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![Indexing Employee Documents
● Megacorp : The index name
● Employee : The type name
● 1 : The ID of this particular employee
PUT /megacorp/employee/1
{
"first_name" : "John",
"last_name" : "Smith",
"age" : 25,
"about" : "I love to go rock climbing",
"interests": [ "sports", "music" ]
}
PUT /megacorp/employee/2
{
"first_name" : "Jane",
"last_name" : "Smith",
"age" : 32,
"about" : "I like to collect rock albums",
"interests": [ "music" ]
}
PUT /megacorp/employee/3
{
"first_name" : "Douglas",
"last_name" : "Fir",
"age" : 35,
"about" : "I like to build cabinets",
"interests": [ "forestry" ]
}](https://image.slidesharecdn.com/01gettingstarted-161004081032/75/01-ElasticSearch-Getting-Started-10-2048.jpg)
![Retrieving a Document
● GET /megacorp/employee/1
{
"_index": "megacorp",
"_type": "employee",
"_id": "1",
"_version": 2,
"found": true,
"_source": {
"first_name": "John",
"last_name": "Smith",
"age": 25,
"about": "I love to go rock climbing",
"interests": [
"sports",
"music"
]
}
}](https://image.slidesharecdn.com/01gettingstarted-161004081032/75/01-ElasticSearch-Getting-Started-11-2048.jpg)
Uploaded byOpenThink Labs
01 ElasticSearch : Getting Started
This document provides an introduction to using ElasticSearch. It discusses installing ElasticSearch and making API calls. It demonstrates indexing employee documents with fields like name, age, interests. It shows how to search for documents by field values or full text, do phrase searches, and highlight search terms. It also introduces analytics capabilities like aggregations to analyze field values.
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01 ElasticSearch : Getting Started
- 1.
- 2. Uji Coba Instalasi ●curl 'http://localhost:9200/?pretty' ● http://localhost:9200/_plugin/marvel/ ● http://localhost:9200/_plugin/marvel/sense/
- 3. Talking to Elasticsearch ●Java API ● RESTful API with JSON over HTTP curl -X<VERB> '<PROTOCOL>://<HOST>/<PATH>?<QUERY_STRING>' -d '<BODY>' curl -XGET 'http://localhost:9200/_count?pretty' -d ' { "query": { "match_all": {} } } '
- 4.
- 5.
- 6.
- 7. Let's Build anEmployee Directory ● Enable data to contain multi value tags, numbers, and full text. ● Retrieve the full details of any employee ● Allow structured search, such as finding employees over the age of 30 ● Allow simple full-text search and more-complex phrase searches ● Return highlighted search snippets from the text in the matching documents ● Enable management to build analytic dashboards over the data
- 8. Indexing Employee Documents ●Relational DB Databases Tables Rows⇒ ⇒ ⇒ Columns⇒ ● Elasticsearch Indices Types Documents⇒ ⇒ ⇒ Fields⇒
- 9. Index Versus IndexVersus Index ● Index (noun) ● Index (verb) ● Inverted index
- 10. Indexing Employee Documents ●Megacorp : The index name ● Employee : The type name ● 1 : The ID of this particular employee PUT /megacorp/employee/1 { "first_name" : "John", "last_name" : "Smith", "age" : 25, "about" : "I love to go rock climbing", "interests": [ "sports", "music" ] } PUT /megacorp/employee/2 { "first_name" : "Jane", "last_name" : "Smith", "age" : 32, "about" : "I like to collect rock albums", "interests": [ "music" ] } PUT /megacorp/employee/3 { "first_name" : "Douglas", "last_name" : "Fir", "age" : 35, "about" : "I like to build cabinets", "interests": [ "forestry" ] }
- 11. Retrieving a Document ●GET /megacorp/employee/1 { "_index": "megacorp", "_type": "employee", "_id": "1", "_version": 2, "found": true, "_source": { "first_name": "John", "last_name": "Smith", "age": 25, "about": "I love to go rock climbing", "interests": [ "sports", "music" ] } }
- 12. Search Lite ● GET/megacorp/employee/_search ● GET /megacorp/employee/_search?q=last_name:Smith
- 13. Search with QueryDSL GET /megacorp/employee/_search { "query" : { "match" : { "last_name" : "Smith" } } }
- 14. More-Complicated Searches GET /megacorp/employee/_search { "query": { "filtered" : { "filter" : { "range" : { "age" : { "gt" : 30 } } }, "query" : { "match" : { "last_name" : "smith" } } } } }
- 15. Full-Text Search GET /megacorp/employee/_search { "query": { "match" : { "about" : "rock climbing" } } }
- 16. Phrase Search GET /megacorp/employee/_search { "query": { "match_phrase" : { "about" : "rock climbing" } } }
- 17. Highlighting Our Searches GET/megacorp/employee/_search { "query" : { "match_phrase" : { "about" : "rock climbing" } }, "highlight": { "fields": { "about":{} } } }
- 18. Analytics GET /megacorp/employee/_search { "aggs": { "all_interests":{ "terms": { "field": "interests" } } } } GET /megacorp/employee/_search { "query": { "match": { "last_name": "smith" } }, "aggs": { "all_interests": { "terms": { "field": "interests" } } } } GET /megacorp/employee/_search { "aggs" : { "all_interests" : { "terms" : { "field" : "interests" }, "aggs" : { "avg_age" : { "avg" : { "field" : "age" } } } } } }
- 19. Referensi ● ElasticSearch, TheDefinitive Guide, A Distributed Real-Time Search and Analytics Engine, Clinton Gormely & Zachary Tong, O’Reilly