Manuel Hurtado. Couchbase paradigma4oct

Introducción a Couchbase Manuel Hurtado Solutions Engineer

©2015 Couchbase Inc. 3 Couchbase Server Defined § Couchbase Server 4.X is the first NoSQL Database to enable you to develop with agility and operate at any scale. Managed Cache Key-Value Store Document Database Embedded Database Sync Management

©2015 Couchbase Inc. 4 The Power of the Flexible JSON Schema Ability to store data in multiple ways • Denormalized single document, as opposed to normalizing data across multiple table • Dynamic Schema to add new values when needed

©2015 Couchbase Inc. 5 Document Fundamentals -‐ Composition § Similar to primary keys in relational databases § Documents are partitioned based on the document ID § ID based document lookup is extremely fast § Must be unique § JSON § Binary -‐ integers, strings, booleans § Common binary values include serialized objects, compressed XML, compressed text, encrypted values Document ID or Key Value § CAS Value (unique identifier for concurrency) § TTL § Flags (optional client library metadata) § Revision # Metadata Document Document ID / Key MetadataValue

©2015 Couchbase Inc. 7 Couchbase Data Access • Everything is layered on top of Key Value • A Document store is a special case of Key- Value • Views provide aggregation and real-time analytics through incremental map-reduce • Global Secondary Indexes provide low latency/high throughput indexes • N1QL is a language that provides a powerful and expressive way of accessing documents

©2015 Couchbase Inc. 9 Docker Support § Deployment Scenarios § Single host, single container § Single host multiple containers § Multiple hosts, single container on each host § Multiple hosts, multiple containers per host § https://hub.docker.com/_/couchbase/

©2015 Couchbase Inc. 10 Top Use Cases Profile Management Personalization 360o Customer View Internet of Things Content Management Catalog Real Time Big Data Digital Communication Mobile Applications HighAvailabilityCaching

©2015 Couchbase Inc. 11 World of Operational Databases 11 Graph Stores Neo4j RDBMS/Transactional Stores Oracle, DB2, SQLServer, MySql, Postgres Caching Stores Coherence , Redis, Gemfire Full-‐text Stores Lucene, SOLR, ElasticSearch Key/Value Stores Hbase, Cassandra, Riak, Dynamo Document Stores Marklogic, mongoDB, Cloudant, DocumentDB Couchbase

Couchbase Architecture Single Node 12

©2015 Couchbase Inc. 13 Couchbase Architecture • Data Service – builds and maintains Distributed secondary indexes (MapReduce Views) • Indexing Engine – builds and maintains Global Secondary Indexes • Query Engine – plans, coordinates, and executes queries against either Global or Distributed indexes • Cluster Manager – configuration, heartbeat, statistics, RESTful Management interface

©2015 Couchbase Inc. 16 Auto sharding – Bucket and vBuckets vB Data buckets vB 1 ….. 1024 Virtual buckets § A bucket is a logical, unique key space § Multiple buckets can exist within a single cluster of nodes § Each bucket has active and replica data sets (1, 2 or 3 extra copies) § Each data set has 1024 Virtual Buckets (vBuckets) § Each vBucket contains 1/1024th portion of the data set § vBuckets do not have a fixed physical server location § Mapping between the vBuckets and physical servers is called the cluster map § Document IDs (keys) always get hashed to the same vbucket § Couchbase SDK’s lookup the vbucket -‐> server mapping

©2015 Couchbase Inc. 20 ACTIVE ACTIVE ACTIVE REPLICA REPLICA REPLICA Couchbase Server 1 Couchbase Server 2 Couchbase Server 3 Basic Operation SHARD 5 SHARD 2 SHARD 9 SHARD SHARD SHARD SHARD 4 SHARD 7 SHARD 8 SHARD SHARD SHARD SHARD 1 SHARD 3 SHARD 6 SHARD SHARD SHARD SHARD 4 SHARD 1 SHARD 8 SHARD SHARD SHARD SHARD 6 SHARD 3 SHARD 2 SHARD SHARD SHARD SHARD 7 SHARD 9 SHARD 5 SHARD SHARD SHARD

©2015 Couchbase Inc. 21 Add Nodes to Cluster ACTIVE ACTIVE ACTIVE REPLICA REPLICA REPLICA Couchbase Server 1 Couchbase Server 2 Couchbase Server 3 ACTIVE ACTIVE REPLICA REPLICA Couchbase Server 4 Couchbase Server 5 SHARD 5 SHARD 2 SHARD SHARD SHARD 4 SHARD SHARD SHARD 1 SHARD 3 SHARD SHARD SHARD 4 SHARD 1 SHARD 8 SHARD SHARD SHARD SHARD 6 SHARD 3 SHARD 2 SHARD SHARD SHARD SHARD 7 SHARD 9 SHARD 5 SHARD SHARD SHARD SHARD 7 SHARD SHARD 6 SHARD SHARD 8 SHARD 9 SHARD READ/WRITE/UPDATE

©2015 Couchbase Inc. 22 Fail Over Node ACTIVE ACTIVE ACTIVE REPLICA REPLICA REPLICA Couchbase Server 1 Couchbase Server 2 Couchbase Server 3 ACTIVE ACTIVE REPLICA REPLICA Couchbase Server 4 Couchbase Server 5 SHARD 5 SHARD 2 SHARD SHARD SHARD 4 SHARD SHARD SHARD 1 SHARD 3 SHARD SHARD SHARD 4 SHARD 1 SHARD 8 SHARD SHARD SHARDSHARD 6 SHARD 2 SHARD SHARD SHARD SHARD 7 SHARD 9 SHARD 5 SHARD SHARD SHARD SHARD 7 SHARD SHARD 6 SHARDSHARD 8 SHARD 9 SHARD SHARD 3 SHARD 1 SHARD 3 SHARD

©2015 Couchbase Inc. 23 Modern Architecture – Multi-Dimensional Scaling MDS is the architecture that enables independent scaling of data, query, and indexing workloads while being managed as one cluster.

Cross Datacenter Replication (XDCR) 27

©2015 Couchbase Inc. 28 XDCR: Cross Data Center Replication § Application can access both clusters (master – master) § Scales out linearly § Within a cluster operations are strongly consistent and you can read-‐ your-‐own-‐write. Between clusters mutations are eventually consistent.

©2015 Couchbase Inc. 29 Memory-‐to-‐memory, topology aware replication New York San Francisco SF Server Cluster Couchbase Server 1 MEMORY DISK Couchbase Server 2 MEMORY DISK Couchbase Server 3 MEMORY DISK NYC Server Cluster Couchbase Server 1 MEMORY DISK Couchbase Server 2 MEMORY DISK Couchbase Server 3 MEMORY DISK Couchbase Server 4 MEMORY DISK USE CASES § Access by Localization § Active-‐Active § Active-‐Passive § Disaster Recovery § BI environment § Test environment

Developing an Application 31

©2015 Couchbase Inc. 32 Languages and Interfaces for Couchbase § Official SDKs – Java – .NET – Node.js – Python § For each of these we have – Full Document support – Interoperability – Common Programming Model Others: Erlang, Perl, TCL, Clojure, Scala – PHP – C – Go – Ruby JDBC and ODBC

©2015 Couchbase Inc. 38 Reference Documents for Lookups 38 § Lookup documents which reference the primary one § PROS § High Performance § Extremely scalable § Immediately consistent § CONS § Needs to be maintained by the application § GSI is a viable alternative § PROS § No need for Referential integrity § Good performance § CONS § Not immediately consistent -‐ but can optional wait for index updates (READ YOUR OWN WRITES)

©2015 Couchbase Inc. 39 Compound keys: example u::1001 { "name": "Matthew Revell", "email": "matthew@couchbase.com", "address": "11-21 Paul Street", "city": "London", "postCode": "EC2A 4JU", "telephone": "44-20-3837-9130", "orders": [ 1, 9, 698, 32 ], “productsViewed”: [8, 33, 99, 100] }

©2015 Couchbase Inc. 40 Compound keys: example u::1001 { "name": "Matthew Revell", "email": "matthew@couchbase.com", "address": "11-21 Paul Street", "city": "London", "postCode": "EC2A 4JU", "telephone": "44-20-3837-9130", "orders": [ 1, 9, 698, 32 ] } u::1001::productsviewed { "productsList": [ 8, 33, 99, 100 ] }

©2015 Couchbase Inc. 41 Compound keys: example u::1001 { "name": "Matthew Revell", "email": "matthew@couchbase.com", "address": "11-21 Paul Street", "city": "London", "postCode": "EC2A 4JU", "telephone": "44-20-3837-9130", "orders": [ 1, 9, 698, 32 ] } u::1001::productsviewed { "productsList": [ 8, 33, 99, 100 ] } p::8 { id": 1, "name": "T-shirt", "description": "Red Couchbase shirt", "quantityInStock": 99, "image": "tshirt.jpg” }

©2015 Couchbase Inc. 42 Compound keys: example u::1001 { "name": "Matthew Revell", "email": "matthew@couchbase.com", "address": "11-21 Paul Street", "city": "London", "postCode": "EC2A 4JU", "telephone": "44-20-3837-9130", "orders": [ 1, 9, 698, 32 ] } u::1001::productsviewed { "productsList": [ 8, 33, 99, 100 ] } p::8 { id": 1, "name": "T-shirt", "description": "Red Couchbase shirt", "quantityInStock": 99 } p::8::img “http://someurl.com/tshirt.jpg”

Couchbase Query (N1QL) N1QL Introduction

©2015 Couchbase Inc. 45 Why SQL for JSON? JSON Documents Provide RichStructure (Noassembly) StructureEvolution (Flexibleschema,easytochange) SQL Provides Generalqueryfunctionality Queryacrossrelationships Why N1QL? Mostdevelopersalreadyknow SQL Noneedforcomplexquery frameworks

©2015 Couchbase Inc. 46 SELECT § Standard SELECT pipeline – SELECT, FROM, WHERE, GROUP BY, ORDER BY, LIMIT, OFFSET § Queries across relationships – JOINs – Subqueries – NEST — a JOIN that embeds child objects within their parent – UNNEST — a JOIN that surfaces nested objects as top-‐level data § Aggregation § Set operators – UNION, INTERSECT, EXCEPT

©2015 Couchbase Inc. 47 Indexing § CREATE / DROP INDEX § Two types of indexes – View indexes – GSI indexes (global secondary indexes) § Can index any data expression – Nested / complex expressions – Computed expressions § EXPLAIN

©2015 Couchbase Inc. 48 Data writes § UPDATE … WHERE … – Partial updates; deep updates § DELETE … WHERE … – Deeply nested conditions § INSERT … VALUES …; INSERT … SELECT … – Bulk insert; transfer and transformation § MERGE – INSERT or UPDATE; ETL support

©2015 Couchbase Inc. 49 Document-‐oriented Extensions § Nested – Paths—user.profile.email, children[0], children[0:2] – NEST, UNNEST – Ranging—EVERY child.age > 5 FOR child IN children END – Transformations—SELECT {“name”: first_name || last_name} § Non-‐uniform – IS MISSING – Type checking and conversion § Distributed – Direct lookup—USE KEYS – Efficient joins—ON KEYS

©2015 Couchbase Inc. 50 Expressions ©2014 Couchbase, Inc. 50 Expressions Literals q Primitives [ 0, ‘hello’, TRUE ] q NULL Operators q Arithmetic [ +, -‐, *, /, % ] q Logical [ AND, OR, NOT ] q Comparison [ <, <=, =, !=, >=, >, BETWEEN, IS NULL ] q Pattern matching [ LIKE ] q Conditional [ CASE ] Scalar functions q Numeric [ trigonometric, ROUND, TRUNC, … ] q String [ UPPER, LOWER, TRIM, SUBSTR, … ] q Date [ string and numeric dates, NOW, date arithmetic, … ] Aggregate functions q MIN, MAX, SUM, AVG, COUNT [ DISTINCT ] Subqueries q Subqueries are full expressions

©2015 Couchbase Inc. 51 Document-‐Oriented Expression Features ©2014 Couchbase, Inc. 51 Features Ranging over collections WHERE ANY c IN children SATISFIES c.age > 10 END WHERE EVERY r IN ratings SATISFIES r > 3 END Mapping with filtering ARRAY c.name FOR c IN children WHEN c.age > 10 END Deep traversal and update WHERE ANY node WITHIN request SATISFIES node.type = “xyz” END UPDATE doc SET c.name = Title(c.name) FOR c WITHIN doc END Dynamic Construction SELECT { “a”: expr1, “b”: expr2 } AS obj1, name FROM … // Dynamic object SELECT [ a, b ] FROM … // Dynamic array Nested sourcing SELECT * FROM a.b.c … // Select from nested objects

©2015 Couchbase Inc. 54 Develop with Agility With Couchbase Server, you can Develop Applications with Agility. Here’s why: Easier, Faster Development Flexible Data Modeling Powerful Querying SQL Integration & Migration Big Data Integration Mobile / IoT

©2015 Couchbase Inc. 55 Operate at Any Scale With Couchbase Server, you can deploy, manage, and scale apps without limits. Here’s why: Elastic Scalability Consistent High Performance Always-on Availability Multi-Data Center Deployment Simple, Powerful Administration Enterprise Grade Security

©2015 Couchbase Inc. 57 Additional Resources 57 § Couchbase Labs: https://github.com/couchbaselabs § Sample Applications: § https://github.com/couchbaselabs?utf8=%E2%9C%93&query=try § https://github.com/couchbaselabs?utf8=%E2%9C%93&query=beer § General Docs: http://docs.couchbase.com § Query Portal: http://query.couchbase.com § Blog: http://blog.couchbase.com § Forum: http://forums.couchbase.com

Manuel Hurtado. Couchbase paradigma4oct

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Manuel Hurtado. Couchbase paradigma4oct