1. Deep Dive intoDeep Dive into Shivansh Srivastava Software
Consultant Knoldus Software LLP Shivansh Srivastava Software
Consultant Knoldus Software LLP
2. AgendaAgenda Using Views And Indexes. Couchbase 4.0 Beta
Main Features Of Couchbase 4.0 Demo Using Views And Indexes.
Couchbase 4.0 Beta Main Features Of Couchbase 4.0 Demo
3. Using Views And Indexes.Using Views And Indexes.
4. Couchbaseviewsenableindexingandqueryingofdata.
Couchbaseviewsenableindexingandqueryingofdata. Views And
Indexes.
5. Views EngineViews Engine
6. Creating A View.Creating A View.
7. Creating a View.
8. Map FunctionMap Function
9. Results from ViewsResults from Views
10. View Query ParametersView Query Parameters
11. Understanding StaleUnderstanding Stale
12. Built In ReducesBuilt In Reduces
13. Couchbase 4.0 BetaCouchbase 4.0 Beta
14. Main Features Of Couchbase 4.0 BetaMain Features Of
Couchbase 4.0 Beta Multi Dimensional Scaling Global Secondary
Indexing N1Ql (Nickel Query)
15. Multi Dimensional ScalingMulti Dimensional Scaling
16. Multi Dimensional ScalingMulti Dimensional Scaling
Question: Few million people are looking for a setup to efficiently
live and interact. What is the most efficient way to build this
infra? A) Build one giant high-rise? B) Build some mid-rises? C)
Build many single-family homes
17. Scaling UpScaling Up Build one big high-rise Vertical
Scaling Cluster processors hyper-threading to cores Locally
partition workload among processors Communicate over memory Great
for fast processing but limited in scalability and elasticity
18. Scaling OutScaling Out Build a large community of
single-family houses Horizontal Scaling Cluster commodity HW
Partition workload among nodes Communicate over network Great for
scaling and elasticity but slower communication
19. Multi Dimensional ScalingMulti Dimensional Scaling The
Solution to this problem is Multi Dimensional Scaling(MDS). What is
Multi-Dimensional Scaling? MDS is the architecture that enables
independent scaling of data, query and indexing workloads.
20. Multi Dimensional ScalingMulti Dimensional Scaling
Independent zones for Query, Index and Data Services Independent
Scalability for Best Computational Capacity per Service Heavier
indexing (index more fields) : scale up index service nodes More
RAM for query processing: scale up query service nodes
21. Global Secondary IndexingGlobal Secondary Indexing
22. Global Secondary IndexingGlobal Secondary Indexing What are
Global Secondary Indexes? High performance indexes for low latency
queries with powerful caching, storage and independent placement.
Power of GSI: Fully integrated into N1QL Query Optimization and
Execution Independent Index Distribution for Limiting
scatter-gather Independent Scalability with Index Service
23. Global Secondary IndexingGlobal Secondary Indexing
24. GSI vs ViewsGSI vs Views
25. N1QL (Nickel) QueryN1QL (Nickel) Query
26. Steps For Running N1QLSteps For Running N1QL Step 1: Start
the Cbq engine for datastore and query. For example: Ubuntu users
can start it by executing these two commands on the terminal cd
/opt/couchbase/bin ./cbq-engine -datastore
http://Administrator:[email protected]:8091
27. Steps For Running N1QLSteps For Running N1QL Step 2: In
other Terminal Start the Cbq engine for starting interactive query
shell. For example: Ubuntu users can start it by executing these
two commands on the terminal Cd /opt/couchbase/bin ./cbq
-engine=http://localhost:8093
28. Enabling Query Parameter.Enabling Query Parameter. To start
querying the couchbase from your code you must first the the Query
by setting it to 'true' For Example: For Java or Scala Users:
System.setProperty("com.couchbase.queryEnabled", "true") Add this
line where you are creating your cluster.
29. Querying Couchbase Using NickelQuerying Couchbase Using
Nickel Here is a sample of executing a Nickel query in
couchase.
