IO caching both for views and for the general functioning of the system.  We typically recommend about 60-80% of an system’s RAM to be allocated to Couchbase’s quota, leaving the rest for headroom and memory needs outside of Couchbase itself.
    2. Cross Datacenter Replication (XDCR) is covered later in this course.
    3. See https://blog.couchbase.com/tag/erlang
  • The Memcache Client also uses a server list, but as contrasted to the Couchbase Client, there are no REST calls, it is only working over port 11210, and is very fast. This is using a proprietary Memchached protocol.
  • 1.  A set request comes in from the application .
    2.  Couchbase Server responds back that they key is written
    3. Couchbase Server then Replicates the data out to memory in the other nodes
    4. At the same time it is put the data into a write que to be persisted to disk