This is the first part of the presentation about elasticsearch

1. Elasticsearch
(Presentation 01)
By
Maruf Hassan
Email: maruf571@gmail.com

2. Contents
● Introduction
● Installation
● Configuration
● Tools(plugin)
● Terms used in Elasticsearch
● Talking with Elasticsearch
● Indexing data
● Retrieving data

3. Introduction
What is Elasticsearch?
● Elasticsearch is an open-source search engine
● Elasticsearch is written in Java
● Built on top of Apache Lucene™
● A distributed real-time document store where
every field is indexed and searchable
● A distributed search engine with real-time
analytics

4. Installation
Setup
● Download zip file for elasticsearch web site
(https://www.elastic.co/downloads/elasticsearch)
● Unzip it anywhere in you pc
Run
● Go to unzip directory & run the following command
./bin/elasticsearch
Test
● To test installation hit on browser @ http://localhost:9200/?pretty or
curl 'http://localhost:9200/?pretty'
“You Know, for Search” Yahoo! everything is file :)

5. Configuration
● elasticsearch.yml file is the main configuration
file in the config directory
● Need restart Elasticsearch to perform update
configuration(if you edit elasticsearch.yml )

6. Tools(plugin)
Installation
● Marvel (plugin) is a monitoring tools, to install
./bin/plugin -i elasticsearch/marvel/latest
● Sense is interactive console inside Marvel.(I like it very much)
● Elasticsearch-head is a document browser, to install
./bin/plugin -install mobz/elasticsearch-head
Run
● To run marvel hit brouwser @ http://localhost:9200/_plugin/marvel/
● To run sence hit brouwser @ http://localhost:9200/_plugin/marvel/sense/
● To run head hit brouwser @ http://localhost:9200/_plugin/head/

7. Terms used in Elasticsearch
● node: running instance of Elasticsearch
● cluster: group of nodes with the same cluster
name
● elasticsearch = relational DB
● indices = databases
● types = tables
● documents = rows

8. Terms used in Elasticsearch
● fields = columns
● index (noun) = like a database in a traditional relational
database
● Index (verb) = to index a document is to store a document
in an index (noun)
● Inverted index = relational databases add an index, such
as a B-tree index, to specific columns in order to improve
the speed of data retrieval. Elasticsearch and Lucene use
a structure called an inverted index for exactly the same
purpose.

9. Talking to Elasticsearch
Two way for java. Node client & Transport client
1. Node client: Work as a node in local cluster, but don’t hold any data
2. Transport client: Send request to remote cluster, don’t join
One way for all
● RESTful API with JSON over HTTP
Port
● Both Java clients talk to the cluster over port 9300
● All other languages can communicate with Elasticsearch over port 9200
using RESTful API

10. Indexing data
● PUT verb used for indexing(inserting data)
●
URL path contains three pieces of information
index_name/type_name/id_of_document
● PUT body contain the document as a json
Example:
PUT /cefalo/employee/1
{
"first_name" : "Maruf",
"last_name" : "Hassan",
"age" : 28,
"about" : "Happy to help",
"interests": [ "science", "music", "internet" ]
}

11. Retrieve data
Two way to retrieve data from Elasticsearch. Search Lite & Query DSL
Search Lite
● allows us to build ad hoc searches
● parameters to be passed in the query string
● Used only for test environment
Query DSL
● allows us to build much more complicated, robust queries
● expects a JSON request body and uses a rich search language called the
query DSL
● Used for production environment

12. Retrieve data(Search Lite)
● Search for all employees in the index cefalo
GET /cefalo/employee/_search
● searching for employees with their last name in
cefalo index
GET /cefalo/employee/_search?
q=last_name:hassan

13. Retrieve data(Query DSL)
● Search for all employees in the cefalo index
GET /cefalo/employee/_search{
}
● Searching for employees with their last name in the cefalo index
GET /cefalo/employee/_search
{
"query" : {
"match" : {
"last_name" : "Hassan"
}
}
}

14. Thanks
&