This document provides an overview of Elasticsearch including what it does, use cases, its history and growth. It describes the Elastic Stack and components like Logstash, Kibana, and Beats. It explains key Elasticsearch concepts such as clusters, nodes, indexes, types, documents, shards, and replication. It also covers search, aggregations, and how to install Elasticsearch on AWS.

1. Agenda
• What it does?
• Use case examples
• What is Elasticsearch?
• History & growth
• Elsatic Stack
• Elastic Cloud and X-Pack
• Cluster, Node, Index, Type, Document
• Primary and replica shards
• Search & Aggregations
• Elastic Stack installation on AWS

2. Elasticsearch
What it Does?
• Stores Data
• Search Data
• Perform Analytics on searched data
– Facets / Aggregations
– Nested Aggregations

3. Elasticsearch
Use Cases / Customers
https://www.elastic.co/use-cases
Example Use Cases
https://www.booking.com (store, search, aggregations/Facets)
https://en.wikipedia.org (Full Text search)
http://www.blubolt.com/customers (Blue commerce - B2B/B2C)

4. Elasticsearch
• Search Engine/Analytics
• Horizontally scalable ( Scale Out)
• Near real time
• Highly Available
• JSON REST API
• Distributed System
• Built over Lucene (Java Library)
• Log and data analysis, full text search, alerting,
recommendations, classifications,

5. History of Elasticsearch
• Compass was Created by Shay Banon in 2004
• Rewritten as Elasticsearch in 2010
• Company was formed in 2012
• Elasticsearch 5.0 - Oct 2016
• Now all components will have same version
no.

6. Elasticsearch Growth

7. Elastic Stack Or ELK Stack (Open Source)
• Elasticsearch (To store data)
• Logstash (Data shipper with input, filter and output,
Required Jvm to run, Built in JRuby)
• Kibana (For Visulization, user interface into Elastic Stack)
• Beats (Light Weight data shipper, Written in Go Language)
– Metricbeat
– Filebeat
– Winlogbeat
– Packetbeat
– And Much more

8. Elastic Cloud & X-Pack (Subscriptions)
• Elastic Cloud (14 days free trial)
• X-Pack
–Security
–Alerting
–Monitoring
–Reporting
–Graphs

9. Cluster
• A cluster is a combination of one or more
running instances of elasticsearch called
node(s) or server(s).
• Cluster hold data on one node or across
different nodes
• Every cluster must have a unique name
• New instance of elasticsearch will find cluster
by its unique name
• By default it's name is "Elasticsearch"

10. Nodes
• Node is single running instance of elastic
search on a server.
• One node per server ( recommended )
• Part of cluster
• Stores data
• Every node has a name to identify it
• By default every node is configured to join
cluster "Elasticsearch"

11. Index & Indices
• Collection of documents
• Similar characteristics
• Every index have a name ( must be lowercase)
• Name is use to refer to index when performing
– Indexing
– Search
– Update
– delete
• Set of shards

12. Type
• Exists within index
• One index can have multiple types
• Group documents of same logic
• Logical partition of index
• Examples
– User data
– Monitoring data
– Logs data

13. Document(s)
• Basic unit of information to index
• Contains data
• JSON objects ( JavaScript Object Notation )
• Examples
–Document of single employee
–Document of single employer
–Document of single product

14. Shard(s) & Replication
• Every index is subdivided into shards
• Default no of shards is 5
• We can specify no of shards at the time of creation of
index
• Shards can live on one node or can be distributed
across node to utilize system resources
• Shards can be primary or replica
• Each document in index live on a single shard
• Once index is created, we can't change no of shards
• Replicas can be changed dynamically

15. Scale Up & Scale out
• Elasticsearch works on scale out
Node 1
P1
P2
Node 2
R0
R1
Node 3
P0
R2
Cluster

16. Search
• Queries
– Unstructured data
– Free text search
– results are based on relevancy score
• Filter
– Structured data
– No relevancy scoring, Its either yes or no
– Fast result
• Combination of Queries & Filter
– For complex scenarios

17. Aggregations (Slice & dice data)
• Bucket (Date Histogram, Term, Ranges)
• Nested Buckets
• Metric (Max, Min, Average, Sum)
• Matrix
• Pipeline

18. # Guide {https://www.elastic.co/learn }