Elasticsearch is an open source, distributed, real-time search and analytics engine. It allows storing and searching of documents of any schema in JSON format. Documents are indexed to allow fast searching, and Elasticsearch can scale horizontally and remain highly available across many servers. Queries can be performed using RESTful APIs to search specific fields, run full-text searches across all fields, or filter results.

1. Elastic Search
James Chen

2. Intro
- ElasticSearch is
- open source search engine
- built on top of Apache Lucene
- a distributed real-time document store
- every field is indexed and searchable
- distributed search engine with real-time analytics
- excellent scaling capabilities
- app can easily communicate with server
- RESTful API
- web client

3. ES V.S. Relational DB
- Index = database
- types = tables
- documents = rows
- fields = columns

4. Document Oriented
- everything is JSON
- standard format for NoSQL
- simple, concise, and easy to read
- store your data exactly how you need it
- say goodbye to joining tables

5. Indexing Documents
- PUT = to index a document
- Ex: PUT /company/employee/1
index name type name
document id
{
“name” : “John Smith”,
“age” : “32”,
“title” : “Operations Manager”,
}

6. Retrieving Documents
- simply execute http GET request
- specify document address
- index, type, ID
- Ex: GET company/employee/1

7. Simple Queries
- GET request
- _search?[field]:[value]
- Ex: /company/employee/_search?q=name:
John

8. Full Text Queries
- GET request
- _search?q=[value]
- Ex: /company/employee/_search?q=john
- this would return all documents where any of the
fields contains the value being queried

9. Empty Queries
- _search
- returns all documents

10. Filters
- term
- bool
- range
- missing
- empty
{
“filter” : {
“missing” : {
“field” : “pn”
}
}
}

11. References
- http://www.elastic.
co/guide/en/elasticsearch/guide/current/in
dex.html