This document provides a 3 sentence summary of an Elasticsearch meetup in Mexico City in April 2016. It introduces Elasticsearch as a open-source search and analytics engine, discusses its features including real-time data, being massively distributed and schema-free, and provides examples of creating an index, mapping types, indexing documents, and searching in Elasticsearch using HTTP requests.

1. Elasticsearch
Mexico City JVM Group
April 2016

2. !Gracias por estar aqui¡

3. ¡El meetup con mas
asistencia de la historia!

4. What is the topic tonight?

5. Elastic search?

6. NO

7. Elastic Search?

8. NO

9. ElasticSearch?

10. NO

11. @superserch?

12. NO

13. Elasticsearch

14. YES

15. Search

16. Do I have to elaborate
why search is important?

17. A little history…

18. Lucene History
• Douglass Read "Doug" Cutting wrote Lucene in 1999
• Doug also is the author of Hadoop
• In Lucene other projects came to life
• Mahout
• Tika
• Nutch

19. Lucene?

20. • Lucene is an open-source Java full-text search
library which makes it easy to add search
functionality to an application or website.

21. Index

22. Query

23. Inverted index
• Lucene creates a data structure where it keeps a
list of where each word belongs.

24. Lucene-Based projects
• Solr
• Compass
• Elasticsearch
• Hibernate search

25. Elasticsearch
You Know, for Search.

26. Features
• Real-Time Data. I (Domingo) say near Real-Time Data.
• Massively Distributed
• High Availability
• Full-Text Search
• Document-Oriented
• Schema-Free
• Developer-Friendly, RESTful API
• Extensible via plugins

27. Concepts
• Cluster
• Node
• Index
• Shard & Replica
• Type
• Mapping
• Document

28. How data is
organized in Elasticsearch

29. Nodes & shards

30. Indexing documents

31. Sharding is crucial
• Shard is a physical Lucene index
• # documents in a Lucent index is 2 billion docs.
• When you create a index you have to declare the
# shards, you can’t change later. Beware!
• Don’t try to over-sharding your index! Beware!

32. Distributed indexing

33. URL
http://localhost:9200/{index}/{type}/{document_id}

34. HTTPie for the samples

35. Creating an index
$ http put :9200/my_index/ settings:='{ "index" : { "number_of_shards" : 3, "number_of_replicas" : 0 } }'
PUT /my_index/ HTTP/1.1
Accept: application/json
Accept-Encoding: gzip, deflate
Connection: keep-alive
Content-Length: 73
Content-Type: application/json
Host: localhost:9200
User-Agent: HTTPie/0.9.3
{
"settings": {
"index": {
"number_of_replicas": 0,
"number_of_shards": 3
}
}
}
HTTP/1.1 200 OK
Content-Length: 21
Content-Type: application/json; charset=UTF-8
{
"acknowledged": true
}

36. Creating a type
$ http put :9200/my_index/_mapping/my_document properties:='{ "user_name": { "type": "string" } }' -v
PUT /my_index/_mapping/my_document1 HTTP/1.1
Accept: application/json
Content-Length: 49
Content-Type: application/json
{
"properties": {
"user_name": {
"type": "string"
}
}
}
HTTP/1.1 200 OK
Content-Length: 21
Content-Type: application/json; charset=UTF-8
{
"acknowledged": true
}

37. Indexing$ http :9200/my_index/my_document user_name="Domingo Suarez" -v
POST /my_index/my_document1 HTTP/1.1
Content-Length: 31
Content-Type: application/json
{ "user_name": "Domingo Suarez” }
HTTP/1.1 201 Created
Content-Length: 149
Content-Type: application/json; charset=UTF-8
{
"_id": "AVRaEeBK3Lbw2oDzSIWN",
"_index": "my_index",
"_shards": {
"failed": 0,
"successful": 1,
"total": 1
},
"_type": "my_document1",
"_version": 1,
"created": true
}

38. Search $ http :9200/my_index/my_document/_search?q=user_name:Domingo
HTTP/1.1 200 OK
Content-Length: 657
Content-Type: application/json; charset=UTF-8
{
"_shards": {
"failed": 0,
"successful": 3,
"total": 3
},
"hits": {
"hits": [
{
"_id": "AVRaEdPJ3Lbw2oDzSIWM",
"_index": "my_index",
"_score": 0.625,
"_source": {
"user_name": "Domingo Suarez"
},
"_type": "my_document1"
}
],
"max_score": 0.625, "total": 1
},
"timed_out": false,
"took": 5
}